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<section id="numpy-random-generator-integers">
<h1>numpy.random.Generator.integers<a class="headerlink" href="#numpy-random-generator-integers" title="Link to this heading">#</a></h1>
<p>method</p>
<dl class="py method">
<dt class="sig sig-object py" id="numpy.random.Generator.integers">
<span class="sig-prename descclassname"><span class="pre">random.Generator.</span></span><span class="sig-name descname"><span class="pre">integers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high</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">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.int64</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">endpoint</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.random.Generator.integers" title="Link to this definition">#</a></dt>
<dd><p>Return random integers from <em class="xref py py-obj">low</em> (inclusive) to <em class="xref py py-obj">high</em> (exclusive), or
if endpoint=True, <em class="xref py py-obj">low</em> (inclusive) to <em class="xref py py-obj">high</em> (inclusive). Replaces
<em class="xref py py-obj">RandomState.randint</em> (with endpoint=False) and
<em class="xref py py-obj">RandomState.random_integers</em> (with endpoint=True)</p>
<p>Return random integers from the “discrete uniform” distribution of
the specified dtype. If <em class="xref py py-obj">high</em> is None (the default), then results are
from 0 to <em class="xref py py-obj">low</em>.</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>low</strong><span class="classifier">int or array-like of ints</span></dt><dd><p>Lowest (signed) integers to be drawn from the distribution (unless
<code class="docutils literal notranslate"><span class="pre">high=None</span></code>, in which case this parameter is 0 and this value is
used for <em class="xref py py-obj">high</em>).</p>
</dd>
<dt><strong>high</strong><span class="classifier">int or array-like of ints, optional</span></dt><dd><p>If provided, one above the largest (signed) integer to be drawn
from the distribution (see above for behavior if <code class="docutils literal notranslate"><span class="pre">high=None</span></code>).
If array-like, must contain integer values</p>
</dd>
<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. Byteorder must be native.
The default value is np.int64.</p>
</dd>
<dt><strong>endpoint</strong><span class="classifier">bool, optional</span></dt><dd><p>If true, sample from the interval [low, high] instead of the
default [low, high)
Defaults to False</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">int or ndarray of ints</span></dt><dd><p><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>-shaped array of random integers from the appropriate
distribution, or a single such random int if <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> not provided.</p>
</dd>
</dl>
</dd>
</dl>
<p class="rubric">Notes</p>
<p>When using broadcasting with uint64 dtypes, the maximum value (2**64)
cannot be represented as a standard integer type. The high array (or
low if high is None) must have object dtype, e.g., array([2**64]).</p>
<p class="rubric">References</p>
<div role="list" class="citation-list">
<div class="citation" id="r4fdcbec07432-1" role="doc-biblioentry">
<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
<p>Daniel Lemire., “Fast Random Integer Generation in an Interval”,
ACM Transactions on Modeling and Computer Simulation 29 (1), 2019,
<a class="reference external" href="https://arxiv.org/abs/1805.10941">https://arxiv.org/abs/1805.10941</a>.</p>
</div>
</div>
<p class="rubric">Examples</p>
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<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">integers</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="go">array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) # random</span>
<span class="gp">>>> </span><span class="n">rng</span><span class="o">.</span><span class="n">integers</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="go">array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])</span>
</pre></div>
</div>
<p>Generate a 2 x 4 array of ints between 0 and 4, inclusive:</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">integers</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="go">array([[4, 0, 2, 1],</span>
<span class="go"> [3, 2, 2, 0]]) # random</span>
</pre></div>
</div>
<p>Generate a 1 x 3 array with 3 different upper bounds</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">integers</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">])</span>
<span class="go">array([2, 2, 9]) # random</span>
</pre></div>
</div>
<p>Generate a 1 by 3 array with 3 different lower bounds</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">integers</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">],</span> <span class="mi">10</span><span class="p">)</span>
<span class="go">array([9, 8, 7]) # random</span>
</pre></div>
</div>
<p>Generate a 2 by 4 array using broadcasting with dtype of uint8</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">integers</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">],</span> <span class="p">[[</span><span class="mi">10</span><span class="p">],</span> <span class="p">[</span><span class="mi">20</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
<span class="go">array([[ 8, 6, 9, 7],</span>
<span class="go"> [ 1, 16, 9, 12]], dtype=uint8) # random</span>
</pre></div>
</div>
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