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<section id="numpy-random-generator-random">
<h1>numpy.random.Generator.random<a class="headerlink" href="#numpy-random-generator-random" title="Link to this heading">#</a></h1>
<p>method</p>
<dl class="py method">
<dt class="sig sig-object py" id="numpy.random.Generator.random">
<span class="sig-prename descclassname"><span class="pre">random.Generator.</span></span><span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</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="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">np.float64</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out</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.random.Generator.random" title="Link to this definition">#</a></dt>
<dd><p>Return random floats in the half-open interval [0.0, 1.0).</p>
<p>Results are from the “continuous uniform” distribution over the
stated interval. To sample <span class="math notranslate nohighlight">\(Unif[a, b), b > a\)</span> use <a class="reference internal" href="numpy.random.Generator.uniform.html#numpy.random.Generator.uniform" title="numpy.random.Generator.uniform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">uniform</span></code></a>
or multiply the output of <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> by <code class="docutils literal notranslate"><span class="pre">(b</span> <span class="pre">-</span> <span class="pre">a)</span></code> and add <code class="docutils literal notranslate"><span class="pre">a</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="p">(</span><span class="n">b</span> <span class="o">-</span> <span class="n">a</span><span class="p">)</span> <span class="o">*</span> <span class="n">random</span><span class="p">()</span> <span class="o">+</span> <span class="n">a</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>size</strong><span class="classifier">int or tuple of ints, optional</span></dt><dd><p>Output shape. If the given shape is, e.g., <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n,</span> <span class="pre">k)</span></code>, then
<code class="docutils literal notranslate"><span class="pre">m</span> <span class="pre">*</span> <span class="pre">n</span> <span class="pre">*</span> <span class="pre">k</span></code> samples are drawn. Default is None, in which case a
single value is returned.</p>
</dd>
<dt><strong>dtype</strong><span class="classifier">dtype, optional</span></dt><dd><p>Desired dtype of the result, only <a class="reference internal" href="../../arrays.scalars.html#numpy.float64" title="numpy.float64"><code class="xref py py-obj docutils literal notranslate"><span class="pre">float64</span></code></a> and <a class="reference internal" href="../../arrays.scalars.html#numpy.float32" title="numpy.float32"><code class="xref py py-obj docutils literal notranslate"><span class="pre">float32</span></code></a> are supported.
Byteorder must be native. The default value is np.float64.</p>
</dd>
<dt><strong>out</strong><span class="classifier">ndarray, optional</span></dt><dd><p>Alternative output array in which to place the result. If size is not None,
it must have the same shape as the provided size and must match the type of
the output values.</p>
</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">float or ndarray of floats</span></dt><dd><p>Array of random floats of shape <a class="reference internal" href="../../generated/numpy.size.html#numpy.size" title="numpy.size"><code class="xref py py-obj docutils literal notranslate"><span class="pre">size</span></code></a> (unless <code class="docutils literal notranslate"><span class="pre">size=None</span></code>, in which
case a single float is returned).</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.random.Generator.uniform.html#numpy.random.Generator.uniform" title="numpy.random.Generator.uniform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">uniform</span></code></a></dt><dd><p>Draw samples from the parameterized uniform distribution.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="54a17204-3190-4b93-bdbd-7bcca48312ea">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('54a17204-3190-4b93-bdbd-7bcca48312ea','6320b28c-ba93-44a8-933c-6ac18893ec90','796d1e43-14b9-4040-b313-02fe8e604c46','../../../lite/tree/../notebooks/index.html?path=2ab769ff_542a_4bec_bca3_de7b2823a1c9.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">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">()</span>
<span class="go">0.47108547995356098 # random</span>
<span class="gp">>>> </span><span class="nb">type</span><span class="p">(</span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">())</span>
<span class="go"><class 'float'></span>
<span class="gp">>>> </span><span class="n">rng</span><span class="o">.</span><span class="n">random</span><span class="p">((</span><span class="mi">5</span><span class="p">,))</span>
<span class="go">array([ 0.30220482, 0.86820401, 0.1654503 , 0.11659149, 0.54323428]) # random</span>
</pre></div>
</div>
<p>Three-by-two array of random numbers from [-5, 0):</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="mi">5</span> <span class="o">*</span> <span class="n">rng</span><span class="o">.</span><span class="n">random</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="o">-</span> <span class="mi">5</span>
<span class="go">array([[-3.99149989, -0.52338984], # random</span>
<span class="go"> [-2.99091858, -0.79479508],</span>
<span class="go"> [-1.23204345, -1.75224494]])</span>
</pre></div>
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