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Documentation updated
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fjosw
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2 changed files with 113 additions and 1 deletions
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@ -149,6 +149,9 @@
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<li>
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<a class="function" href="#Obs.dump">dump</a>
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</li>
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<li>
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<a class="function" href="#Obs.export_jackknife">export_jackknife</a>
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</li>
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<li>
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<a class="function" href="#Obs.sqrt">sqrt</a>
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</li>
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@ -871,6 +874,33 @@
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<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file_name</span><span class="p">,</span> <span class="s1">'wb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fb</span><span class="p">:</span>
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<span class="n">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fb</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">export_jackknife</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="sd">"""Export jackknife samples from the Obs</span>
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<span class="sd"> Returns</span>
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<span class="sd"> -------</span>
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<span class="sd"> np.ndarray</span>
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<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
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<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
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<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
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<span class="sd"> derived from the Obs. The current implementation only works for observables</span>
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<span class="sd"> defined on exactly one ensemble and replicum.</span>
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<span class="sd"> """</span>
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<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">names</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"'export_jackknife' is only implemented for Obs defined on one ensemble and replicum."</span><span class="p">)</span>
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<span class="n">name</span> <span class="o">=</span> <span class="bp">self</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">full_data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
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<span class="n">n</span> <span class="o">=</span> <span class="n">full_data</span><span class="o">.</span><span class="n">size</span>
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<span class="n">mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">full_data</span><span class="p">)</span>
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<span class="n">tmp_jacks</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">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
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<span class="n">tmp_jacks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span>
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<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
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<span class="n">tmp_jacks</span><span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">n</span> <span class="o">*</span> <span class="n">mean</span> <span class="o">-</span> <span class="n">full_data</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">tmp_jacks</span>
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<span class="k">def</span> <span class="fm">__float__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="k">return</span> <span class="nb">float</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
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@ -2425,6 +2455,33 @@
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<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file_name</span><span class="p">,</span> <span class="s1">'wb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">fb</span><span class="p">:</span>
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<span class="n">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fb</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">export_jackknife</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="sd">"""Export jackknife samples from the Obs</span>
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<span class="sd"> Returns</span>
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<span class="sd"> -------</span>
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<span class="sd"> np.ndarray</span>
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<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
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<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
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<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
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<span class="sd"> derived from the Obs. The current implementation only works for observables</span>
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<span class="sd"> defined on exactly one ensemble and replicum.</span>
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<span class="sd"> """</span>
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<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">names</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"'export_jackknife' is only implemented for Obs defined on one ensemble and replicum."</span><span class="p">)</span>
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<span class="n">name</span> <span class="o">=</span> <span class="bp">self</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">full_data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
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<span class="n">n</span> <span class="o">=</span> <span class="n">full_data</span><span class="o">.</span><span class="n">size</span>
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<span class="n">mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">full_data</span><span class="p">)</span>
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<span class="n">tmp_jacks</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">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
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<span class="n">tmp_jacks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span>
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<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
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<span class="n">tmp_jacks</span><span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">n</span> <span class="o">*</span> <span class="n">mean</span> <span class="o">-</span> <span class="n">full_data</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">tmp_jacks</span>
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<span class="k">def</span> <span class="fm">__float__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="k">return</span> <span class="nb">float</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
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@ -3556,6 +3613,61 @@ specifies a custom path for the file (default '.')</li>
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</div>
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</div>
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<div id="Obs.export_jackknife" class="classattr">
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<div class="attr function"><a class="headerlink" href="#Obs.export_jackknife">#  </a>
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<span class="def">def</span>
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<span class="name">export_jackknife</span><span class="signature">(self)</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">export_jackknife</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="sd">"""Export jackknife samples from the Obs</span>
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<span class="sd"> Returns</span>
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<span class="sd"> -------</span>
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<span class="sd"> np.ndarray</span>
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<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
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<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
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<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
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<span class="sd"> derived from the Obs. The current implementation only works for observables</span>
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<span class="sd"> defined on exactly one ensemble and replicum.</span>
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<span class="sd"> """</span>
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<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">names</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"'export_jackknife' is only implemented for Obs defined on one ensemble and replicum."</span><span class="p">)</span>
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<span class="n">name</span> <span class="o">=</span> <span class="bp">self</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">full_data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
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<span class="n">n</span> <span class="o">=</span> <span class="n">full_data</span><span class="o">.</span><span class="n">size</span>
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<span class="n">mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">full_data</span><span class="p">)</span>
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<span class="n">tmp_jacks</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">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
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<span class="n">tmp_jacks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span>
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<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
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<span class="n">tmp_jacks</span><span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">n</span> <span class="o">*</span> <span class="n">mean</span> <span class="o">-</span> <span class="n">full_data</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">tmp_jacks</span>
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</pre></div>
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</details>
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<div class="docstring"><p>Export jackknife samples from the Obs</p>
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<h6 id="returns">Returns</h6>
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<ul>
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<li><strong>np.ndarray</strong>: Returns a numpy array of length N + 1 where N is the number of samples
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for the given ensemble and replicum. The zeroth entry of the array contains
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the mean value of the Obs, entries 1 to N contain the N jackknife samples
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derived from the Obs. The current implementation only works for observables
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defined on exactly one ensemble and replicum.</li>
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</ul>
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</div>
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</div>
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<div id="Obs.sqrt" class="classattr">
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<div class="attr function"><a class="headerlink" href="#Obs.sqrt">#  </a>
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