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fjosw 2022-03-04 17:16:50 +00:00
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commit da15864bc2
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@ -1667,7 +1667,7 @@
<span class="n">length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs</span><span class="p">)</span>
<span class="n">max_samples</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">N</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">obs</span><span class="p">])</span>
<span class="k">if</span> <span class="n">max_samples</span> <span class="o">&lt;=</span> <span class="n">length</span><span class="p">:</span>
<span class="k">if</span> <span class="n">max_samples</span> <span class="o">&lt;=</span> <span class="n">length</span> <span class="ow">and</span> <span class="ow">not</span> <span class="p">[</span><span class="n">item</span> <span class="k">for</span> <span class="n">sublist</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">cov_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">obs</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">sublist</span><span class="p">]:</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;The dimension of the covariance matrix (</span><span class="si">{</span><span class="n">length</span><span class="si">}</span><span class="s2">) is larger or equal to the number of samples (</span><span class="si">{</span><span class="n">max_samples</span><span class="si">}</span><span class="s2">). This will result in a rank deficient matrix.&quot;</span><span class="p">,</span> <span class="ne">RuntimeWarning</span><span class="p">)</span>
<span class="n">cov</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">length</span><span class="p">,</span> <span class="n">length</span><span class="p">))</span>
@ -4861,7 +4861,7 @@ Second observable</li>
<span class="n">length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs</span><span class="p">)</span>
<span class="n">max_samples</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">N</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">obs</span><span class="p">])</span>
<span class="k">if</span> <span class="n">max_samples</span> <span class="o">&lt;=</span> <span class="n">length</span><span class="p">:</span>
<span class="k">if</span> <span class="n">max_samples</span> <span class="o">&lt;=</span> <span class="n">length</span> <span class="ow">and</span> <span class="ow">not</span> <span class="p">[</span><span class="n">item</span> <span class="k">for</span> <span class="n">sublist</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">cov_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">obs</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">sublist</span><span class="p">]:</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;The dimension of the covariance matrix (</span><span class="si">{</span><span class="n">length</span><span class="si">}</span><span class="s2">) is larger or equal to the number of samples (</span><span class="si">{</span><span class="n">max_samples</span><span class="si">}</span><span class="s2">). This will result in a rank deficient matrix.&quot;</span><span class="p">,</span> <span class="ne">RuntimeWarning</span><span class="p">)</span>
<span class="n">cov</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">length</span><span class="p">,</span> <span class="n">length</span><span class="p">))</span>