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<section id="numpy-all">
<h1>numpy.all<a class="headerlink" href="#numpy-all" title="Link to this heading">#</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="numpy.all">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">all</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims=<no</span> <span class="pre">value></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">where=<no</span> <span class="pre">value></span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/fromnumeric.py#L2588-L2675"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.all" title="Link to this definition">#</a></dt>
<dd><p>Test whether all array elements along a given axis evaluate to True.</p>
<dl class="field-list">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl>
<dt><strong>a</strong><span class="classifier">array_like</span></dt><dd><p>Input array or object that can be converted to an array.</p>
</dd>
<dt><strong>axis</strong><span class="classifier">None or int or tuple of ints, optional</span></dt><dd><p>Axis or axes along which a logical AND reduction is performed.
The default (<code class="docutils literal notranslate"><span class="pre">axis=None</span></code>) is to perform a logical AND over all
the dimensions of the input array. <em class="xref py py-obj">axis</em> may be negative, in
which case it counts from the last to the first axis. If this
is a tuple of ints, a reduction is performed on multiple
axes, instead of a single axis or all the axes as before.</p>
</dd>
<dt><strong>out</strong><span class="classifier">ndarray, optional</span></dt><dd><p>Alternate output array in which to place the result.
It must have the same shape as the expected output and its
type is preserved (e.g., if <code class="docutils literal notranslate"><span class="pre">dtype(out)</span></code> is float, the result
will consist of 0.0’s and 1.0’s). See <a class="reference internal" href="../../user/basics.ufuncs.html#ufuncs-output-type"><span class="std std-ref">Output type determination</span></a>
for more details.</p>
</dd>
<dt><strong>keepdims</strong><span class="classifier">bool, optional</span></dt><dd><p>If this is set to True, the axes which are reduced are left
in the result as dimensions with size one. With this option,
the result will broadcast correctly against the input array.</p>
<p>If the default value is passed, then <em class="xref py py-obj">keepdims</em> will not be
passed through to the <a class="reference internal" href="#numpy.all" title="numpy.all"><code class="xref py py-obj docutils literal notranslate"><span class="pre">all</span></code></a> method of sub-classes of
<a class="reference internal" href="numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray</span></code></a>, however any non-default value will be. If the
sub-class’ method does not implement <em class="xref py py-obj">keepdims</em> any
exceptions will be raised.</p>
</dd>
<dt><strong>where</strong><span class="classifier">array_like of bool, optional</span></dt><dd><p>Elements to include in checking for all <em class="xref py py-obj">True</em> values.
See <a class="reference internal" href="numpy.ufunc.reduce.html#numpy.ufunc.reduce" title="numpy.ufunc.reduce"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reduce</span></code></a> for details.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.20.0.</span></p>
</div>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>all</strong><span class="classifier">ndarray, bool</span></dt><dd><p>A new boolean or array is returned unless <em class="xref py py-obj">out</em> is specified,
in which case a reference to <em class="xref py py-obj">out</em> 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.ndarray.all.html#numpy.ndarray.all" title="numpy.ndarray.all"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray.all</span></code></a></dt><dd><p>equivalent method</p>
</dd>
<dt><a class="reference internal" href="numpy.any.html#numpy.any" title="numpy.any"><code class="xref py py-obj docutils literal notranslate"><span class="pre">any</span></code></a></dt><dd><p>Test whether any element along a given axis evaluates to True.</p>
</dd>
</dl>
</div>
<p class="rubric">Notes</p>
<p>Not a Number (NaN), positive infinity and negative infinity
evaluate to <em class="xref py py-obj">True</em> because these are not equal to zero.</p>
<div class="versionchanged">
<p><span class="versionmodified changed">Changed in version 2.0: </span>Before NumPy 2.0, <code class="docutils literal notranslate"><span class="pre">all</span></code> did not return booleans for object dtype
input arrays.
This behavior is still available via <code class="docutils literal notranslate"><span class="pre">np.logical_and.reduce</span></code>.</p>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="05f53ffc-ebda-4ddd-8639-f06f03119e99">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('05f53ffc-ebda-4ddd-8639-f06f03119e99','ae7831f1-2d25-462a-8749-e95fc9d3c457','af6dcab4-6513-4d06-a852-46c5bcc3e091','../../lite/tree/../notebooks/index.html?path=92b422ae_bd8c_4870_b2c9_7de53830a0f9.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="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">([[</span><span class="kc">True</span><span class="p">,</span><span class="kc">False</span><span class="p">],[</span><span class="kc">True</span><span class="p">,</span><span class="kc">True</span><span class="p">]])</span>
<span class="go">False</span>
</pre></div>
</div>
<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">all</span><span class="p">([[</span><span class="kc">True</span><span class="p">,</span><span class="kc">False</span><span class="p">],[</span><span class="kc">True</span><span class="p">,</span><span class="kc">True</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="go">array([ True, False])</span>
</pre></div>
</div>
<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">all</span><span class="p">([</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">])</span>
<span class="go">True</span>
</pre></div>
</div>
<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">all</span><span class="p">([</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">])</span>
<span class="go">True</span>
</pre></div>
</div>
<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">all</span><span class="p">([[</span><span class="kc">True</span><span class="p">,</span> <span class="kc">True</span><span class="p">],</span> <span class="p">[</span><span class="kc">False</span><span class="p">,</span> <span class="kc">True</span><span class="p">]],</span> <span class="n">where</span><span class="o">=</span><span class="p">[[</span><span class="kc">True</span><span class="p">],</span> <span class="p">[</span><span class="kc">False</span><span class="p">]])</span>
<span class="go">True</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">o</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">z</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">([</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">out</span><span class="o">=</span><span class="n">o</span><span class="p">)</span>
<span class="gp">>>> </span><span class="nb">id</span><span class="p">(</span><span class="n">z</span><span class="p">),</span> <span class="nb">id</span><span class="p">(</span><span class="n">o</span><span class="p">),</span> <span class="n">z</span>
<span class="go">(28293632, 28293632, array(True)) # may vary</span>
</pre></div>
</div>
</div>
</div>
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