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pygsti.create_count_vec_dict.html
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pygsti.create_count_vec_dict.html
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<h1>pygsti.create_count_vec_dict<a class="headerlink" href="#pygsti-create-count-vec-dict" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="pygsti.create_count_vec_dict">
<code class="descclassname">pygsti.</code><code class="descname">create_count_vec_dict</code><span class="sig-paren">(</span><em>spamLabels</em>, <em>dataset</em>, <em>gatestring_list</em><span class="sig-paren">)</span><a class="headerlink" href="#pygsti.create_count_vec_dict" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a count-vector dictionary that is useful for speeding up multiple
evaluations of logl(...). The returned dictionary has keys that are
spam labels and values that are numpy vectors containing the dataset counts
for that spam label for each gate string in gatestring_list.</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"><ul class="first simple">
<li><strong>spamLabels</strong> (<em>list of strings</em>) – List of the spam labels to include as keys in returned dict.</li>
<li><strong>dataset</strong> (<a class="reference internal" href="pygsti.objects.DataSet.html#pygsti.objects.DataSet" title="pygsti.objects.DataSet"><em>DataSet</em></a>) – The dataset to extract counts from.</li>
<li><strong>gatestring_list</strong> (<em>list of (tuples or GateStrings)</em>) – List of the gate strings to extract counts for, which
determines the ordering of the counts within each dictionary
value.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">as described above.</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">dict</p>
</td>
</tr>
</tbody>
</table>
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