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<section id="numpy-random-generator-standard-exponential">
<h1>numpy.random.Generator.standard_exponential<a class="headerlink" href="#numpy-random-generator-standard-exponential" title="Link to this heading">#</a></h1>
<p>method</p>
<dl class="py method">
<dt class="sig sig-object py" id="numpy.random.Generator.standard_exponential">
<span class="sig-prename descclassname"><span class="pre">random.Generator.</span></span><span class="sig-name descname"><span class="pre">standard_exponential</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">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'zig'</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.standard_exponential" title="Link to this definition">#</a></dt>
<dd><p>Draw samples from the standard exponential distribution.</p>
<p><a class="reference internal" href="#numpy.random.Generator.standard_exponential" title="numpy.random.Generator.standard_exponential"><code class="xref py py-obj docutils literal notranslate"><span class="pre">standard_exponential</span></code></a> is identical to the exponential distribution
with a scale parameter of 1.</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>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>method</strong><span class="classifier">str, optional</span></dt><dd><p>Either ‘inv’ or ‘zig’. ‘inv’ uses the default inverse CDF method.
‘zig’ uses the much faster Ziggurat method of Marsaglia and Tsang.</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</span></dt><dd><p>Drawn samples.</p>
</dd>
</dl>
</dd>
</dl>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="7adafbcb-3e41-48d8-b829-3699859b6432">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('7adafbcb-3e41-48d8-b829-3699859b6432','afa467e7-3b91-4c34-b7f1-6cf2839906fa','c5b645f7-9be7-498e-96f6-6a8290e89d0f','../../../lite/tree/../notebooks/index.html?path=b73fd52c_6e63_458d_9f64_1c52e59eb516.ipynb','None')">Try it in your browser!</button></div><div class="try_examples_content docutils container">
<p>Output a 3x8000 array:</p>
<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">n</span> <span class="o">=</span> <span class="n">rng</span><span class="o">.</span><span class="n">standard_exponential</span><span class="p">((</span><span class="mi">3</span><span class="p">,</span> <span class="mi">8000</span><span class="p">))</span>
</pre></div>
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