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Documentation updated
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fjosw
parent
95fa13aaac
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bcd9571a41
3 changed files with 75 additions and 45 deletions
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@ -278,20 +278,19 @@
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<span class="k">return</span> <span class="n">derived_array</span><span class="p">(</span><span class="n">multi_dot</span><span class="p">,</span> <span class="n">operands</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">jack_matmul</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">):</span>
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<span class="k">def</span> <span class="nf">jack_matmul</span><span class="p">(</span><span class="o">*</span><span class="n">operands</span><span class="p">):</span>
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<span class="sd">"""Matrix multiply both operands making use of the jackknife approximation.</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> a : numpy.ndarray</span>
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<span class="sd"> First matrix, can be real or complex Obs valued</span>
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<span class="sd"> b : numpy.ndarray</span>
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<span class="sd"> Second matrix, can be real or complex Obs valued</span>
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<span class="sd"> operands : numpy.ndarray</span>
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<span class="sd"> Arbitrary number of 2d-numpy arrays which can be real or complex</span>
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<span class="sd"> Obs valued.</span>
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<span class="sd"> For large matrices this is considerably faster compared to matmul.</span>
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<span class="sd"> """</span>
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<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">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="n">CObs</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="p">[</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">]):</span>
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<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">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="n">CObs</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">operands</span><span class="p">):</span>
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<span class="k">def</span> <span class="nf">_exp_to_jack</span><span class="p">(</span><span class="n">matrix</span><span class="p">):</span>
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<span class="n">base_matrix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">matrix</span><span class="p">)</span>
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<span class="k">for</span> <span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">),</span> <span class="n">entry</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">ndenumerate</span><span class="p">(</span><span class="n">matrix</span><span class="p">):</span>
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@ -305,10 +304,10 @@
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<span class="n">import_jackknife</span><span class="p">(</span><span class="n">entry</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">name</span><span class="p">))</span>
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<span class="k">return</span> <span class="n">base_matrix</span>
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<span class="n">j_a</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
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<span class="n">j_b</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">j_a</span> <span class="o">@</span> <span class="n">j_b</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">a</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">operands</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">for</span> <span class="n">op</span> <span class="ow">in</span> <span class="n">operands</span><span class="p">[</span><span class="mi">1</span><span class="p">:]:</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">r</span> <span class="o">@</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">op</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">op</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">else</span><span class="p">:</span>
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<span class="k">def</span> <span class="nf">_exp_to_jack</span><span class="p">(</span><span class="n">matrix</span><span class="p">):</span>
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<span class="n">base_matrix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">matrix</span><span class="p">)</span>
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@ -322,10 +321,10 @@
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<span class="n">base_matrix</span><span class="p">[</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">]</span> <span class="o">=</span> <span class="n">import_jackknife</span><span class="p">(</span><span class="n">entry</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">base_matrix</span>
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<span class="n">j_a</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
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<span class="n">j_b</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">j_a</span> <span class="o">@</span> <span class="n">j_b</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">a</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">operands</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">for</span> <span class="n">op</span> <span class="ow">in</span> <span class="n">operands</span><span class="p">[</span><span class="mi">1</span><span class="p">:]:</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">r</span> <span class="o">@</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">op</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">op</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">def</span> <span class="nf">inv</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
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@ -942,25 +941,24 @@ Obs valued.</li>
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<span class="def">def</span>
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<span class="name">jack_matmul</span><span class="signature">(a, b)</span>:
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<span class="name">jack_matmul</span><span class="signature">(*operands)</span>:
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</div>
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<details>
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<summary>View Source</summary>
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<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">jack_matmul</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">):</span>
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<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">jack_matmul</span><span class="p">(</span><span class="o">*</span><span class="n">operands</span><span class="p">):</span>
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<span class="sd">"""Matrix multiply both operands making use of the jackknife approximation.</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> a : numpy.ndarray</span>
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<span class="sd"> First matrix, can be real or complex Obs valued</span>
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<span class="sd"> b : numpy.ndarray</span>
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<span class="sd"> Second matrix, can be real or complex Obs valued</span>
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<span class="sd"> operands : numpy.ndarray</span>
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<span class="sd"> Arbitrary number of 2d-numpy arrays which can be real or complex</span>
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<span class="sd"> Obs valued.</span>
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<span class="sd"> For large matrices this is considerably faster compared to matmul.</span>
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<span class="sd"> """</span>
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<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">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="n">CObs</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="p">[</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">]):</span>
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<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">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="n">CObs</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">operands</span><span class="p">):</span>
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<span class="k">def</span> <span class="nf">_exp_to_jack</span><span class="p">(</span><span class="n">matrix</span><span class="p">):</span>
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<span class="n">base_matrix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">matrix</span><span class="p">)</span>
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<span class="k">for</span> <span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">),</span> <span class="n">entry</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">ndenumerate</span><span class="p">(</span><span class="n">matrix</span><span class="p">):</span>
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@ -974,10 +972,10 @@ Obs valued.</li>
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<span class="n">import_jackknife</span><span class="p">(</span><span class="n">entry</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">name</span><span class="p">))</span>
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<span class="k">return</span> <span class="n">base_matrix</span>
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<span class="n">j_a</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
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<span class="n">j_b</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">j_a</span> <span class="o">@</span> <span class="n">j_b</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">a</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">operands</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">for</span> <span class="n">op</span> <span class="ow">in</span> <span class="n">operands</span><span class="p">[</span><span class="mi">1</span><span class="p">:]:</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">r</span> <span class="o">@</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">op</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">op</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">else</span><span class="p">:</span>
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<span class="k">def</span> <span class="nf">_exp_to_jack</span><span class="p">(</span><span class="n">matrix</span><span class="p">):</span>
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<span class="n">base_matrix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">matrix</span><span class="p">)</span>
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@ -991,10 +989,10 @@ Obs valued.</li>
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<span class="n">base_matrix</span><span class="p">[</span><span class="n">n</span><span class="p">,</span> <span class="n">m</span><span class="p">]</span> <span class="o">=</span> <span class="n">import_jackknife</span><span class="p">(</span><span class="n">entry</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">base_matrix</span>
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<span class="n">j_a</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
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<span class="n">j_b</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">b</span><span class="p">)</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">j_a</span> <span class="o">@</span> <span class="n">j_b</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">a</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">operands</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<span class="k">for</span> <span class="n">op</span> <span class="ow">in</span> <span class="n">operands</span><span class="p">[</span><span class="mi">1</span><span class="p">:]:</span>
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<span class="n">r</span> <span class="o">=</span> <span class="n">r</span> <span class="o">@</span> <span class="n">_exp_to_jack</span><span class="p">(</span><span class="n">op</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">_imp_from_jack</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">op</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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</pre></div>
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</details>
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@ -1004,10 +1002,9 @@ Obs valued.</li>
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<h6 id="parameters">Parameters</h6>
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<ul>
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<li><strong>a</strong> (numpy.ndarray):
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First matrix, can be real or complex Obs valued</li>
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<li><strong>b</strong> (numpy.ndarray):
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Second matrix, can be real or complex Obs valued</li>
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<li><strong>operands</strong> (numpy.ndarray):
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Arbitrary number of 2d-numpy arrays which can be real or complex
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Obs valued.</li>
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<li><strong>For large matrices this is considerably faster compared to matmul.</strong></li>
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</ul>
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</div>
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@ -738,9 +738,17 @@
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<span class="sd"> """</span>
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<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_zero</span><span class="p">()</span> <span class="ow">or</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> <span class="o"><=</span> <span class="n">sigma</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">dvalue</span>
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<span class="k">def</span> <span class="nf">is_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="sd">"""Checks whether the observable is zero within machine precision."""</span>
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<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">delta</span><span class="p">)</span> <span class="k">for</span> <span class="n">delta</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
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<span class="k">def</span> <span class="nf">is_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rtol</span><span class="o">=</span><span class="mf">1.e-5</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1.e-8</span><span class="p">):</span>
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<span class="sd">"""Checks whether the observable is zero within a given tolerance.</span>
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|
||||
<span class="sd"> Parameters</span>
|
||||
<span class="sd"> ----------</span>
|
||||
<span class="sd"> rtol : float</span>
|
||||
<span class="sd"> Relative tolerance (for details see numpy documentation).</span>
|
||||
<span class="sd"> atol : float</span>
|
||||
<span class="sd"> Absolute tolerance (for details see numpy documentation).</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">rtol</span><span class="p">,</span> <span class="n">atol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">delta</span><span class="p">,</span> <span class="n">rtol</span><span class="p">,</span> <span class="n">atol</span><span class="p">)</span> <span class="k">for</span> <span class="n">delta</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">plot_tauint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">save</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""Plot integrated autocorrelation time for each ensemble.</span>
|
||||
|
|
@ -2341,9 +2349,17 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_zero</span><span class="p">()</span> <span class="ow">or</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> <span class="o"><=</span> <span class="n">sigma</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">dvalue</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">is_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="sd">"""Checks whether the observable is zero within machine precision."""</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">delta</span><span class="p">)</span> <span class="k">for</span> <span class="n">delta</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
|
||||
<span class="k">def</span> <span class="nf">is_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rtol</span><span class="o">=</span><span class="mf">1.e-5</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1.e-8</span><span class="p">):</span>
|
||||
<span class="sd">"""Checks whether the observable is zero within a given tolerance.</span>
|
||||
|
||||
<span class="sd"> Parameters</span>
|
||||
<span class="sd"> ----------</span>
|
||||
<span class="sd"> rtol : float</span>
|
||||
<span class="sd"> Relative tolerance (for details see numpy documentation).</span>
|
||||
<span class="sd"> atol : float</span>
|
||||
<span class="sd"> Absolute tolerance (for details see numpy documentation).</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">rtol</span><span class="p">,</span> <span class="n">atol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">delta</span><span class="p">,</span> <span class="n">rtol</span><span class="p">,</span> <span class="n">atol</span><span class="p">)</span> <span class="k">for</span> <span class="n">delta</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">plot_tauint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">save</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""Plot integrated autocorrelation time for each ensemble.</span>
|
||||
|
|
@ -3362,19 +3378,36 @@ Number of standard errors used for the check.</li>
|
|||
|
||||
|
||||
<span class="def">def</span>
|
||||
<span class="name">is_zero</span><span class="signature">(self)</span>:
|
||||
<span class="name">is_zero</span><span class="signature">(self, rtol=1e-05, atol=1e-08)</span>:
|
||||
</div>
|
||||
|
||||
<details>
|
||||
<summary>View Source</summary>
|
||||
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">is_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="sd">"""Checks whether the observable is zero within machine precision."""</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">delta</span><span class="p">)</span> <span class="k">for</span> <span class="n">delta</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
|
||||
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">is_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rtol</span><span class="o">=</span><span class="mf">1.e-5</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1.e-8</span><span class="p">):</span>
|
||||
<span class="sd">"""Checks whether the observable is zero within a given tolerance.</span>
|
||||
|
||||
<span class="sd"> Parameters</span>
|
||||
<span class="sd"> ----------</span>
|
||||
<span class="sd"> rtol : float</span>
|
||||
<span class="sd"> Relative tolerance (for details see numpy documentation).</span>
|
||||
<span class="sd"> atol : float</span>
|
||||
<span class="sd"> Absolute tolerance (for details see numpy documentation).</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">rtol</span><span class="p">,</span> <span class="n">atol</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">delta</span><span class="p">,</span> <span class="n">rtol</span><span class="p">,</span> <span class="n">atol</span><span class="p">)</span> <span class="k">for</span> <span class="n">delta</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
|
||||
</pre></div>
|
||||
|
||||
</details>
|
||||
|
||||
<div class="docstring"><p>Checks whether the observable is zero within machine precision.</p>
|
||||
<div class="docstring"><p>Checks whether the observable is zero within a given tolerance.</p>
|
||||
|
||||
<h6 id="parameters">Parameters</h6>
|
||||
|
||||
<ul>
|
||||
<li><strong>rtol</strong> (float):
|
||||
Relative tolerance (for details see numpy documentation).</li>
|
||||
<li><strong>atol</strong> (float):
|
||||
Absolute tolerance (for details see numpy documentation).</li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
|
||||
|
|
|
|||
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