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<section id="numpy-random-generator-spawn">
<h1>numpy.random.Generator.spawn<a class="headerlink" href="#numpy-random-generator-spawn" title="Link to this heading">#</a></h1>
<p>method</p>
<dl class="py method">
<dt class="sig sig-object py" id="numpy.random.Generator.spawn">
<span class="sig-prename descclassname"><span class="pre">random.Generator.</span></span><span class="sig-name descname"><span class="pre">spawn</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_children</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.random.Generator.spawn" title="Link to this definition">#</a></dt>
<dd><p>Create new independent child generators.</p>
<p>See <a class="reference internal" href="../parallel.html#seedsequence-spawn"><span class="std std-ref">SeedSequence spawning</span></a> for additional notes on spawning
children.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.25.0.</span></p>
</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>n_children</strong><span class="classifier">int</span></dt><dd></dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>child_generators</strong><span class="classifier">list of Generators</span></dt><dd></dd>
</dl>
</dd>
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt>TypeError</dt><dd><p>When the underlying SeedSequence does not implement spawning.</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="../bit_generators/generated/numpy.random.BitGenerator.spawn.html#numpy.random.BitGenerator.spawn" title="numpy.random.BitGenerator.spawn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random.BitGenerator.spawn</span></code></a>, <a class="reference internal" href="../bit_generators/generated/numpy.random.SeedSequence.spawn.html#numpy.random.SeedSequence.spawn" title="numpy.random.SeedSequence.spawn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random.SeedSequence.spawn</span></code></a></dt><dd><p>Equivalent method on the bit generator and seed sequence.</p>
</dd>
<dt><a class="reference internal" href="numpy.random.Generator.bit_generator.html#numpy.random.Generator.bit_generator" title="numpy.random.Generator.bit_generator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">bit_generator</span></code></a></dt><dd><p>The bit generator instance used by the generator.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="9adb6ad8-7662-482a-b6a5-5577fd9a300e">
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<p>Starting from a seeded default generator:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># High quality entropy created with: f"0x{secrets.randbits(128):x}"</span>
<span class="gp">>>> </span><span class="n">entropy</span> <span class="o">=</span> <span class="mh">0x3034c61a9ae04ff8cb62ab8ec2c4b501</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="n">entropy</span><span class="p">)</span>
</pre></div>
</div>
<p>Create two new generators for example for parallel execution:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">child_rng1</span><span class="p">,</span> <span class="n">child_rng2</span> <span class="o">=</span> <span class="n">rng</span><span class="o">.</span><span class="n">spawn</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
</div>
<p>Drawn numbers from each are independent but derived from the initial
seeding entropy:</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">uniform</span><span class="p">(),</span> <span class="n">child_rng1</span><span class="o">.</span><span class="n">uniform</span><span class="p">(),</span> <span class="n">child_rng2</span><span class="o">.</span><span class="n">uniform</span><span class="p">()</span>
<span class="go">(0.19029263503854454, 0.9475673279178444, 0.4702687338396767)</span>
</pre></div>
</div>
<p>It is safe to spawn additional children from the original <code class="docutils literal notranslate"><span class="pre">rng</span></code> or
the children:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">more_child_rngs</span> <span class="o">=</span> <span class="n">rng</span><span class="o">.</span><span class="n">spawn</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">nested_spawn</span> <span class="o">=</span> <span class="n">child_rng1</span><span class="o">.</span><span class="n">spawn</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>
</pre></div>
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