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<h1>scipy.optimize.LbfgsInvHessProduct.matmat<a class="headerlink" href="#scipy-optimize-lbfgsinvhessproduct-matmat" title="Permalink to this headline">¶</a></h1>
<dl class="method">
<dt id="scipy.optimize.LbfgsInvHessProduct.matmat">
<code class="descclassname">LbfgsInvHessProduct.</code><code class="descname">matmat</code><span class="sig-paren">(</span><em>X</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scipy/scipy/blob/4e64658/scipy/sparse/linalg/interface.py#L290-L331"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#scipy.optimize.LbfgsInvHessProduct.matmat" title="Permalink to this definition">¶</a></dt>
<dd><p>Matrix-matrix multiplication.</p>
<p>Performs the operation y=A*X where A is an MxN linear
operator and X dense N*K matrix or ndarray.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><p class="first"><strong>X</strong> : {matrix, ndarray}</p>
<blockquote>
<div><p>An array with shape (N,K).</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>Y</strong> : {matrix, ndarray}</p>
<blockquote class="last">
<div><p>A matrix or ndarray with shape (M,K) depending on
the type of the X argument.</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric">Notes</p>
<p>This matmat wraps any user-specified matmat routine or overridden
_matmat method to ensure that y has the correct type.</p>
</dd></dl>

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