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<section id="constants-of-the-numpy-ma-module">
<span id="numpy-ma-constants"></span><h1>Constants of the <a class="reference internal" href="maskedarray.generic.html#module-numpy.ma" title="numpy.ma"><code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.ma</span></code></a> module<a class="headerlink" href="#constants-of-the-numpy-ma-module" title="Link to this heading">#</a></h1>
<p>In addition to the <a class="reference internal" href="#numpy.ma.MaskedArray" title="numpy.ma.MaskedArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MaskedArray</span></code></a> class, the <a class="reference internal" href="maskedarray.generic.html#module-numpy.ma" title="numpy.ma"><code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.ma</span></code></a> module
defines several constants.</p>
<dl class="py data">
<dt class="sig sig-object py" id="numpy.ma.masked">
<span class="sig-prename descclassname"><span class="pre">numpy.ma.</span></span><span class="sig-name descname"><span class="pre">masked</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/ma/core.py"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.ma.masked" title="Link to this definition">#</a></dt>
<dd><p>The <a class="reference internal" href="#numpy.ma.masked" title="numpy.ma.masked"><code class="xref py py-attr docutils literal notranslate"><span class="pre">masked</span></code></a> constant is a special case of <a class="reference internal" href="#numpy.ma.MaskedArray" title="numpy.ma.MaskedArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MaskedArray</span></code></a>,
with a float datatype and a null shape. It is used to test whether a
specific entry of a masked array is masked, or to mask one or several
entries of a masked array:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">..</span> <span class="n">try_examples</span><span class="p">::</span>
</pre></div>
</div>
<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>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="n">mask</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="ow">is</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">masked</span>
<span class="go">True</span>
<span class="gp">>>> </span><span class="n">x</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">masked</span>
<span class="gp">>>> </span><span class="n">x</span>
<span class="go">masked_array(data=[1, --, --],</span>
<span class="go"> mask=[False, True, True],</span>
<span class="go"> fill_value=999999)</span>
</pre></div>
</div>
</dd></dl>
<dl class="py data">
<dt class="sig sig-object py" id="numpy.ma.nomask">
<span class="sig-prename descclassname"><span class="pre">numpy.ma.</span></span><span class="sig-name descname"><span class="pre">nomask</span></span><a class="headerlink" href="#numpy.ma.nomask" title="Link to this definition">#</a></dt>
<dd><p>Value indicating that a masked array has no invalid entry.
<a class="reference internal" href="#numpy.ma.nomask" title="numpy.ma.nomask"><code class="xref py py-attr docutils literal notranslate"><span class="pre">nomask</span></code></a> is used internally to speed up computations when the mask
is not needed. It is represented internally as <code class="docutils literal notranslate"><span class="pre">np.False_</span></code>.</p>
</dd></dl>
<dl class="py data">
<dt class="sig sig-object py" id="numpy.ma.masked_print_option">
<span class="sig-prename descclassname"><span class="pre">numpy.ma.</span></span><span class="sig-name descname"><span class="pre">masked_print_option</span></span><a class="headerlink" href="#numpy.ma.masked_print_option" title="Link to this definition">#</a></dt>
<dd><p>String used in lieu of missing data when a masked array is printed.
By default, this string is <code class="docutils literal notranslate"><span class="pre">'--'</span></code>.</p>
<p>Use <code class="docutils literal notranslate"><span class="pre">set_display()</span></code> to change the default string.
Example usage: <code class="docutils literal notranslate"><span class="pre">numpy.ma.masked_print_option.set_display('X')</span></code>
replaces missing data with <code class="docutils literal notranslate"><span class="pre">'X'</span></code>.</p>
</dd></dl>
</section>
<section id="the-maskedarray-class">
<span id="maskedarray-baseclass"></span><h1>The <a class="reference internal" href="#numpy.ma.MaskedArray" title="numpy.ma.MaskedArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MaskedArray</span></code></a> class<a class="headerlink" href="#the-maskedarray-class" title="Link to this heading">#</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.ma.</span></span><span class="sig-name descname"><span class="pre">MaskedArray</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/ma/core.py"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.ma.MaskedArray" title="Link to this definition">#</a></dt>
<dd></dd></dl>
<p>A subclass of <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code></a> designed to manipulate numerical arrays with missing data.</p>
<p>An instance of <a class="reference internal" href="#numpy.ma.MaskedArray" title="numpy.ma.MaskedArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MaskedArray</span></code></a> can be thought as the combination of several elements:</p>
<ul class="simple">
<li><p>The <a class="reference internal" href="#numpy.ma.MaskedArray.data" title="numpy.ma.MaskedArray.data"><code class="xref py py-attr docutils literal notranslate"><span class="pre">data</span></code></a>, as a regular <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">numpy.ndarray</span></code></a> of any shape or datatype (the data).</p></li>
<li><p>A boolean <a class="reference internal" href="#numpy.ma.MaskedArray.mask" title="numpy.ma.MaskedArray.mask"><code class="xref py py-attr docutils literal notranslate"><span class="pre">mask</span></code></a> with the same shape as the data, where a <code class="docutils literal notranslate"><span class="pre">True</span></code> value indicates that the corresponding element of the data is invalid.
The special value <a class="reference internal" href="#numpy.ma.nomask" title="numpy.ma.nomask"><code class="xref py py-const docutils literal notranslate"><span class="pre">nomask</span></code></a> is also acceptable for arrays without named fields, and indicates that no data is invalid.</p></li>
<li><p>A <a class="reference internal" href="#numpy.ma.MaskedArray.fill_value" title="numpy.ma.MaskedArray.fill_value"><code class="xref py py-attr docutils literal notranslate"><span class="pre">fill_value</span></code></a>, a value that may be used to replace the invalid entries in order to return a standard <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">numpy.ndarray</span></code></a>.</p></li>
</ul>
<section id="attributes-and-properties-of-masked-arrays">
<span id="ma-attributes"></span><h2>Attributes and properties of masked arrays<a class="headerlink" href="#attributes-and-properties-of-masked-arrays" title="Link to this heading">#</a></h2>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<p><a class="reference internal" href="arrays.ndarray.html#arrays-ndarray-attributes"><span class="std std-ref">Array Attributes</span></a></p>
</div>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.data">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">data</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.data" title="Link to this definition">#</a></dt>
<dd><p>Returns the underlying data, as a view of the masked array.</p>
<p>If the underlying data is a subclass of <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">numpy.ndarray</span></code></a>, it is
returned as such.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">matrix</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]]),</span> <span class="n">mask</span><span class="o">=</span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">data</span>
<span class="go">matrix([[1, 2],</span>
<span class="go"> [3, 4]])</span>
</pre></div>
</div>
<p>The type of the data can be accessed through the <a class="reference internal" href="#numpy.ma.MaskedArray.baseclass" title="numpy.ma.MaskedArray.baseclass"><code class="xref py py-attr docutils literal notranslate"><span class="pre">baseclass</span></code></a>
attribute.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.mask">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">mask</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.mask" title="Link to this definition">#</a></dt>
<dd><p>Current mask.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.recordmask">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">recordmask</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.recordmask" title="Link to this definition">#</a></dt>
<dd><p>Get or set the mask of the array if it has no named fields. For
structured arrays, returns a ndarray of booleans where entries are
<code class="docutils literal notranslate"><span class="pre">True</span></code> if <strong>all</strong> the fields are masked, <code class="docutils literal notranslate"><span class="pre">False</span></code> otherwise:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">array</span><span class="p">([(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">)],</span>
<span class="gp">... </span> <span class="n">mask</span><span class="o">=</span><span class="p">[(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">)],</span>
<span class="gp">... </span> <span class="n">dtype</span><span class="o">=</span><span class="p">[(</span><span class="s1">'a'</span><span class="p">,</span> <span class="nb">int</span><span class="p">),</span> <span class="p">(</span><span class="s1">'b'</span><span class="p">,</span> <span class="nb">int</span><span class="p">)])</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">recordmask</span>
<span class="go">array([False, False, True, False, False])</span>
</pre></div>
</div>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.fill_value">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">fill_value</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.fill_value" title="Link to this definition">#</a></dt>
<dd><p>The filling value of the masked array is a scalar. When setting, None
will set to a default based on the data type.</p>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="29a67514-4e35-45b8-8bf8-56e6996948ad">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('29a67514-4e35-45b8-8bf8-56e6996948ad','8bb078c5-0b56-4033-9ae5-0a31e15208a7','3fae2409-da7d-45f4-b229-682ff8739aba','../lite/tree/../notebooks/index.html?path=a7aa6c90_2a20_41cf_947e_65b71fbdfa83.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="k">for</span> <span class="n">dt</span> <span class="ow">in</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int64</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">complex128</span><span class="p">]:</span>
<span class="gp">... </span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dt</span><span class="p">)</span><span class="o">.</span><span class="n">get_fill_value</span><span class="p">()</span>
<span class="gp">...</span>
<span class="go">np.int64(999999)</span>
<span class="go">np.int64(999999)</span>
<span class="go">np.float64(1e+20)</span>
<span class="go">np.complex128(1e+20+0j)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mf">1.</span><span class="p">],</span> <span class="n">fill_value</span><span class="o">=-</span><span class="n">np</span><span class="o">.</span><span class="n">inf</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">fill_value</span>
<span class="go">np.float64(-inf)</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">fill_value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">fill_value</span>
<span class="go">np.float64(3.1415926535897931)</span>
</pre></div>
</div>
<p>Reset to default:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">fill_value</span> <span class="o">=</span> <span class="kc">None</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">fill_value</span>
<span class="go">np.float64(1e+20)</span>
</pre></div>
</div>
</div>
</div>
<div id="3fae2409-da7d-45f4-b229-682ff8739aba" class="try_examples_outer_iframe hidden"><div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesHideIframe('29a67514-4e35-45b8-8bf8-56e6996948ad','3fae2409-da7d-45f4-b229-682ff8739aba')">Go Back</button><button class="try_examples_button" onclick="window.openInNewTab('29a67514-4e35-45b8-8bf8-56e6996948ad','3fae2409-da7d-45f4-b229-682ff8739aba')">Open In Tab</button></div><div id="8bb078c5-0b56-4033-9ae5-0a31e15208a7" class="jupyterlite_sphinx_iframe_container"></div></div><script>document.addEventListener("DOMContentLoaded", function() {window.loadTryExamplesConfig("../try_examples.json");});</script></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.baseclass">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">baseclass</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.baseclass" title="Link to this definition">#</a></dt>
<dd><p>Class of the underlying data (read-only).</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.sharedmask">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">sharedmask</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.sharedmask" title="Link to this definition">#</a></dt>
<dd><p>Share status of the mask (read-only).</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ma.MaskedArray.hardmask">
<span class="sig-prename descclassname"><span class="pre">ma.MaskedArray.</span></span><span class="sig-name descname"><span class="pre">hardmask</span></span><a class="headerlink" href="#numpy.ma.MaskedArray.hardmask" title="Link to this definition">#</a></dt>
<dd><p>Specifies whether values can be unmasked through assignments.</p>
<p>By default, assigning definite values to masked array entries will
unmask them. When <a class="reference internal" href="#numpy.ma.MaskedArray.hardmask" title="numpy.ma.MaskedArray.hardmask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hardmask</span></code></a> is <code class="docutils literal notranslate"><span class="pre">True</span></code>, the mask will not change
through assignments.</p>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="generated/numpy.ma.MaskedArray.harden_mask.html#numpy.ma.MaskedArray.harden_mask" title="numpy.ma.MaskedArray.harden_mask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ma.MaskedArray.harden_mask</span></code></a></dt><dd></dd>
<dt><a class="reference internal" href="generated/numpy.ma.MaskedArray.soften_mask.html#numpy.ma.MaskedArray.soften_mask" title="numpy.ma.MaskedArray.soften_mask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ma.MaskedArray.soften_mask</span></code></a></dt><dd></dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="dfd92937-4711-4db9-9ea4-a179a8017f3d">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('dfd92937-4711-4db9-9ea4-a179a8017f3d','ad5722bb-a598-460b-8021-2ebb25498a2a','54c8f3fc-10ef-4c70-bde7-0c9fc8841bf7','../lite/tree/../notebooks/index.html?path=1b67078a_f43a_4ef3_8721_3e2d4b31838e.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">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">m</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">masked_array</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="o">></span><span class="mi">5</span><span class="p">)</span>
<span class="gp">>>> </span><span class="k">assert</span> <span class="ow">not</span> <span class="n">m</span><span class="o">.</span><span class="n">hardmask</span>
</pre></div>
</div>
<p>Since <em class="xref py py-obj">m</em> has a soft mask, assigning an element value unmasks that
element:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">m</span><span class="p">[</span><span class="mi">8</span><span class="p">]</span> <span class="o">=</span> <span class="mi">42</span>
<span class="gp">>>> </span><span class="n">m</span>
<span class="go">masked_array(data=[0, 1, 2, 3, 4, 5, --, --, 42, --],</span>
<span class="go"> mask=[False, False, False, False, False, False,</span>
<span class="go"> True, True, False, True],</span>
<span class="go"> fill_value=999999)</span>
</pre></div>
</div>
<p>After hardening, the mask is not affected by assignments:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">hardened</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">harden_mask</span><span class="p">(</span><span class="n">m</span><span class="p">)</span>
<span class="gp">>>> </span><span class="k">assert</span> <span class="n">m</span><span class="o">.</span><span class="n">hardmask</span> <span class="ow">and</span> <span class="n">hardened</span> <span class="ow">is</span> <span class="n">m</span>
<span class="gp">>>> </span><span class="n">m</span><span class="p">[:]</span> <span class="o">=</span> <span class="mi">23</span>
<span class="gp">>>> </span><span class="n">m</span>
<span class="go">masked_array(data=[23, 23, 23, 23, 23, 23, --, --, 23, --],</span>
<span class="go"> mask=[False, False, False, False, False, False,</span>
<span class="go"> True, True, False, True],</span>
<span class="go"> fill_value=999999)</span>
</pre></div>
</div>
</div>
</div>
<div id="54c8f3fc-10ef-4c70-bde7-0c9fc8841bf7" class="try_examples_outer_iframe hidden"><div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesHideIframe('dfd92937-4711-4db9-9ea4-a179a8017f3d','54c8f3fc-10ef-4c70-bde7-0c9fc8841bf7')">Go Back</button><button class="try_examples_button" onclick="window.openInNewTab('dfd92937-4711-4db9-9ea4-a179a8017f3d','54c8f3fc-10ef-4c70-bde7-0c9fc8841bf7')">Open In Tab</button></div><div id="ad5722bb-a598-460b-8021-2ebb25498a2a" class="jupyterlite_sphinx_iframe_container"></div></div><script>document.addEventListener("DOMContentLoaded", function() {window.loadTryExamplesConfig("../try_examples.json");});</script></dd></dl>
<p>As <a class="reference internal" href="#numpy.ma.MaskedArray" title="numpy.ma.MaskedArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MaskedArray</span></code></a> is a subclass of <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code></a>, a masked array also inherits all the attributes and properties of a <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code></a> instance.</p>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.base.html#numpy.ma.MaskedArray.base" title="numpy.ma.MaskedArray.base"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.base</span></code></a></p></td>
<td><p>Base object if memory is from some other object.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.ctypes.html#numpy.ma.MaskedArray.ctypes" title="numpy.ma.MaskedArray.ctypes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.ctypes</span></code></a></p></td>
<td><p>An object to simplify the interaction of the array with the ctypes module.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.dtype.html#numpy.ma.MaskedArray.dtype" title="numpy.ma.MaskedArray.dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.dtype</span></code></a></p></td>
<td><p>Data-type of the array's elements.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.flags.html#numpy.ma.MaskedArray.flags" title="numpy.ma.MaskedArray.flags"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.flags</span></code></a></p></td>
<td><p>Information about the memory layout of the array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.itemsize.html#numpy.ma.MaskedArray.itemsize" title="numpy.ma.MaskedArray.itemsize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.itemsize</span></code></a></p></td>
<td><p>Length of one array element in bytes.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.nbytes.html#numpy.ma.MaskedArray.nbytes" title="numpy.ma.MaskedArray.nbytes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.nbytes</span></code></a></p></td>
<td><p>Total bytes consumed by the elements of the array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.ndim.html#numpy.ma.MaskedArray.ndim" title="numpy.ma.MaskedArray.ndim"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.ndim</span></code></a></p></td>
<td><p>Number of array dimensions.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.shape.html#numpy.ma.MaskedArray.shape" title="numpy.ma.MaskedArray.shape"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.shape</span></code></a></p></td>
<td><p>Tuple of array dimensions.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.size.html#numpy.ma.MaskedArray.size" title="numpy.ma.MaskedArray.size"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.size</span></code></a></p></td>
<td><p>Number of elements in the array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.strides.html#numpy.ma.MaskedArray.strides" title="numpy.ma.MaskedArray.strides"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.strides</span></code></a></p></td>
<td><p>Tuple of bytes to step in each dimension when traversing an array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.imag.html#numpy.ma.MaskedArray.imag" title="numpy.ma.MaskedArray.imag"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.imag</span></code></a></p></td>
<td><p>The imaginary part of the masked array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.real.html#numpy.ma.MaskedArray.real" title="numpy.ma.MaskedArray.real"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.real</span></code></a></p></td>
<td><p>The real part of the masked array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.flat.html#numpy.ma.MaskedArray.flat" title="numpy.ma.MaskedArray.flat"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.flat</span></code></a></p></td>
<td><p>Return a flat iterator, or set a flattened version of self to value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.__array_priority__.html#numpy.ma.MaskedArray.__array_priority__" title="numpy.ma.MaskedArray.__array_priority__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.__array_priority__</span></code></a></p></td>
<td><p></p></td>
</tr>
</tbody>
</table>
</div>
</section>
</section>
<section id="maskedarray-methods">
<h1><a class="reference internal" href="#numpy.ma.MaskedArray" title="numpy.ma.MaskedArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MaskedArray</span></code></a> methods<a class="headerlink" href="#maskedarray-methods" title="Link to this heading">#</a></h1>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<p><a class="reference internal" href="arrays.ndarray.html#array-ndarray-methods"><span class="std std-ref">Array methods</span></a></p>
</div>
<section id="conversion">
<h2>Conversion<a class="headerlink" href="#conversion" title="Link to this heading">#</a></h2>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.__float__.html#numpy.ma.MaskedArray.__float__" title="numpy.ma.MaskedArray.__float__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.__float__</span></code></a>()</p></td>
<td><p>Convert to float.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.__int__.html#numpy.ma.MaskedArray.__int__" title="numpy.ma.MaskedArray.__int__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.__int__</span></code></a>()</p></td>
<td><p>Convert to int.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.view.html#numpy.ma.MaskedArray.view" title="numpy.ma.MaskedArray.view"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.view</span></code></a>([dtype, type, fill_value])</p></td>
<td><p>Return a view of the MaskedArray data.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.astype.html#numpy.ma.MaskedArray.astype" title="numpy.ma.MaskedArray.astype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.astype</span></code></a>(dtype[, order, casting, ...])</p></td>
<td><p>Copy of the array, cast to a specified type.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.byteswap.html#numpy.ma.MaskedArray.byteswap" title="numpy.ma.MaskedArray.byteswap"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.byteswap</span></code></a>([inplace])</p></td>
<td><p>Swap the bytes of the array elements</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.compressed.html#numpy.ma.MaskedArray.compressed" title="numpy.ma.MaskedArray.compressed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.compressed</span></code></a>()</p></td>
<td><p>Return all the non-masked data as a 1-D array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.filled.html#numpy.ma.MaskedArray.filled" title="numpy.ma.MaskedArray.filled"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.filled</span></code></a>([fill_value])</p></td>
<td><p>Return a copy of self, with masked values filled with a given value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.tofile.html#numpy.ma.MaskedArray.tofile" title="numpy.ma.MaskedArray.tofile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.tofile</span></code></a>(fid[, sep, format])</p></td>
<td><p>Save a masked array to a file in binary format.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.toflex.html#numpy.ma.MaskedArray.toflex" title="numpy.ma.MaskedArray.toflex"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.toflex</span></code></a>()</p></td>
<td><p>Transforms a masked array into a flexible-type array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.tolist.html#numpy.ma.MaskedArray.tolist" title="numpy.ma.MaskedArray.tolist"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.tolist</span></code></a>([fill_value])</p></td>
<td><p>Return the data portion of the masked array as a hierarchical Python list.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.torecords.html#numpy.ma.MaskedArray.torecords" title="numpy.ma.MaskedArray.torecords"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.torecords</span></code></a>()</p></td>
<td><p>Transforms a masked array into a flexible-type array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.tobytes.html#numpy.ma.MaskedArray.tobytes" title="numpy.ma.MaskedArray.tobytes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.tobytes</span></code></a>([fill_value, order])</p></td>
<td><p>Return the array data as a string containing the raw bytes in the array.</p></td>
</tr>
</tbody>
</table>
</div>
</section>
<section id="shape-manipulation">
<h2>Shape manipulation<a class="headerlink" href="#shape-manipulation" title="Link to this heading">#</a></h2>
<p>For reshape, resize, and transpose, the single tuple argument may be
replaced with <code class="docutils literal notranslate"><span class="pre">n</span></code> integers which will be interpreted as an n-tuple.</p>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.flatten.html#numpy.ma.MaskedArray.flatten" title="numpy.ma.MaskedArray.flatten"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.flatten</span></code></a>([order])</p></td>
<td><p>Return a copy of the array collapsed into one dimension.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.ravel.html#numpy.ma.MaskedArray.ravel" title="numpy.ma.MaskedArray.ravel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.ravel</span></code></a>([order])</p></td>
<td><p>Returns a 1D version of self, as a view.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.reshape.html#numpy.ma.MaskedArray.reshape" title="numpy.ma.MaskedArray.reshape"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.reshape</span></code></a>(*s, **kwargs)</p></td>
<td><p>Give a new shape to the array without changing its data.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.resize.html#numpy.ma.MaskedArray.resize" title="numpy.ma.MaskedArray.resize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.resize</span></code></a>(newshape[, refcheck, order])</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.squeeze.html#numpy.ma.MaskedArray.squeeze" title="numpy.ma.MaskedArray.squeeze"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.squeeze</span></code></a>([axis])</p></td>
<td><p>Remove axes of length one from <em class="xref py py-obj">a</em>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.swapaxes.html#numpy.ma.MaskedArray.swapaxes" title="numpy.ma.MaskedArray.swapaxes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.swapaxes</span></code></a>(axis1, axis2)</p></td>
<td><p>Return a view of the array with <em class="xref py py-obj">axis1</em> and <em class="xref py py-obj">axis2</em> interchanged.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.transpose.html#numpy.ma.MaskedArray.transpose" title="numpy.ma.MaskedArray.transpose"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.transpose</span></code></a>(*axes)</p></td>
<td><p>Returns a view of the array with axes transposed.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.T.html#numpy.ma.MaskedArray.T" title="numpy.ma.MaskedArray.T"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.T</span></code></a></p></td>
<td><p>View of the transposed array.</p></td>
</tr>
</tbody>
</table>
</div>
</section>
<section id="item-selection-and-manipulation">
<h2>Item selection and manipulation<a class="headerlink" href="#item-selection-and-manipulation" title="Link to this heading">#</a></h2>
<p>For array methods that take an <code class="docutils literal notranslate"><span class="pre">axis</span></code> keyword, it defaults to None.
If axis is None, then the array is treated as a 1-D array.
Any other value for <code class="docutils literal notranslate"><span class="pre">axis</span></code> represents the dimension along which
the operation should proceed.</p>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.argmax.html#numpy.ma.MaskedArray.argmax" title="numpy.ma.MaskedArray.argmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.argmax</span></code></a>([axis, fill_value, out, ...])</p></td>
<td><p>Returns array of indices of the maximum values along the given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.argmin.html#numpy.ma.MaskedArray.argmin" title="numpy.ma.MaskedArray.argmin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.argmin</span></code></a>([axis, fill_value, out, ...])</p></td>
<td><p>Return array of indices to the minimum values along the given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.argsort.html#numpy.ma.MaskedArray.argsort" title="numpy.ma.MaskedArray.argsort"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.argsort</span></code></a>([axis, kind, order, ...])</p></td>
<td><p>Return an ndarray of indices that sort the array along the specified axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.choose.html#numpy.ma.MaskedArray.choose" title="numpy.ma.MaskedArray.choose"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.choose</span></code></a>(choices[, out, mode])</p></td>
<td><p>Use an index array to construct a new array from a set of choices.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.compress.html#numpy.ma.MaskedArray.compress" title="numpy.ma.MaskedArray.compress"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.compress</span></code></a>(condition[, axis, out])</p></td>
<td><p>Return <em class="xref py py-obj">a</em> where condition is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.diagonal.html#numpy.ma.MaskedArray.diagonal" title="numpy.ma.MaskedArray.diagonal"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.diagonal</span></code></a>([offset, axis1, axis2])</p></td>
<td><p>Return specified diagonals.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.fill.html#numpy.ma.MaskedArray.fill" title="numpy.ma.MaskedArray.fill"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.fill</span></code></a>(value)</p></td>
<td><p>Fill the array with a scalar value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.item.html#numpy.ma.MaskedArray.item" title="numpy.ma.MaskedArray.item"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.item</span></code></a>(*args)</p></td>
<td><p>Copy an element of an array to a standard Python scalar and return it.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.nonzero.html#numpy.ma.MaskedArray.nonzero" title="numpy.ma.MaskedArray.nonzero"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.nonzero</span></code></a>()</p></td>
<td><p>Return the indices of unmasked elements that are not zero.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.put.html#numpy.ma.MaskedArray.put" title="numpy.ma.MaskedArray.put"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.put</span></code></a>(indices, values[, mode])</p></td>
<td><p>Set storage-indexed locations to corresponding values.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.repeat.html#numpy.ma.MaskedArray.repeat" title="numpy.ma.MaskedArray.repeat"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.repeat</span></code></a>(repeats[, axis])</p></td>
<td><p>Repeat elements of an array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.searchsorted.html#numpy.ma.MaskedArray.searchsorted" title="numpy.ma.MaskedArray.searchsorted"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.searchsorted</span></code></a>(v[, side, sorter])</p></td>
<td><p>Find indices where elements of v should be inserted in a to maintain order.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.sort.html#numpy.ma.MaskedArray.sort" title="numpy.ma.MaskedArray.sort"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.sort</span></code></a>([axis, kind, order, ...])</p></td>
<td><p>Sort the array, in-place</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.take.html#numpy.ma.MaskedArray.take" title="numpy.ma.MaskedArray.take"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.take</span></code></a>(indices[, axis, out, mode])</p></td>
<td><p>Take elements from a masked array along an axis.</p></td>
</tr>
</tbody>
</table>
</div>
</section>
<section id="pickling-and-copy">
<h2>Pickling and copy<a class="headerlink" href="#pickling-and-copy" title="Link to this heading">#</a></h2>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.copy.html#numpy.ma.MaskedArray.copy" title="numpy.ma.MaskedArray.copy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.copy</span></code></a>([order])</p></td>
<td><p>Return a copy of the array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.dump.html#numpy.ma.MaskedArray.dump" title="numpy.ma.MaskedArray.dump"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.dump</span></code></a>(file)</p></td>
<td><p>Dump a pickle of the array to the specified file.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.dumps.html#numpy.ma.MaskedArray.dumps" title="numpy.ma.MaskedArray.dumps"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.dumps</span></code></a>()</p></td>
<td><p>Returns the pickle of the array as a string.</p></td>
</tr>
</tbody>
</table>
</div>
</section>
<section id="calculations">
<h2>Calculations<a class="headerlink" href="#calculations" title="Link to this heading">#</a></h2>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.all.html#numpy.ma.MaskedArray.all" title="numpy.ma.MaskedArray.all"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.all</span></code></a>([axis, out, keepdims])</p></td>
<td><p>Returns True if all elements evaluate to True.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.anom.html#numpy.ma.MaskedArray.anom" title="numpy.ma.MaskedArray.anom"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.anom</span></code></a>([axis, dtype])</p></td>
<td><p>Compute the anomalies (deviations from the arithmetic mean) along the given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.any.html#numpy.ma.MaskedArray.any" title="numpy.ma.MaskedArray.any"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.any</span></code></a>([axis, out, keepdims])</p></td>
<td><p>Returns True if any of the elements of <em class="xref py py-obj">a</em> evaluate to True.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.clip.html#numpy.ma.MaskedArray.clip" title="numpy.ma.MaskedArray.clip"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.clip</span></code></a>([min, max, out])</p></td>
<td><p>Return an array whose values are limited to <code class="docutils literal notranslate"><span class="pre">[min,</span> <span class="pre">max]</span></code>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.conj.html#numpy.ma.MaskedArray.conj" title="numpy.ma.MaskedArray.conj"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.conj</span></code></a>()</p></td>
<td><p>Complex-conjugate all elements.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.conjugate.html#numpy.ma.MaskedArray.conjugate" title="numpy.ma.MaskedArray.conjugate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.conjugate</span></code></a>()</p></td>
<td><p>Return the complex conjugate, element-wise.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.cumprod.html#numpy.ma.MaskedArray.cumprod" title="numpy.ma.MaskedArray.cumprod"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.cumprod</span></code></a>([axis, dtype, out])</p></td>
<td><p>Return the cumulative product of the array elements over the given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.cumsum.html#numpy.ma.MaskedArray.cumsum" title="numpy.ma.MaskedArray.cumsum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.cumsum</span></code></a>([axis, dtype, out])</p></td>
<td><p>Return the cumulative sum of the array elements over the given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.max.html#numpy.ma.MaskedArray.max" title="numpy.ma.MaskedArray.max"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.max</span></code></a>([axis, out, fill_value, ...])</p></td>
<td><p>Return the maximum along a given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.mean.html#numpy.ma.MaskedArray.mean" title="numpy.ma.MaskedArray.mean"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.mean</span></code></a>([axis, dtype, out, keepdims])</p></td>
<td><p>Returns the average of the array elements along given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.min.html#numpy.ma.MaskedArray.min" title="numpy.ma.MaskedArray.min"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.min</span></code></a>([axis, out, fill_value, ...])</p></td>
<td><p>Return the minimum along a given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.prod.html#numpy.ma.MaskedArray.prod" title="numpy.ma.MaskedArray.prod"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.prod</span></code></a>([axis, dtype, out, keepdims])</p></td>
<td><p>Return the product of the array elements over the given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.product.html#numpy.ma.MaskedArray.product" title="numpy.ma.MaskedArray.product"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.product</span></code></a>([axis, dtype, out, keepdims])</p></td>
<td><p>Return the product of the array elements over the given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.ptp.html#numpy.ma.MaskedArray.ptp" title="numpy.ma.MaskedArray.ptp"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.ptp</span></code></a>([axis, out, fill_value, ...])</p></td>
<td><p>Return (maximum - minimum) along the given dimension (i.e. peak-to-peak value).</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.round.html#numpy.ma.MaskedArray.round" title="numpy.ma.MaskedArray.round"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.round</span></code></a>([decimals, out])</p></td>
<td><p>Return each element rounded to the given number of decimals.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.std.html#numpy.ma.MaskedArray.std" title="numpy.ma.MaskedArray.std"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.std</span></code></a>([axis, dtype, out, ddof, ...])</p></td>
<td><p>Returns the standard deviation of the array elements along given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.sum.html#numpy.ma.MaskedArray.sum" title="numpy.ma.MaskedArray.sum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.sum</span></code></a>([axis, dtype, out, keepdims])</p></td>
<td><p>Return the sum of the array elements over the given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.ma.MaskedArray.trace.html#numpy.ma.MaskedArray.trace" title="numpy.ma.MaskedArray.trace"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaskedArray.trace</span></code></a>([offset, axis1, axis2, ...])</p></td>
<td><p>Return the sum along diagonals of the array.</p></td>
</tr>