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<section id="numpy-random-randomstate-rand">
<h1>numpy.random.RandomState.rand<a class="headerlink" href="#numpy-random-randomstate-rand" title="Link to this heading">#</a></h1>
<p>method</p>
<dl class="py method">
<dt class="sig sig-object py" id="numpy.random.RandomState.rand">
<span class="sig-prename descclassname"><span class="pre">random.RandomState.</span></span><span class="sig-name descname"><span class="pre">rand</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d1</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">dn</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.random.RandomState.rand" title="Link to this definition">#</a></dt>
<dd><p>Random values in a given shape.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>This is a convenience function for users porting code from Matlab,
and wraps <a class="reference internal" href="numpy.random.RandomState.random_sample.html#numpy.random.RandomState.random_sample" title="numpy.random.RandomState.random_sample"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random_sample</span></code></a>. That function takes a
tuple to specify the size of the output, which is consistent with
other NumPy functions like <a class="reference internal" href="../../generated/numpy.zeros.html#numpy.zeros" title="numpy.zeros"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.zeros</span></code></a> and <a class="reference internal" href="../../generated/numpy.ones.html#numpy.ones" title="numpy.ones"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.ones</span></code></a>.</p>
</div>
<p>Create an array of the given shape and populate it with
random samples from a uniform distribution
over <code class="docutils literal notranslate"><span class="pre">[0,</span> <span class="pre">1)</span></code>.</p>
<dl class="field-list">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>d0, d1, …, dn</strong><span class="classifier">int, optional</span></dt><dd><p>The dimensions of the returned array, must be non-negative.
If no argument is given a single Python float is returned.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl>
<dt><strong>out</strong><span class="classifier">ndarray, shape <code class="docutils literal notranslate"><span class="pre">(d0,</span> <span class="pre">d1,</span> <span class="pre">...,</span> <span class="pre">dn)</span></code></span></dt><dd><p>Random values.</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="../index.html#module-numpy.random" title="numpy.random"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random</span></code></a></dt><dd></dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="abfb0441-7cf9-44c6-af22-8174c4422525">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('abfb0441-7cf9-44c6-af22-8174c4422525','c5e80374-b4b2-4ec7-bd61-f8d97276f9da','0996f227-5ddd-4d4b-a6ef-4de988df7562','../../../lite/tree/../notebooks/index.html?path=8f167fbc_3774_4756_ab1d_5d567037bab9.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="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span>
<span class="go">array([[ 0.14022471, 0.96360618], #random</span>
<span class="go"> [ 0.37601032, 0.25528411], #random</span>
<span class="go"> [ 0.49313049, 0.94909878]]) #random</span>
</pre></div>
</div>
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