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@ -232,7 +232,7 @@ The standard value for the parameter $S$ of this automatic windowing procedure i
<span class="n">my_sum</span> <span class="o">=</span> <span class="n">obs1</span> <span class="o">+</span> <span class="n">obs2</span>
<span class="n">my_sum</span><span class="o">.</span><span class="n">details</span><span class="p">()</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">2.00697958e+00</span> <span class="o">+/-</span> <span class="mf">0.00000000e+00</span> <span class="o">+/-</span> <span class="mf">0.00000000e+00</span> <span class="p">(</span><span class="mf">0.000</span><span class="o">%</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">2.00697958e+00</span>
<span class="o">&gt;</span> <span class="mi">1500</span> <span class="n">samples</span> <span class="ow">in</span> <span class="mi">2</span> <span class="n">ensembles</span><span class="p">:</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Ensemble</span> <span class="s1">&#39;ensemble1&#39;</span> <span class="p">:</span> <span class="mi">1000</span> <span class="n">configurations</span> <span class="p">(</span><span class="kn">from</span> <span class="mi">1</span> <span class="n">to</span> <span class="mi">1000</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Ensemble</span> <span class="s1">&#39;ensemble2&#39;</span> <span class="p">:</span> <span class="mi">500</span> <span class="n">configurations</span> <span class="p">(</span><span class="kn">from</span> <span class="mi">1</span> <span class="n">to</span> <span class="mi">500</span><span class="p">)</span>
@ -247,7 +247,7 @@ The standard value for the parameter $S$ of this automatic windowing procedure i
<span class="o">&gt;</span> <span class="n">my_sum</span> <span class="o">=</span> <span class="n">obs1</span> <span class="o">+</span> <span class="n">obs2</span>
<span class="o">&gt;</span> <span class="n">my_sum</span><span class="o">.</span><span class="n">details</span><span class="p">()</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">2.00697958e+00</span> <span class="o">+/-</span> <span class="mf">0.00000000e+00</span> <span class="o">+/-</span> <span class="mf">0.00000000e+00</span> <span class="p">(</span><span class="mf">0.000</span><span class="o">%</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">2.00697958e+00</span>
<span class="o">&gt;</span> <span class="mi">1500</span> <span class="n">samples</span> <span class="ow">in</span> <span class="mi">1</span> <span class="n">ensemble</span><span class="p">:</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Ensemble</span> <span class="s1">&#39;ensemble1&#39;</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Replicum</span> <span class="s1">&#39;r01&#39;</span> <span class="p">:</span> <span class="mi">1000</span> <span class="n">configurations</span> <span class="p">(</span><span class="kn">from</span> <span class="mi">1</span> <span class="n">to</span> <span class="mi">1000</span><span class="p">)</span>
@ -276,12 +276,24 @@ Passing arguments to the <code>gamma_method</code> still dominates over the dict
<div class="codehilite"><pre><span></span><code><span class="c1"># Observable defined on configurations 20 to 519</span>
<span class="n">obs1</span> <span class="o">=</span> <span class="n">pe</span><span class="o">.</span><span class="n">Obs</span><span class="p">([</span><span class="n">samples1</span><span class="p">],</span> <span class="p">[</span><span class="s1">&#39;ensemble1&#39;</span><span class="p">],</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="nb">range</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">520</span><span class="p">)])</span>
<span class="n">obs1</span><span class="o">.</span><span class="n">details</span><span class="p">()</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">9.98319881e-01</span>
<span class="o">&gt;</span> <span class="mi">500</span> <span class="n">samples</span> <span class="ow">in</span> <span class="mi">1</span> <span class="n">ensemble</span><span class="p">:</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Ensemble</span> <span class="s1">&#39;ensemble1&#39;</span> <span class="p">:</span> <span class="mi">500</span> <span class="n">configurations</span> <span class="p">(</span><span class="kn">from</span> <span class="mi">20</span> <span class="n">to</span> <span class="mi">519</span><span class="p">)</span>
<span class="c1"># Observable defined on every second configuration between 5 and 1003</span>
<span class="n">obs2</span> <span class="o">=</span> <span class="n">pe</span><span class="o">.</span><span class="n">Obs</span><span class="p">([</span><span class="n">samples2</span><span class="p">],</span> <span class="p">[</span><span class="s1">&#39;ensemble1&#39;</span><span class="p">],</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">1005</span><span class="p">,</span> <span class="mi">2</span><span class="p">)])</span>
<span class="n">obs2</span><span class="o">.</span><span class="n">details</span><span class="p">()</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">9.99100712e-01</span>
<span class="o">&gt;</span> <span class="mi">500</span> <span class="n">samples</span> <span class="ow">in</span> <span class="mi">1</span> <span class="n">ensemble</span><span class="p">:</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Ensemble</span> <span class="s1">&#39;ensemble1&#39;</span> <span class="p">:</span> <span class="mi">500</span> <span class="n">configurations</span> <span class="p">(</span><span class="kn">from</span> <span class="mi">5</span> <span class="n">to</span> <span class="mi">1003</span> <span class="ow">in</span> <span class="n">steps</span> <span class="n">of</span> <span class="mi">2</span><span class="p">)</span>
<span class="c1"># Observable defined on configurations 2, 9, 28, 29 and 501</span>
<span class="n">obs3</span> <span class="o">=</span> <span class="n">pe</span><span class="o">.</span><span class="n">Obs</span><span class="p">([</span><span class="n">samples3</span><span class="p">],</span> <span class="p">[</span><span class="s1">&#39;ensemble1&#39;</span><span class="p">],</span> <span class="n">idl</span><span class="o">=</span><span class="p">[[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">29</span><span class="p">,</span> <span class="mi">501</span><span class="p">]])</span>
<span class="n">obs3</span><span class="o">.</span><span class="n">details</span><span class="p">()</span>
<span class="o">&gt;</span> <span class="n">Result</span> <span class="mf">1.01718064e+00</span>
<span class="o">&gt;</span> <span class="mi">5</span> <span class="n">samples</span> <span class="ow">in</span> <span class="mi">1</span> <span class="n">ensemble</span><span class="p">:</span>
<span class="o">&gt;</span> <span class="err">·</span> <span class="n">Ensemble</span> <span class="s1">&#39;ensemble1&#39;</span> <span class="p">:</span> <span class="mi">5</span> <span class="n">configurations</span> <span class="p">(</span><span class="n">irregular</span> <span class="nb">range</span><span class="p">)</span>
</code></pre></div>
<p><strong>Warning:</strong> Irregular Monte Carlo chains can result in odd patterns in the autocorrelation functions.
@ -469,7 +481,7 @@ See <code><a href="pyerrors/obs.html#Obs.export_jackknife">pyerrors.obs.Obs.expo
<span class="sd">my_sum = obs1 + obs2</span>
<span class="sd">my_sum.details()</span>
<span class="sd">&gt; Result 2.00697958e+00 +/- 0.00000000e+00 +/- 0.00000000e+00 (0.000%)</span>
<span class="sd">&gt; Result 2.00697958e+00</span>
<span class="sd">&gt; 1500 samples in 2 ensembles:</span>
<span class="sd">&gt; · Ensemble &#39;ensemble1&#39; : 1000 configurations (from 1 to 1000)</span>
<span class="sd">&gt; · Ensemble &#39;ensemble2&#39; : 500 configurations (from 1 to 500)</span>
@ -484,7 +496,7 @@ See <code><a href="pyerrors/obs.html#Obs.export_jackknife">pyerrors.obs.Obs.expo
<span class="sd">&gt; my_sum = obs1 + obs2</span>
<span class="sd">&gt; my_sum.details()</span>
<span class="sd">&gt; Result 2.00697958e+00 +/- 0.00000000e+00 +/- 0.00000000e+00 (0.000%)</span>
<span class="sd">&gt; Result 2.00697958e+00</span>
<span class="sd">&gt; 1500 samples in 1 ensemble:</span>
<span class="sd">&gt; · Ensemble &#39;ensemble1&#39;</span>
<span class="sd">&gt; · Replicum &#39;r01&#39; : 1000 configurations (from 1 to 1000)</span>
@ -514,12 +526,25 @@ See <code><a href="pyerrors/obs.html#Obs.export_jackknife">pyerrors.obs.Obs.expo
<span class="sd">```python</span>
<span class="sd"># Observable defined on configurations 20 to 519</span>
<span class="sd">obs1 = pe.Obs([samples1], [&#39;ensemble1&#39;], idl=[range(20, 520)])</span>
<span class="sd">obs1.details()</span>
<span class="sd">&gt; Result 9.98319881e-01</span>
<span class="sd">&gt; 500 samples in 1 ensemble:</span>
<span class="sd">&gt; · Ensemble &#39;ensemble1&#39; : 500 configurations (from 20 to 519)</span>
<span class="sd"># Observable defined on every second configuration between 5 and 1003</span>
<span class="sd">obs2 = pe.Obs([samples2], [&#39;ensemble1&#39;], idl=[range(5, 1005, 2)])</span>
<span class="sd">obs2.details()</span>
<span class="sd">&gt; Result 9.99100712e-01</span>
<span class="sd">&gt; 500 samples in 1 ensemble:</span>
<span class="sd">&gt; · Ensemble &#39;ensemble1&#39; : 500 configurations (from 5 to 1003 in steps of 2)</span>
<span class="sd"># Observable defined on configurations 2, 9, 28, 29 and 501</span>
<span class="sd">obs3 = pe.Obs([samples3], [&#39;ensemble1&#39;], idl=[[2, 9, 28, 29, 501]])</span>
<span class="sd">obs3.details()</span>
<span class="sd">&gt; Result 1.01718064e+00</span>
<span class="sd">&gt; 5 samples in 1 ensemble:</span>
<span class="sd">&gt; · Ensemble &#39;ensemble1&#39; : 5 configurations (irregular range)</span>
<span class="sd">```</span>
<span class="sd">**Warning:** Irregular Monte Carlo chains can result in odd patterns in the autocorrelation functions.</span>

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@ -665,12 +665,14 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Description:&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tag</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Result</span><span class="se">\t</span><span class="s1"> </span><span class="si">%3.8e</span><span class="s1">&#39;</span> <span class="o">%</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="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="n">percentage</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">percentage</span> <span class="o">=</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">dvalue</span> <span class="o">/</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="mi">100</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Result</span><span class="se">\t</span><span class="s1"> </span><span class="si">%3.8e</span><span class="s1"> +/- </span><span class="si">%3.8e</span><span class="s1"> +/- </span><span class="si">%3.8e</span><span class="s1"> (</span><span class="si">%3.3f%%</span><span class="s1">)&#39;</span> <span class="o">%</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="bp">self</span><span class="o">.</span><span class="n">dvalue</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span><span class="p">,</span> <span class="n">percentage</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; Ensemble errors:&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">:</span>
@ -737,7 +739,7 @@
<span class="sd"> save : str</span>
<span class="sd"> saves the figure to a file named &#39;save&#39; if.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
@ -770,7 +772,7 @@
<span class="k">def</span> <span class="nf">plot_rho</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot normalized autocorrelation function time for each ensemble.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;W&#39;</span><span class="p">)</span>
@ -792,7 +794,7 @@
<span class="k">def</span> <span class="nf">plot_rep_dist</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot replica distribution for each ensemble with more than one replicum.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
@ -820,7 +822,7 @@
<span class="sd"> expand : bool</span>
<span class="sd"> show expanded history for irregular Monte Carlo chains (default: True).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
@ -844,7 +846,7 @@
<span class="k">def</span> <span class="nf">plot_piechart</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot piechart which shows the fractional contribution of each</span>
<span class="sd"> ensemble to the error and returns a dictionary containing the fractions.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error is 0.0&#39;</span><span class="p">)</span>
@ -2252,12 +2254,14 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Description:&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tag</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Result</span><span class="se">\t</span><span class="s1"> </span><span class="si">%3.8e</span><span class="s1">&#39;</span> <span class="o">%</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="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="n">percentage</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">percentage</span> <span class="o">=</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">dvalue</span> <span class="o">/</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="mi">100</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Result</span><span class="se">\t</span><span class="s1"> </span><span class="si">%3.8e</span><span class="s1"> +/- </span><span class="si">%3.8e</span><span class="s1"> +/- </span><span class="si">%3.8e</span><span class="s1"> (</span><span class="si">%3.3f%%</span><span class="s1">)&#39;</span> <span class="o">%</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="bp">self</span><span class="o">.</span><span class="n">dvalue</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span><span class="p">,</span> <span class="n">percentage</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; Ensemble errors:&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">:</span>
@ -2324,7 +2328,7 @@
<span class="sd"> save : str</span>
<span class="sd"> saves the figure to a file named &#39;save&#39; if.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
@ -2357,7 +2361,7 @@
<span class="k">def</span> <span class="nf">plot_rho</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot normalized autocorrelation function time for each ensemble.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;W&#39;</span><span class="p">)</span>
@ -2379,7 +2383,7 @@
<span class="k">def</span> <span class="nf">plot_rep_dist</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot replica distribution for each ensemble with more than one replicum.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
@ -2407,7 +2411,7 @@
<span class="sd"> expand : bool</span>
<span class="sd"> show expanded history for irregular Monte Carlo chains (default: True).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
@ -2431,7 +2435,7 @@
<span class="k">def</span> <span class="nf">plot_piechart</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot piechart which shows the fractional contribution of each</span>
<span class="sd"> ensemble to the error and returns a dictionary containing the fractions.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error is 0.0&#39;</span><span class="p">)</span>
@ -3205,12 +3209,14 @@ of the autocorrelation function (default True)</li>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Description:&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tag</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Result</span><span class="se">\t</span><span class="s1"> </span><span class="si">%3.8e</span><span class="s1">&#39;</span> <span class="o">%</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="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="n">percentage</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">percentage</span> <span class="o">=</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">dvalue</span> <span class="o">/</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="mi">100</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Result</span><span class="se">\t</span><span class="s1"> </span><span class="si">%3.8e</span><span class="s1"> +/- </span><span class="si">%3.8e</span><span class="s1"> +/- </span><span class="si">%3.8e</span><span class="s1"> (</span><span class="si">%3.3f%%</span><span class="s1">)&#39;</span> <span class="o">%</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="bp">self</span><span class="o">.</span><span class="n">dvalue</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span><span class="p">,</span> <span class="n">percentage</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; Ensemble errors:&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">:</span>
@ -3362,7 +3368,7 @@ Number of standard errors used for the check.</li>
<span class="sd"> save : str</span>
<span class="sd"> saves the figure to a file named &#39;save&#39; if.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
@ -3420,7 +3426,7 @@ saves the figure to a file named 'save' if.</li>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">plot_rho</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot normalized autocorrelation function time for each ensemble.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;W&#39;</span><span class="p">)</span>
@ -3460,7 +3466,7 @@ saves the figure to a file named 'save' if.</li>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">plot_rep_dist</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot replica distribution for each ensemble with more than one replicum.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
@ -3506,7 +3512,7 @@ saves the figure to a file named 'save' if.</li>
<span class="sd"> expand : bool</span>
<span class="sd"> show expanded history for irregular Monte Carlo chains (default: True).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">e</span><span class="p">,</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_names</span><span class="p">):</span>
@ -3555,7 +3561,7 @@ show expanded history for irregular Monte Carlo chains (default: True).</li>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">plot_piechart</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot piechart which shows the fractional contribution of each</span>
<span class="sd"> ensemble to the error and returns a dictionary containing the fractions.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_names&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Run the gamma method first.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error is 0.0&#39;</span><span class="p">)</span>

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docs/search.js
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