pyerrors/docs/pyerrors/obs.html
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<h2>API Documentation</h2>
<ul class="memberlist">
<li>
<a class="class" href="#Obs">Obs</a>
<ul class="memberlist">
<li>
<a class="function" href="#Obs.__init__">Obs</a>
</li>
<li>
<a class="variable" href="#Obs.S_global">S_global</a>
</li>
<li>
<a class="variable" href="#Obs.S_dict">S_dict</a>
</li>
<li>
<a class="variable" href="#Obs.tau_exp_global">tau_exp_global</a>
</li>
<li>
<a class="variable" href="#Obs.tau_exp_dict">tau_exp_dict</a>
</li>
<li>
<a class="variable" href="#Obs.N_sigma_global">N_sigma_global</a>
</li>
<li>
<a class="variable" href="#Obs.N_sigma_dict">N_sigma_dict</a>
</li>
<li>
<a class="variable" href="#Obs.filter_eps">filter_eps</a>
</li>
<li>
<a class="variable" href="#Obs.names">names</a>
</li>
<li>
<a class="variable" href="#Obs.shape">shape</a>
</li>
<li>
<a class="variable" href="#Obs.r_values">r_values</a>
</li>
<li>
<a class="variable" href="#Obs.deltas">deltas</a>
</li>
<li>
<a class="variable" href="#Obs.idl">idl</a>
</li>
<li>
<a class="variable" href="#Obs.ddvalue">ddvalue</a>
</li>
<li>
<a class="variable" href="#Obs.reweighted">reweighted</a>
</li>
<li>
<a class="variable" href="#Obs.tag">tag</a>
</li>
<li>
<a class="variable" href="#Obs.value">value</a>
</li>
<li>
<a class="variable" href="#Obs.dvalue">dvalue</a>
</li>
<li>
<a class="variable" href="#Obs.e_names">e_names</a>
</li>
<li>
<a class="variable" href="#Obs.cov_names">cov_names</a>
</li>
<li>
<a class="variable" href="#Obs.mc_names">mc_names</a>
</li>
<li>
<a class="variable" href="#Obs.e_content">e_content</a>
</li>
<li>
<a class="variable" href="#Obs.covobs">covobs</a>
</li>
<li>
<a class="function" href="#Obs.gamma_method">gamma_method</a>
</li>
<li>
<a class="function" href="#Obs.details">details</a>
</li>
<li>
<a class="function" href="#Obs.is_zero_within_error">is_zero_within_error</a>
</li>
<li>
<a class="function" href="#Obs.is_zero">is_zero</a>
</li>
<li>
<a class="function" href="#Obs.plot_tauint">plot_tauint</a>
</li>
<li>
<a class="function" href="#Obs.plot_rho">plot_rho</a>
</li>
<li>
<a class="function" href="#Obs.plot_rep_dist">plot_rep_dist</a>
</li>
<li>
<a class="function" href="#Obs.plot_history">plot_history</a>
</li>
<li>
<a class="function" href="#Obs.plot_piechart">plot_piechart</a>
</li>
<li>
<a class="function" href="#Obs.dump">dump</a>
</li>
<li>
<a class="function" href="#Obs.export_jackknife">export_jackknife</a>
</li>
<li>
<a class="function" href="#Obs.sqrt">sqrt</a>
</li>
<li>
<a class="function" href="#Obs.log">log</a>
</li>
<li>
<a class="function" href="#Obs.exp">exp</a>
</li>
<li>
<a class="function" href="#Obs.sin">sin</a>
</li>
<li>
<a class="function" href="#Obs.cos">cos</a>
</li>
<li>
<a class="function" href="#Obs.tan">tan</a>
</li>
<li>
<a class="function" href="#Obs.arcsin">arcsin</a>
</li>
<li>
<a class="function" href="#Obs.arccos">arccos</a>
</li>
<li>
<a class="function" href="#Obs.arctan">arctan</a>
</li>
<li>
<a class="function" href="#Obs.sinh">sinh</a>
</li>
<li>
<a class="function" href="#Obs.cosh">cosh</a>
</li>
<li>
<a class="function" href="#Obs.tanh">tanh</a>
</li>
<li>
<a class="function" href="#Obs.arcsinh">arcsinh</a>
</li>
<li>
<a class="function" href="#Obs.arccosh">arccosh</a>
</li>
<li>
<a class="function" href="#Obs.arctanh">arctanh</a>
</li>
<li>
<a class="variable" href="#Obs.N">N</a>
</li>
<li>
<a class="variable" href="#Obs.N_sigma">N_sigma</a>
</li>
<li>
<a class="variable" href="#Obs.S">S</a>
</li>
<li>
<a class="variable" href="#Obs.e_ddvalue">e_ddvalue</a>
</li>
<li>
<a class="variable" href="#Obs.e_drho">e_drho</a>
</li>
<li>
<a class="variable" href="#Obs.e_dtauint">e_dtauint</a>
</li>
<li>
<a class="variable" href="#Obs.e_dvalue">e_dvalue</a>
</li>
<li>
<a class="variable" href="#Obs.e_n_dtauint">e_n_dtauint</a>
</li>
<li>
<a class="variable" href="#Obs.e_n_tauint">e_n_tauint</a>
</li>
<li>
<a class="variable" href="#Obs.e_rho">e_rho</a>
</li>
<li>
<a class="variable" href="#Obs.e_tauint">e_tauint</a>
</li>
<li>
<a class="variable" href="#Obs.e_windowsize">e_windowsize</a>
</li>
<li>
<a class="variable" href="#Obs.is_merged">is_merged</a>
</li>
<li>
<a class="variable" href="#Obs.tau_exp">tau_exp</a>
</li>
</ul>
</li>
<li>
<a class="class" href="#CObs">CObs</a>
<ul class="memberlist">
<li>
<a class="function" href="#CObs.__init__">CObs</a>
</li>
<li>
<a class="variable" href="#CObs.tag">tag</a>
</li>
<li>
<a class="variable" href="#CObs.real">real</a>
</li>
<li>
<a class="variable" href="#CObs.imag">imag</a>
</li>
<li>
<a class="function" href="#CObs.gamma_method">gamma_method</a>
</li>
<li>
<a class="function" href="#CObs.is_zero">is_zero</a>
</li>
<li>
<a class="function" href="#CObs.conjugate">conjugate</a>
</li>
</ul>
</li>
<li>
<a class="function" href="#derived_observable">derived_observable</a>
</li>
<li>
<a class="function" href="#reweight">reweight</a>
</li>
<li>
<a class="function" href="#correlate">correlate</a>
</li>
<li>
<a class="function" href="#covariance">covariance</a>
</li>
<li>
<a class="function" href="#import_jackknife">import_jackknife</a>
</li>
<li>
<a class="function" href="#merge_obs">merge_obs</a>
</li>
<li>
<a class="function" href="#cov_Obs">cov_Obs</a>
</li>
</ul>
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<section>
<h1 class="modulename">
<a href="./../pyerrors.html">pyerrors</a><wbr>.obs </h1>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">import</span> <span class="nn">pickle</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">autograd.numpy</span> <span class="k">as</span> <span class="nn">anp</span> <span class="c1"># Thinly-wrapped numpy</span>
<span class="kn">from</span> <span class="nn">autograd</span> <span class="kn">import</span> <span class="n">jacobian</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">scipy.stats</span> <span class="kn">import</span> <span class="n">skew</span><span class="p">,</span> <span class="n">skewtest</span><span class="p">,</span> <span class="n">kurtosis</span><span class="p">,</span> <span class="n">kurtosistest</span>
<span class="kn">import</span> <span class="nn">numdifftools</span> <span class="k">as</span> <span class="nn">nd</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">groupby</span>
<span class="kn">from</span> <span class="nn">.covobs</span> <span class="kn">import</span> <span class="n">Covobs</span>
<span class="k">class</span> <span class="nc">Obs</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;Class for a general observable.</span>
<span class="sd"> Instances of Obs are the basic objects of a pyerrors error analysis.</span>
<span class="sd"> They are initialized with a list which contains arrays of samples for</span>
<span class="sd"> different ensembles/replica and another list of same length which contains</span>
<span class="sd"> the names of the ensembles/replica. Mathematical operations can be</span>
<span class="sd"> performed on instances. The result is another instance of Obs. The error of</span>
<span class="sd"> an instance can be computed with the gamma_method. Also contains additional</span>
<span class="sd"> methods for output and visualization of the error calculation.</span>
<span class="sd"> Attributes</span>
<span class="sd"> ----------</span>
<span class="sd"> S_global : float</span>
<span class="sd"> Standard value for S (default 2.0)</span>
<span class="sd"> S_dict : dict</span>
<span class="sd"> Dictionary for S values. If an entry for a given ensemble</span>
<span class="sd"> exists this overwrites the standard value for that ensemble.</span>
<span class="sd"> tau_exp_global : float</span>
<span class="sd"> Standard value for tau_exp (default 0.0)</span>
<span class="sd"> tau_exp_dict : dict</span>
<span class="sd"> Dictionary for tau_exp values. If an entry for a given ensemble exists</span>
<span class="sd"> this overwrites the standard value for that ensemble.</span>
<span class="sd"> N_sigma_global : float</span>
<span class="sd"> Standard value for N_sigma (default 1.0)</span>
<span class="sd"> N_sigma_dict : dict</span>
<span class="sd"> Dictionary for N_sigma values. If an entry for a given ensemble exists</span>
<span class="sd"> this overwrites the standard value for that ensemble.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;names&#39;</span><span class="p">,</span> <span class="s1">&#39;shape&#39;</span><span class="p">,</span> <span class="s1">&#39;r_values&#39;</span><span class="p">,</span> <span class="s1">&#39;deltas&#39;</span><span class="p">,</span> <span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;_value&#39;</span><span class="p">,</span> <span class="s1">&#39;_dvalue&#39;</span><span class="p">,</span>
<span class="s1">&#39;ddvalue&#39;</span><span class="p">,</span> <span class="s1">&#39;reweighted&#39;</span><span class="p">,</span> <span class="s1">&#39;S&#39;</span><span class="p">,</span> <span class="s1">&#39;tau_exp&#39;</span><span class="p">,</span> <span class="s1">&#39;N_sigma&#39;</span><span class="p">,</span>
<span class="s1">&#39;e_dvalue&#39;</span><span class="p">,</span> <span class="s1">&#39;e_ddvalue&#39;</span><span class="p">,</span> <span class="s1">&#39;e_tauint&#39;</span><span class="p">,</span> <span class="s1">&#39;e_dtauint&#39;</span><span class="p">,</span>
<span class="s1">&#39;e_windowsize&#39;</span><span class="p">,</span> <span class="s1">&#39;e_rho&#39;</span><span class="p">,</span> <span class="s1">&#39;e_drho&#39;</span><span class="p">,</span> <span class="s1">&#39;e_n_tauint&#39;</span><span class="p">,</span> <span class="s1">&#39;e_n_dtauint&#39;</span><span class="p">,</span>
<span class="s1">&#39;idl&#39;</span><span class="p">,</span> <span class="s1">&#39;is_merged&#39;</span><span class="p">,</span> <span class="s1">&#39;tag&#39;</span><span class="p">,</span> <span class="s1">&#39;_covobs&#39;</span><span class="p">,</span> <span class="s1">&#39;__dict__&#39;</span><span class="p">]</span>
<span class="n">S_global</span> <span class="o">=</span> <span class="mf">2.0</span>
<span class="n">S_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">tau_exp_global</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="n">tau_exp_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">N_sigma_global</span> <span class="o">=</span> <span class="mf">1.0</span>
<span class="n">N_sigma_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">filter_eps</span> <span class="o">=</span> <span class="mf">1e-10</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">samples</span><span class="p">,</span> <span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">means</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Initialize Obs object.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> samples : list</span>
<span class="sd"> list of numpy arrays containing the Monte Carlo samples</span>
<span class="sd"> names : list</span>
<span class="sd"> list of strings labeling the individual samples</span>
<span class="sd"> idl : list, optional</span>
<span class="sd"> list of ranges or lists on which the samples are defined</span>
<span class="sd"> means : list, optional</span>
<span class="sd"> list of mean values for the case that the mean values were</span>
<span class="sd"> already subtracted from the samples</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">means</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of samples and names incompatible.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">idl</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of idl incompatible with samples and names.&#39;</span><span class="p">)</span>
<span class="n">name_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="k">if</span> <span class="n">name_length</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name_length</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">names</span><span class="p">)):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;names are not unique.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">&#39;All names have to be strings.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">str</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">&#39;All names have to be strings.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">min</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">samples</span><span class="p">)</span> <span class="o">&lt;=</span> <span class="mi">4</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Samples have to have at least 5 entries.&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">r_values</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_covobs</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">):</span>
<span class="k">if</span> <span class="n">idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="nb">range</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">idx</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
<span class="n">dc</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">idx</span><span class="p">))</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">any</span><span class="p">(</span><span class="n">dc</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Unsorted idx for idl[</span><span class="si">%s</span><span class="s2">]&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">dc</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">dc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">dc</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;incompatible type for idl[</span><span class="si">%s</span><span class="s1">].&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">if</span> <span class="n">means</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">mean</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">,</span> <span class="n">means</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</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> <span class="o">=</span> <span class="n">mean</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="n">sample</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Incompatible samples and idx for </span><span class="si">%s</span><span class="s1">: </span><span class="si">%d</span><span class="s1"> vs. </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]))</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> <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">sample</span><span class="p">)</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="n">sample</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>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</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>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">/=</span> <span class="bp">self</span><span class="o">.</span><span class="n">N</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">=</span> <span class="mi">0</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="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">value</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">dvalue</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">e_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;|&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">names</span><span class="p">]))</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">cov_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="o">.</span><span class="n">keys</span><span class="p">()]))</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">mc_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;|&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">names</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">cov_names</span><span class="p">]))</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">e_content</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">res</span> <span class="o">=</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">res</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;|&#39;</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="k">if</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="n">res</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">e_name</span><span class="p">)</span>
<span class="k">return</span> <span class="n">res</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">covobs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_covobs</span>
<span class="k">def</span> <span class="nf">gamma_method</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Estimate the error and related properties of the Obs.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> S : float</span>
<span class="sd"> specifies a custom value for the parameter S (default 2.0).</span>
<span class="sd"> If set to 0 it is assumed that the data exhibits no</span>
<span class="sd"> autocorrelation. In this case the error estimates coincides</span>
<span class="sd"> with the sample standard error.</span>
<span class="sd"> tau_exp : float</span>
<span class="sd"> positive value triggers the critical slowing down analysis</span>
<span class="sd"> (default 0.0).</span>
<span class="sd"> N_sigma : float</span>
<span class="sd"> number of standard deviations from zero until the tail is</span>
<span class="sd"> attached to the autocorrelation function (default 1).</span>
<span class="sd"> fft : bool</span>
<span class="sd"> determines whether the fft algorithm is used for the computation</span>
<span class="sd"> of the autocorrelation function (default True)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">e_content</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_content</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_gamma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span> <span class="o">=</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="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">S</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fft&#39;</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">False</span><span class="p">:</span>
<span class="n">fft</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">fft</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">_parse_kwarg</span><span class="p">(</span><span class="n">kwarg_name</span><span class="p">):</span>
<span class="k">if</span> <span class="n">kwarg_name</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">kwarg_name</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">)):</span>
<span class="k">if</span> <span class="n">tmp</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39; has to be larger or equal to 0.&#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="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39; is not in proper format.&#39;</span><span class="p">)</span>
<span class="k">else</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="n">e_name</span> <span class="ow">in</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_dict&#39;</span><span class="p">):</span>
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_dict&#39;</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_global&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;S&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;tau_exp&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;N_sigma&#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">mc_names</span><span class="p">):</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]])</span>
<span class="n">w_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calc_gamma</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">)</span>
<span class="n">gamma_div</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="n">gamma_div</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calc_gamma</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">])),</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">)</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/=</span> <span class="n">gamma_div</span><span class="p">[:</span><span class="n">w_max</span><span class="p">]</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mi">10</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">finfo</span><span class="p">(</span><span class="nb">float</span><span class="p">)</span><span class="o">.</span><span class="n">tiny</span><span class="p">:</span> <span class="c1"># Prevent division by zero</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">continue</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">w_max</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(([</span><span class="mf">0.5</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:])))</span>
<span class="c1"># Make sure no entry of tauint is smaller than 0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">finfo</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span><span class="o">.</span><span class="n">eps</span>
<span class="c1"># hep-lat/0306017 eq. (42)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">w_max</span><span class="p">)</span> <span class="o">+</span> <span class="mf">0.5</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="k">def</span> <span class="nf">_compute_drho</span><span class="p">(</span><span class="n">i</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</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="n">w_max</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</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="mi">1</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="n">w_max</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">i</span><span class="p">]])</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="n">w_max</span> <span class="o">-</span> <span class="n">i</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">tmp</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">texp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span>
<span class="c1"># Critical slowing down analysis</span>
<span class="k">if</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">&lt;=</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Need at least 8 samples for tau_exp error analysis&quot;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span><span class="p">):</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
<span class="c1"># Bias correction hep-lat/0306017 eq. (49) included</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">+</span> <span class="n">texp</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">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> <span class="c1"># The absolute makes sure, that the tail contribution is always positive</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">texp</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span>
<span class="c1"># Error of tau_exp neglected so far, missing term: self.e_rho[e_name][n + 1] ** 2 * d_tau_exp ** 2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">n</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">n</span>
<span class="k">break</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">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="p">(</span><span class="n">e_N</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mf">0.5</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Standard automatic windowing procedure</span>
<span class="n">tau</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">((</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">g_w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span> <span class="o">/</span> <span class="n">tau</span><span class="p">)</span> <span class="o">-</span> <span class="n">tau</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span> <span class="o">*</span> <span class="n">e_N</span><span class="p">)</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">):</span>
<span class="k">if</span> <span class="n">n</span> <span class="o">&lt;</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">g_w</span><span class="p">[</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="n">w_max</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="c1"># Bias correction hep-lat/0306017 eq. (49)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">n</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">n</span>
<span class="k">break</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">+=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</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">cov_names</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">errsq</span><span class="p">())</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">**</span><span class="mi">2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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="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="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span>
<span class="k">return</span>
<span class="k">def</span> <span class="nf">_calc_gamma</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Calculate Gamma_{AA} from the deltas, which are defined on idx.</span>
<span class="sd"> idx is assumed to be a contiguous range (possibly with a stepsize != 1)</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas : list</span>
<span class="sd"> List of fluctuations</span>
<span class="sd"> idx : list</span>
<span class="sd"> List or range of configurations on which the deltas are defined.</span>
<span class="sd"> shape : int</span>
<span class="sd"> Number of configurations in idx.</span>
<span class="sd"> w_max : int</span>
<span class="sd"> Upper bound for the summation window.</span>
<span class="sd"> fft : bool</span>
<span class="sd"> determines whether the fft algorithm is used for the computation</span>
<span class="sd"> of the autocorrelation function.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">gamma</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">w_max</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">=</span> <span class="n">_expand_deltas</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">)</span>
<span class="n">new_shape</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span>
<span class="k">if</span> <span class="n">fft</span><span class="p">:</span>
<span class="n">max_gamma</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">new_shape</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span>
<span class="c1"># The padding for the fft has to be even</span>
<span class="n">padding</span> <span class="o">=</span> <span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span> <span class="o">+</span> <span class="p">(</span><span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span><span class="p">)</span> <span class="o">%</span> <span class="mi">2</span>
<span class="n">gamma</span><span class="p">[:</span><span class="n">max_gamma</span><span class="p">]</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">padding</span><span class="p">))</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)[:</span><span class="n">max_gamma</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">w_max</span><span class="p">):</span>
<span class="k">if</span> <span class="n">new_shape</span> <span class="o">-</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">gamma</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="o">+=</span> <span class="n">deltas</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="n">new_shape</span> <span class="o">-</span> <span class="n">n</span><span class="p">]</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">deltas</span><span class="p">[</span><span class="n">n</span><span class="p">:</span><span class="n">new_shape</span><span class="p">])</span>
<span class="k">return</span> <span class="n">gamma</span>
<span class="k">def</span> <span class="nf">details</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ens_content</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Output detailed properties of the Obs.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> ens_content : bool</span>
<span class="sd"> print details about the ensembles and replica if true.</span>
<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">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">mc_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_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;&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;</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">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; t_int</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"> tau_exp = </span><span class="si">%3.2f</span><span class="s1">, N_sigma = </span><span class="si">%1.0i</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">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; t_int</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"> S = </span><span class="si">%3.2f</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">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</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">cov_names</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="n">ens_content</span> <span class="ow">is</span> <span class="kc">True</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">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">N</span><span class="p">,</span> <span class="s1">&#39;samples in&#39;</span><span class="p">,</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="s1">&#39;ensemble:&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">N</span><span class="p">,</span> <span class="s1">&#39;samples in&#39;</span><span class="p">,</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="s1">&#39;ensembles:&#39;</span><span class="p">)</span>
<span class="n">my_string_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_content</span><span class="o">.</span><span class="n">items</span><span class="p">()):</span>
<span class="k">if</span> <span class="n">key</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Ensemble &#39;&quot;</span> <span class="o">+</span> <span class="n">key</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39;: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="si">}</span><span class="s1"> configurations&#39;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39; (from </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">start</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">step</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="sa">f</span><span class="s1">&#39; in steps of </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">step</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="s1">&#39; (irregular range)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">sublist</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">value</span><span class="p">:</span>
<span class="n">my_substring</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Replicum &#39;&quot;</span> <span class="o">+</span> <span class="n">v</span><span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">key</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39;: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="si">}</span><span class="s1"> configurations&#39;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39; (from </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">start</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">step</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="sa">f</span><span class="s1">&#39; in steps of </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">step</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="s1">&#39; (irregular range)&#39;</span>
<span class="n">sublist</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_substring</span><span class="p">)</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">sublist</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Covobs &#39;&quot;</span> <span class="o">+</span> <span class="n">key</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="n">my_string_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_string</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">my_string_list</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">is_zero_within_error</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Checks whether the observable is zero within &#39;sigma&#39; standard errors.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> sigma : int</span>
<span class="sd"> Number of standard errors used for the check.</span>
<span class="sd"> Works only properly when the gamma method was run.</span>
<span class="sd"> &quot;&quot;&quot;</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">&lt;=</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="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">&quot;&quot;&quot;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"> &quot;&quot;&quot;</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="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="o">.</span><span class="n">errsq</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">covobs</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">&quot;&quot;&quot;Plot integrated autocorrelation time for each ensemble.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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_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">mc_names</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>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;$W$&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;$\tau_\mathrm</span><span class="si">{int}</span><span class="s1">$&#39;</span><span class="p">)</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]]</span>
<span class="n">x_help</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="n">y_help</span> <span class="o">=</span> <span class="p">(</span><span class="n">x_help</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</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">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">x_help</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</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> <span class="o">+</span> <span class="n">base</span>
<span class="n">x_arr</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x_arr</span><span class="p">,</span> <span class="n">y_help</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span>
<span class="n">yerr</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span> <span class="n">fmt</span><span class="o">=</span><span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">mfc</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">&#39;axes.facecolor&#39;</span><span class="p">])</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.5</span>
<span class="n">label</span> <span class="o">=</span> <span class="n">e_name</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;, $\tau_\mathrm</span><span class="si">{exp}</span><span class="s1">$=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">label</span> <span class="o">=</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;, S=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mf">10.5</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">length</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">yerr</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">(</span><span class="n">bottom</span><span class="o">=</span><span class="mf">0.0</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">))</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="n">save</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot normalized autocorrelation function time for each ensemble.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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_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">mc_names</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>
<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>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;rho&#39;</span><span class="p">)</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">length</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">length</span><span class="p">],</span> <span class="n">yerr</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;r&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="mi">0</span><span class="p">],</span> <span class="s1">&#39;k-&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.5</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Rho &#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;, tau\_exp=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">)))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mf">10.5</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Rho &#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;, S=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">)))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">],</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="s1">&#39;k--&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">))</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_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">mc_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>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;No replica distribution for a single replicum (&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;)&#39;</span><span class="p">)</span>
<span class="k">continue</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">sub_r_mean</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="n">sub_r_mean</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">]</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span>
<span class="n">sub_r_mean</span> <span class="o">/=</span> <span class="n">e_N</span>
<span class="n">arr</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="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="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">arr</span><span class="p">[</span><span class="n">r</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">-</span> <span class="n">sub_r_mean</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">e_N</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">rwidth</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</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="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Replica distribution&#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39; (mean=0, var=1)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">plot_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot derived Monte Carlo history for each ensemble</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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">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">mc_names</span><span class="p">):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp_expanded</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">])</span>
<span class="k">if</span> <span class="n">expand</span><span class="p">:</span>
<span class="n">tmp_expanded</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_expand_deltas</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">])</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tmp_expanded</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">e_N</span><span class="p">)</span>
<span class="n">y_test</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="n">expand</span><span class="p">:</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">tmp_expanded</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">y_test</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">fmt</span><span class="o">=</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">e_N</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">e_name</span> <span class="o">+</span> <span class="sa">f</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">skew: </span><span class="si">{</span><span class="n">skew</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> (p=</span><span class="si">{</span><span class="n">skewtest</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="o">.</span><span class="n">pvalue</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">), kurtosis: </span><span class="si">{</span><span class="n">kurtosis</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> (p=</span><span class="si">{</span><span class="n">kurtosistest</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="o">.</span><span class="n">pvalue</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</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_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>
<span class="n">labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_names</span>
<span class="n">sizes</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">**</span> <span class="mi">2</span>
<span class="n">fig1</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">pie</span><span class="p">(</span><span class="n">sizes</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">,</span> <span class="n">startangle</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span> <span class="n">normalize</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">&#39;equal&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">return</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">zip</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">sizes</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">,</span> <span class="n">datatype</span><span class="o">=</span><span class="s2">&quot;json.gz&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Dump the Obs to a file &#39;name&#39; of chosen format.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> filename : str</span>
<span class="sd"> name of the file to be saved.</span>
<span class="sd"> datatype : str</span>
<span class="sd"> Format of the exported file. Supported formats include</span>
<span class="sd"> &quot;json.gz&quot; and &quot;pickle&quot;</span>
<span class="sd"> path : str</span>
<span class="sd"> specifies a custom path for the file (default &#39;.&#39;)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="s1">&#39;path&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">file_name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;path&#39;</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">filename</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">file_name</span> <span class="o">=</span> <span class="n">filename</span>
<span class="k">if</span> <span class="n">datatype</span> <span class="o">==</span> <span class="s2">&quot;json.gz&quot;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">.input.json</span> <span class="kn">import</span> <span class="n">dump_to_json</span>
<span class="n">dump_to_json</span><span class="p">([</span><span class="bp">self</span><span class="p">],</span> <span class="n">file_name</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">datatype</span> <span class="o">==</span> <span class="s2">&quot;pickle&quot;</span><span class="p">:</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file_name</span> <span class="o">+</span> <span class="s1">&#39;.p&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">fb</span><span class="p">:</span>
<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>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Unknown datatype &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">datatype</span><span class="p">))</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>
<span class="sd">&quot;&quot;&quot;Export jackknife samples from the Obs</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> numpy.ndarray</span>
<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
<span class="sd"> derived from the Obs. The current implementation only works for observables</span>
<span class="sd"> defined on exactly one ensemble and replicum. The derived jackknife samples</span>
<span class="sd"> should agree with samples from a full jackknife analysis up to O(1/N).</span>
<span class="sd"> &quot;&quot;&quot;</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">names</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;&#39;export_jackknife&#39; is only implemented for Obs defined on one ensemble and replicum.&quot;</span><span class="p">)</span>
<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>
<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>
<span class="n">n</span> <span class="o">=</span> <span class="n">full_data</span><span class="o">.</span><span class="n">size</span>
<span class="n">mean</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span>
<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>
<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="n">mean</span>
<span class="n">tmp_jacks</span><span class="p">[</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="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">return</span> <span class="n">tmp_jacks</span>
<span class="k">def</span> <span class="fm">__float__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<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>
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;Obs[&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;]&#39;</span>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</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">return</span> <span class="nb">str</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">fexp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">floor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">log10</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="k">if</span> <span class="n">fexp</span> <span class="o">&lt;</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="s1">&#39;{:</span><span class="si">{form}</span><span class="s1">}(</span><span class="si">{:2.0f}</span><span class="s1">)&#39;</span><span class="o">.</span><span class="n">format</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="o">*</span> <span class="mi">10</span> <span class="o">**</span> <span class="p">(</span><span class="o">-</span><span class="n">fexp</span> <span class="o">+</span> <span class="mi">1</span><span class="p">),</span> <span class="n">form</span><span class="o">=</span><span class="s1">&#39;.&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="o">-</span><span class="nb">int</span><span class="p">(</span><span class="n">fexp</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;f&#39;</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">fexp</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="s1">&#39;</span><span class="si">{:.1f}</span><span class="s1">(</span><span class="si">{:1.1f}</span><span class="s1">)&#39;</span><span class="o">.</span><span class="n">format</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="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="s1">&#39;</span><span class="si">{:.0f}</span><span class="s1">(</span><span class="si">{:2.0f}</span><span class="s1">)&#39;</span><span class="o">.</span><span class="n">format</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="c1"># Overload comparisons</span>
<span class="k">def</span> <span class="fm">__lt__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&lt;</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__le__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&lt;=</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__gt__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&gt;</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__ge__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&gt;=</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">is_zero</span><span class="p">()</span>
<span class="k">def</span> <span class="fm">__ne__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="ow">not</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">is_zero</span><span class="p">()</span>
<span class="c1"># Overload math operations</span>
<span class="k">def</span> <span class="fm">__add__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">+</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__radd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">+</span> <span class="n">y</span>
<span class="k">def</span> <span class="fm">__mul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">y</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">value</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">*</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="nb">complex</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span> <span class="o">*</span> <span class="n">y</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span> <span class="o">*</span> <span class="n">y</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">y</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rmul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">*</span> <span class="n">y</span>
<span class="k">def</span> <span class="fm">__sub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">-</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rsub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">y</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__neg__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="bp">self</span>
<span class="k">def</span> <span class="fm">__truediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">y</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">/</span> <span class="n">y</span><span class="o">.</span><span class="n">value</span> <span class="o">**</span> <span class="mi">2</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">/</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">y</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rtruediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</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="n">y</span><span class="o">.</span><span class="n">value</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">**</span> <span class="mi">2</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">o</span> <span class="o">/</span> <span class="bp">self</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">y</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="n">y</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">**</span> <span class="mi">2</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__pow__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">**</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">**</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rpow__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">**</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="bp">self</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">y</span> <span class="o">**</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__abs__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="c1"># Overload numpy functions</span>
<span class="k">def</span> <span class="nf">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="mi">2</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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">def</span> <span class="nf">log</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</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="k">def</span> <span class="nf">exp</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">exp</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">def</span> <span class="nf">sin</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">cos</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">def</span> <span class="nf">cos</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">sin</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">def</span> <span class="nf">tan</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">tan</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</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="mi">2</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arcsin</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arcsin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arccos</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arccos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arctan</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arctan</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">sinh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sinh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">cosh</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">def</span> <span class="nf">cosh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">cosh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">sinh</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">def</span> <span class="nf">tanh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">cosh</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="mi">2</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arcsinh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arcsinh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arccosh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arccosh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arctanh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arctanh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">class</span> <span class="nc">CObs</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;Class for a complex valued observable.&quot;&quot;&quot;</span>
<span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;_real&#39;</span><span class="p">,</span> <span class="s1">&#39;_imag&#39;</span><span class="p">,</span> <span class="s1">&#39;tag&#39;</span><span class="p">]</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">real</span><span class="p">,</span> <span class="n">imag</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_real</span> <span class="o">=</span> <span class="n">real</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imag</span> <span class="o">=</span> <span class="n">imag</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">real</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_real</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">imag</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imag</span>
<span class="k">def</span> <span class="nf">gamma_method</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Executes the gamma_method for the real and the imaginary part.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</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="sd">&quot;&quot;&quot;Checks whether both real and imaginary part are zero within machine precision.&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">==</span> <span class="mf">0.0</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">==</span> <span class="mf">0.0</span>
<span class="k">def</span> <span class="nf">conjugate</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__add__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">other</span> <span class="o">+</span> <span class="bp">self</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">+</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__radd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">+</span> <span class="n">y</span>
<span class="k">def</span> <span class="fm">__sub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="n">other</span> <span class="o">-</span> <span class="bp">self</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">-</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__rsub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">other</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__mul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">other</span> <span class="o">*</span> <span class="bp">self</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">Obs</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">]):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">],</span>
<span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">other</span><span class="o">.</span><span class="n">real</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">real</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">-</span><span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">value</span><span class="p">]),</span>
<span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">],</span>
<span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">other</span><span class="o">.</span><span class="n">imag</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">imag</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</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">real</span><span class="o">.</span><span class="n">value</span><span class="p">]))</span>
<span class="k">elif</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__rmul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">*</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__truediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="mi">1</span> <span class="o">/</span> <span class="p">(</span><span class="n">other</span> <span class="o">/</span> <span class="bp">self</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="n">r</span> <span class="o">=</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span> <span class="o">**</span> <span class="mi">2</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">/</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">/</span> <span class="n">other</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__rtruediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="n">r</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">**</span> <span class="mi">2</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span> <span class="o">/</span> <span class="n">r</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span> <span class="o">/</span> <span class="n">r</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__abs__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__neg__</span><span class="p">(</span><span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;(&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">)</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">&gt;=</span> <span class="mf">0.0</span><span class="p">)</span> <span class="o">*</span> <span class="s1">&#39;+&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;j)&#39;</span>
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;CObs[&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;]&#39;</span>
<span class="k">def</span> <span class="nf">_expand_deltas</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Expand deltas defined on idx to a regular, contiguous range, where holes are filled by 0.</span>
<span class="sd"> If idx is of type range, the deltas are not changed</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas : list</span>
<span class="sd"> List of fluctuations</span>
<span class="sd"> idx : list</span>
<span class="sd"> List or range of configs on which the deltas are defined.</span>
<span class="sd"> shape : int</span>
<span class="sd"> Number of configs in idx.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="nb">range</span><span class="p">):</span>
<span class="k">return</span> <span class="n">deltas</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">ret</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">idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<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">shape</span><span class="p">):</span>
<span class="n">ret</span><span class="p">[</span><span class="n">idx</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">=</span> <span class="n">deltas</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="k">return</span> <span class="n">ret</span>
<span class="k">def</span> <span class="nf">_merge_idx</span><span class="p">(</span><span class="n">idl</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Returns the union of all lists in idl</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> idl : list</span>
<span class="sd"> List of lists or ranges.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Use groupby to efficiently check whether all elements of idl are identical</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">g</span> <span class="o">=</span> <span class="n">groupby</span><span class="p">(</span><span class="n">idl</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">next</span><span class="p">(</span><span class="n">g</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">next</span><span class="p">(</span><span class="n">g</span><span class="p">,</span> <span class="kc">False</span><span class="p">):</span>
<span class="k">return</span> <span class="n">idl</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span>
<span class="k">pass</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">([</span><span class="nb">type</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">idl</span><span class="p">]):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">idl</span><span class="p">]))</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">idstart</span> <span class="o">=</span> <span class="nb">min</span><span class="p">([</span><span class="n">idx</span><span class="o">.</span><span class="n">start</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">idl</span><span class="p">])</span>
<span class="n">idstop</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="n">idx</span><span class="o">.</span><span class="n">stop</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">idl</span><span class="p">])</span>
<span class="n">idstep</span> <span class="o">=</span> <span class="nb">min</span><span class="p">([</span><span class="n">idx</span><span class="o">.</span><span class="n">step</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">idl</span><span class="p">])</span>
<span class="k">return</span> <span class="nb">range</span><span class="p">(</span><span class="n">idstart</span><span class="p">,</span> <span class="n">idstop</span><span class="p">,</span> <span class="n">idstep</span><span class="p">)</span>
<span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">()</span><span class="o">.</span><span class="n">union</span><span class="p">(</span><span class="o">*</span><span class="n">idl</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">_expand_deltas_for_merge</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">new_idx</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Expand deltas defined on idx to the list of configs that is defined by new_idx.</span>
<span class="sd"> New, empy entries are filled by 0. If idx and new_idx are of type range, the smallest</span>
<span class="sd"> common divisor of the step sizes is used as new step size.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas : list</span>
<span class="sd"> List of fluctuations</span>
<span class="sd"> idx : list</span>
<span class="sd"> List or range of configs on which the deltas are defined.</span>
<span class="sd"> Has to be a subset of new_idx.</span>
<span class="sd"> shape : list</span>
<span class="sd"> Number of configs in idx.</span>
<span class="sd"> new_idx : list</span>
<span class="sd"> List of configs that defines the new range.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span> <span class="ow">and</span> <span class="nb">type</span><span class="p">(</span><span class="n">new_idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span><span class="p">:</span>
<span class="k">if</span> <span class="n">idx</span> <span class="o">==</span> <span class="n">new_idx</span><span class="p">:</span>
<span class="k">return</span> <span class="n">deltas</span>
<span class="n">ret</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">new_idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<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">shape</span><span class="p">):</span>
<span class="n">ret</span><span class="p">[</span><span class="n">idx</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">=</span> <span class="n">deltas</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">ret</span><span class="p">[</span><span class="n">new_idx</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <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="nb">len</span><span class="p">(</span><span class="n">new_idx</span><span class="p">))])</span>
<span class="k">def</span> <span class="nf">_filter_zeroes</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="n">Obs</span><span class="o">.</span><span class="n">filter_eps</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Filter out all configurations with vanishing fluctuation such that they do not</span>
<span class="sd"> contribute to the error estimate anymore. Returns the new deltas and</span>
<span class="sd"> idx according to the filtering.</span>
<span class="sd"> A fluctuation is considered to be vanishing, if it is smaller than eps times</span>
<span class="sd"> the mean of the absolute values of all deltas in one list.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas : list</span>
<span class="sd"> List of fluctuations</span>
<span class="sd"> idx : list</span>
<span class="sd"> List or ranges of configs on which the deltas are defined.</span>
<span class="sd"> eps : float</span>
<span class="sd"> Prefactor that enters the filter criterion.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">new_deltas</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_idx</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">maxd</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">np</span><span class="o">.</span><span class="n">fabs</span><span class="p">(</span><span class="n">deltas</span><span class="p">))</span>
<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="nb">len</span><span class="p">(</span><span class="n">deltas</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">deltas</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="o">&gt;</span> <span class="n">eps</span> <span class="o">*</span> <span class="n">maxd</span><span class="p">:</span>
<span class="n">new_deltas</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">deltas</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="n">new_idx</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">idx</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="k">if</span> <span class="n">new_idx</span><span class="p">:</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">new_deltas</span><span class="p">),</span> <span class="n">new_idx</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span>
<span class="k">def</span> <span class="nf">derived_observable</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">array_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Construct a derived Obs according to func(data, **kwargs) using automatic differentiation.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> func : object</span>
<span class="sd"> arbitrary function of the form func(data, **kwargs). For the</span>
<span class="sd"> automatic differentiation to work, all numpy functions have to have</span>
<span class="sd"> the autograd wrapper (use &#39;import autograd.numpy as anp&#39;).</span>
<span class="sd"> data : list</span>
<span class="sd"> list of Obs, e.g. [obs1, obs2, obs3].</span>
<span class="sd"> num_grad : bool</span>
<span class="sd"> if True, numerical derivatives are used instead of autograd</span>
<span class="sd"> (default False). To control the numerical differentiation the</span>
<span class="sd"> kwargs of numdifftools.step_generators.MaxStepGenerator</span>
<span class="sd"> can be used.</span>
<span class="sd"> man_grad : list</span>
<span class="sd"> manually supply a list or an array which contains the jacobian</span>
<span class="sd"> of func. Use cautiously, supplying the wrong derivative will</span>
<span class="sd"> not be intercepted.</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> For simple mathematical operations it can be practical to use anonymous</span>
<span class="sd"> functions. For the ratio of two observables one can e.g. use</span>
<span class="sd"> new_obs = derived_observable(lambda x: x[0] / x[1], [obs1, obs2])</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="n">raveled_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="c1"># Workaround for matrix operations containing non Obs data</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">Obs</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">):</span>
<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="nb">len</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">)):</span>
<span class="n">raveled_data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">cov_Obs</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="mf">0.0</span><span class="p">,</span> <span class="s2">&quot;###dummy_covobs###&quot;</span><span class="p">)</span>
<span class="n">allcov</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">allcov</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">allcov</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">cov</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Inconsistent covariance matrices for </span><span class="si">%s</span><span class="s1">!&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">allcov</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">cov</span>
<span class="n">n_obs</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">)</span>
<span class="n">new_names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">]</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]))</span>
<span class="n">new_cov_names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">cov_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">]</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]))</span>
<span class="n">new_sample_names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">new_names</span><span class="p">)</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">new_cov_names</span><span class="p">))</span>
<span class="n">is_merged</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="k">lambda</span> <span class="n">o</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">,</span> <span class="n">raveled_data</span><span class="p">)))</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">}</span>
<span class="n">reweighted</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="k">lambda</span> <span class="n">o</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">,</span> <span class="n">raveled_data</span><span class="p">)))</span> <span class="o">&gt;</span> <span class="mi">0</span>
<span class="k">if</span> <span class="n">data</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">value</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">data</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vectorize</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">value</span><span class="p">)(</span><span class="n">data</span><span class="p">)</span>
<span class="n">new_values</span> <span class="o">=</span> <span class="n">func</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">multi</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">new_values</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">))</span>
<span class="n">new_r_values</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">new_idl_d</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">:</span>
<span class="n">idl</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp_values</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_obs</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">item</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">):</span>
<span class="n">tmp_values</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">item</span><span class="o">.</span><span class="n">r_values</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">item</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
<span class="n">tmp_idl</span> <span class="o">=</span> <span class="n">item</span><span class="o">.</span><span class="n">idl</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="k">if</span> <span class="n">tmp_idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">idl</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp_idl</span><span class="p">)</span>
<span class="k">if</span> <span class="n">multi</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">tmp_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">tmp_values</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="n">new_r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">func</span><span class="p">(</span><span class="n">tmp_values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">_merge_idx</span><span class="p">(</span><span class="n">idl</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">is_merged</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="n">is_merged</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="p">[</span><span class="o">*</span><span class="n">idl</span><span class="p">,</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]]])))</span>
<span class="k">if</span> <span class="s1">&#39;man_grad&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;man_grad&#39;</span><span class="p">))</span>
<span class="k">if</span> <span class="n">new_values</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span> <span class="o">!=</span> <span class="n">deriv</span><span class="o">.</span><span class="n">shape</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Manual derivative does not have correct shape.&#39;</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;num_grad&#39;</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="k">if</span> <span class="n">multi</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Multi mode currently not supported for numerical derivative&#39;</span><span class="p">)</span>
<span class="n">options</span> <span class="o">=</span> <span class="p">{</span>
<span class="s1">&#39;base_step&#39;</span><span class="p">:</span> <span class="mf">0.1</span><span class="p">,</span>
<span class="s1">&#39;step_ratio&#39;</span><span class="p">:</span> <span class="mf">2.5</span><span class="p">}</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">options</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">kwarg</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">)</span>
<span class="k">if</span> <span class="n">kwarg</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">options</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">kwarg</span>
<span class="n">tmp_df</span> <span class="o">=</span> <span class="n">nd</span><span class="o">.</span><span class="n">Gradient</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="o">**</span><span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">options</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">v</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">})(</span><span class="n">values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="n">tmp_df</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">tmp_df</span><span class="o">.</span><span class="n">real</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">tmp_df</span><span class="o">.</span><span class="n">real</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">jacobian</span><span class="p">(</span><span class="n">func</span><span class="p">)(</span><span class="n">values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">final_result</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">new_values</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">object</span><span class="p">)</span>
<span class="k">if</span> <span class="n">array_mode</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="k">class</span> <span class="nc">_Zero_grad</span><span class="p">():</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">N</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">grad</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="p">,</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">new_covobs_lengths</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">[[(</span><span class="n">n</span><span class="p">,</span> <span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">n</span><span class="p">]</span><span class="o">.</span><span class="n">N</span><span class="p">)</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">cov_names</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">]</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]))</span>
<span class="n">d_extracted</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">g_extracted</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">:</span>
<span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">ens_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
<span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">_expand_deltas_for_merge</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">ens_length</span><span class="p">)),</span> <span class="n">o</span><span class="o">.</span><span class="n">idl</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]),</span> <span class="n">o</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">ens_length</span><span class="p">),</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">dat</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span><span class="p">))])</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="p">(</span><span class="n">ens_length</span><span class="p">,</span> <span class="p">)))</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_cov_names</span><span class="p">:</span>
<span class="n">g_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">zero_grad</span> <span class="o">=</span> <span class="n">_Zero_grad</span><span class="p">(</span><span class="n">new_covobs_lengths</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
<span class="n">g_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">zero_grad</span><span class="p">)</span><span class="o">.</span><span class="n">grad</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">dat</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span><span class="p">))])</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="p">(</span><span class="n">new_covobs_lengths</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="mi">1</span><span class="p">)))</span>
<span class="k">for</span> <span class="n">i_val</span><span class="p">,</span> <span class="n">new_val</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">new_values</span><span class="p">):</span>
<span class="n">new_deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">new_grad</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="n">array_mode</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">:</span>
<span class="n">ens_length</span> <span class="o">=</span> <span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
<span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</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">ens_length</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]):</span>
<span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">tensordot</span><span class="p">(</span><span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="p">(</span><span class="n">i_dat</span><span class="p">,</span> <span class="p">)],</span> <span class="n">dat</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_cov_names</span><span class="p">:</span>
<span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">g_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]):</span>
<span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">tensordot</span><span class="p">(</span><span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="p">(</span><span class="n">i_dat</span><span class="p">,</span> <span class="p">)],</span> <span class="n">dat</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">j_obs</span><span class="p">,</span> <span class="n">obs</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">data</span><span class="p">):</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">new_grad</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">+</span> <span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="n">j_obs</span><span class="p">]</span> <span class="o">*</span> <span class="n">obs</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">new_deltas</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">+</span> <span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="n">j_obs</span><span class="p">]</span> <span class="o">*</span> <span class="n">_expand_deltas_for_merge</span><span class="p">(</span><span class="n">obs</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="n">obs</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">obs</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">new_covobs</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="n">Covobs</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">allcov</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">name</span><span class="p">,</span> <span class="n">grad</span><span class="o">=</span><span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_grad</span><span class="p">}</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">new_covobs</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">.</span><span class="n">isdisjoint</span><span class="p">(</span><span class="n">new_deltas</span><span class="o">.</span><span class="n">keys</span><span class="p">()):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;The same name has been used for deltas and covobs!&#39;</span><span class="p">)</span>
<span class="n">new_samples</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_means</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_idl</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_names_obs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">new_covobs</span><span class="p">:</span>
<span class="k">if</span> <span class="n">is_merged</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="n">filtered_deltas</span><span class="p">,</span> <span class="n">filtered_idl_d</span> <span class="o">=</span> <span class="n">_filter_zeroes</span><span class="p">(</span><span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">filtered_deltas</span> <span class="o">=</span> <span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="n">filtered_idl_d</span> <span class="o">=</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="n">new_samples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">filtered_deltas</span><span class="p">)</span>
<span class="n">new_idl</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">filtered_idl_d</span><span class="p">)</span>
<span class="n">new_means</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">new_r_values</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="n">i_val</span><span class="p">])</span>
<span class="n">new_names_obs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">new_samples</span><span class="p">,</span> <span class="n">new_names_obs</span><span class="p">,</span> <span class="n">means</span><span class="o">=</span><span class="n">new_means</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="n">new_idl</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_covobs</span><span class="p">:</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">_covobs</span> <span class="o">=</span> <span class="n">new_covobs</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="n">new_val</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="n">is_merged</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="n">reweighted</span>
<span class="k">if</span> <span class="n">multi</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">final_result</span> <span class="o">=</span> <span class="n">final_result</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="k">return</span> <span class="n">final_result</span>
<span class="k">def</span> <span class="nf">_reduce_deltas</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx_old</span><span class="p">,</span> <span class="n">idx_new</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Extract deltas defined on idx_old on all configs of idx_new.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas : list</span>
<span class="sd"> List of fluctuations</span>
<span class="sd"> idx_old : list</span>
<span class="sd"> List or range of configs on which the deltas are defined</span>
<span class="sd"> idx_new : list</span>
<span class="sd"> List of configs for which we want to extract the deltas.</span>
<span class="sd"> Has to be a subset of idx_old.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">len</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx_old</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of deltas and idx_old have to be the same: </span><span class="si">%d</span><span class="s1"> != </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">deltas</span><span class="p">),</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx_old</span><span class="p">)))</span>
<span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">idx_old</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span> <span class="ow">and</span> <span class="nb">type</span><span class="p">(</span><span class="n">idx_new</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span><span class="p">:</span>
<span class="k">if</span> <span class="n">idx_old</span> <span class="o">==</span> <span class="n">idx_new</span><span class="p">:</span>
<span class="k">return</span> <span class="n">deltas</span>
<span class="n">shape</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx_new</span><span class="p">)</span>
<span class="n">ret</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">shape</span><span class="p">)</span>
<span class="n">oldpos</span> <span class="o">=</span> <span class="mi">0</span>
<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">shape</span><span class="p">):</span>
<span class="k">if</span> <span class="n">oldpos</span> <span class="o">==</span> <span class="n">idx_old</span><span class="p">[</span><span class="n">i</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;idx_old and idx_new do not match!&#39;</span><span class="p">)</span>
<span class="n">pos</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
<span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">oldpos</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx_old</span><span class="p">)):</span>
<span class="k">if</span> <span class="n">idx_old</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o">==</span> <span class="n">idx_new</span><span class="p">[</span><span class="n">i</span><span class="p">]:</span>
<span class="n">pos</span> <span class="o">=</span> <span class="n">j</span>
<span class="k">break</span>
<span class="k">if</span> <span class="n">pos</span> <span class="o">&lt;</span> <span class="mi">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 in _reduce_deltas: Config </span><span class="si">%d</span><span class="s1"> not in idx_old&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">idx_new</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>
<span class="n">ret</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">deltas</span><span class="p">[</span><span class="n">j</span><span class="p">]</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">reweight</span><span class="p">(</span><span class="n">weight</span><span class="p">,</span> <span class="n">obs</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Reweight a list of observables.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> weight : Obs</span>
<span class="sd"> Reweighting factor. An Observable that has to be defined on a superset of the</span>
<span class="sd"> configurations in obs[i].idl for all i.</span>
<span class="sd"> obs : list</span>
<span class="sd"> list of Obs, e.g. [obs1, obs2, obs3].</span>
<span class="sd"> all_configs : bool</span>
<span class="sd"> if True, the reweighted observables are normalized by the average of</span>
<span class="sd"> the reweighting factor on all configurations in weight.idl and not</span>
<span class="sd"> on the configurations in obs[i].idl.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">result</span> <span class="o">=</span> <span class="p">[]</span>
<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="nb">len</span><span class="p">(</span><span class="n">obs</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">cov_names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error: Not possible to reweight an Obs that contains covobs!&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)</span><span class="o">.</span><span class="n">issubset</span><span class="p">(</span><span class="n">weight</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error: Ensembles do not fit&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span><span class="o">.</span><span class="n">issubset</span><span class="p">(</span><span class="n">weight</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;obs[</span><span class="si">%d</span><span class="s1">] has to be defined on a subset of the configs in weight.idl[</span><span class="si">%s</span><span class="s1">]!&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">name</span><span class="p">))</span>
<span class="n">new_samples</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">w_deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="n">w_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">_reduce_deltas</span><span class="p">(</span><span class="n">weight</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="n">weight</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">new_samples</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">w_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">weight</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="o">*</span> <span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</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="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]))</span>
<span class="n">tmp_obs</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">new_samples</span><span class="p">,</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">),</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)])</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;all_configs&#39;</span><span class="p">):</span>
<span class="n">new_weight</span> <span class="o">=</span> <span class="n">weight</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">new_weight</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([</span><span class="n">w_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">weight</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)],</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">),</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)])</span>
<span class="n">result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="n">tmp_obs</span><span class="p">,</span> <span class="n">new_weight</span><span class="p">],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
<span class="n">result</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">result</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">is_merged</span>
<span class="k">return</span> <span class="n">result</span>
<span class="k">def</span> <span class="nf">correlate</span><span class="p">(</span><span class="n">obs_a</span><span class="p">,</span> <span class="n">obs_b</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Correlate two observables.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> obs_a : Obs</span>
<span class="sd"> First observable</span>
<span class="sd"> obs_b : Obs</span>
<span class="sd"> Second observable</span>
<span class="sd"> Keep in mind to only correlate primary observables which have not been reweighted</span>
<span class="sd"> yet. The reweighting has to be applied after correlating the observables.</span>
<span class="sd"> Currently only works if ensembles are identical (this is not strictly necessary).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_b</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Ensembles do not fit&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">cov_names</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs_b</span><span class="o">.</span><span class="n">cov_names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error: Not possible to correlate Obs that contain covobs!&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">!=</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Shapes of ensemble&#39;</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="s1">&#39;do not fit&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">!=</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;idl of ensemble&#39;</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="s1">&#39;do not fit&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s2">&quot;The first observable is already reweighted.&quot;</span><span class="p">,</span> <span class="ne">RuntimeWarning</span><span class="p">)</span>
<span class="k">if</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s2">&quot;The second observable is already reweighted.&quot;</span><span class="p">,</span> <span class="ne">RuntimeWarning</span><span class="p">)</span>
<span class="n">new_samples</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_idl</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="n">new_samples</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">obs_a</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="n">obs_a</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="o">*</span> <span class="p">(</span><span class="n">obs_b</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="n">obs_b</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]))</span>
<span class="n">new_idl</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">o</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">new_samples</span><span class="p">,</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">),</span> <span class="n">idl</span><span class="o">=</span><span class="n">new_idl</span><span class="p">)</span>
<span class="n">o</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="ow">or</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">))</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">names</span><span class="p">}</span>
<span class="n">o</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">or</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">reweighted</span>
<span class="k">return</span> <span class="n">o</span>
<span class="k">def</span> <span class="nf">covariance</span><span class="p">(</span><span class="n">obs1</span><span class="p">,</span> <span class="n">obs2</span><span class="p">,</span> <span class="n">correlation</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Calculates the covariance of two observables.</span>
<span class="sd"> covariance(obs, obs) is equal to obs.dvalue ** 2</span>
<span class="sd"> The gamma method has to be applied first to both observables.</span>
<span class="sd"> If abs(covariance(obs1, obs2)) &gt; obs1.dvalue * obs2.dvalue, the covariance</span>
<span class="sd"> is constrained to the maximum value.</span>
<span class="sd"> Keyword arguments</span>
<span class="sd"> -----------------</span>
<span class="sd"> correlation -- if true the correlation instead of the covariance is</span>
<span class="sd"> returned (default False)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">expand_deltas</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">new_idx</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Expand deltas defined on idx to a contiguous range [new_idx[0], new_idx[-1]].</span>
<span class="sd"> New, empy entries are filled by 0. If idx and new_idx are of type range, the smallest</span>
<span class="sd"> common divisor of the step sizes is used as new step size.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas -- List of fluctuations</span>
<span class="sd"> idx -- List or range of configs on which the deltas are defined.</span>
<span class="sd"> Has to be a subset of new_idx.</span>
<span class="sd"> shape -- Number of configs in idx.</span>
<span class="sd"> new_idx -- List of configs that defines the new range.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span> <span class="ow">and</span> <span class="nb">type</span><span class="p">(</span><span class="n">new_idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span><span class="p">:</span>
<span class="k">if</span> <span class="n">idx</span> <span class="o">==</span> <span class="n">new_idx</span><span class="p">:</span>
<span class="k">return</span> <span class="n">deltas</span>
<span class="n">ret</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">new_idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<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">shape</span><span class="p">):</span>
<span class="n">ret</span><span class="p">[</span><span class="n">idx</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">=</span> <span class="n">deltas</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="k">return</span> <span class="n">ret</span>
<span class="k">def</span> <span class="nf">calc_gamma</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">deltas2</span><span class="p">,</span> <span class="n">idx1</span><span class="p">,</span> <span class="n">idx2</span><span class="p">,</span> <span class="n">new_idx</span><span class="p">,</span> <span class="n">w_max</span><span class="p">):</span>
<span class="n">gamma</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">w_max</span><span class="p">)</span>
<span class="n">deltas1</span> <span class="o">=</span> <span class="n">expand_deltas</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">idx1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx1</span><span class="p">),</span> <span class="n">new_idx</span><span class="p">)</span>
<span class="n">deltas2</span> <span class="o">=</span> <span class="n">expand_deltas</span><span class="p">(</span><span class="n">deltas2</span><span class="p">,</span> <span class="n">idx2</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx2</span><span class="p">),</span> <span class="n">new_idx</span><span class="p">)</span>
<span class="n">new_shape</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">deltas1</span><span class="p">)</span>
<span class="n">max_gamma</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">new_shape</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span>
<span class="c1"># The padding for the fft has to be even</span>
<span class="n">padding</span> <span class="o">=</span> <span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span> <span class="o">+</span> <span class="p">(</span><span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span><span class="p">)</span> <span class="o">%</span> <span class="mi">2</span>
<span class="n">gamma</span><span class="p">[:</span><span class="n">max_gamma</span><span class="p">]</span> <span class="o">+=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">padding</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">conjugate</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas2</span><span class="p">,</span> <span class="n">padding</span><span class="p">)))[:</span><span class="n">max_gamma</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas2</span><span class="p">,</span> <span class="n">padding</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">conjugate</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">padding</span><span class="p">)))[:</span><span class="n">max_gamma</span><span class="p">])</span> <span class="o">/</span> <span class="mf">2.0</span>
<span class="k">return</span> <span class="n">gamma</span>
<span class="k">if</span> <span class="nb">set</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">names</span><span class="p">)</span><span class="o">.</span><span class="n">isdisjoint</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">obs2</span><span class="o">.</span><span class="n">names</span><span class="p">)):</span>
<span class="k">return</span> <span class="mf">0.</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">obs1</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">obs2</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;The gamma method has to be applied to both Obs first.&#39;</span><span class="p">)</span>
<span class="n">dvalue</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">e_gamma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_dvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_n_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_rho</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="n">obs1</span><span class="o">.</span><span class="n">mc_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">e_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</span><span class="o">.</span><span class="n">mc_names</span><span class="p">:</span>
<span class="k">continue</span>
<span class="n">idl_d</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="k">if</span> <span class="n">r_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</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="k">continue</span>
<span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">_merge_idx</span><span class="p">([</span><span class="n">obs1</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]])</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">r_length</span><span class="p">:</span>
<span class="k">return</span> <span class="mf">0.</span>
<span class="n">w_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="k">if</span> <span class="n">r_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</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="k">continue</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+=</span> <span class="n">calc_gamma</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs1</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">)</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">):</span>
<span class="k">continue</span>
<span class="n">e_shapes</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="n">e_shapes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">])</span>
<span class="n">gamma_div</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">w_max</span><span class="p">)</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="k">if</span> <span class="n">r_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</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="k">continue</span>
<span class="n">gamma_div</span> <span class="o">+=</span> <span class="n">calc_gamma</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">obs2</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="n">obs1</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">)</span>
<span class="n">e_N</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/=</span> <span class="n">gamma_div</span><span class="p">[:</span><span class="n">w_max</span><span class="p">]</span>
<span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">w_max</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(([</span><span class="mf">0.5</span><span class="p">],</span> <span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:])))</span>
<span class="c1"># Make sure no entry of tauint is smaller than 0.5</span>
<span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.500000000001</span>
<span class="n">window</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="c1"># Bias correction hep-lat/0306017 eq. (49)</span>
<span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">window</span><span class="p">]</span> <span class="o">+</span> <span class="n">obs1</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">window</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]))</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">window</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_N</span>
<span class="n">dvalue</span> <span class="o">+=</span> <span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="n">obs1</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">e_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="k">continue</span>
<span class="n">dvalue</span> <span class="o">+=</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">cov</span><span class="p">,</span> <span class="n">obs2</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span><span class="p">)))</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs1</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs2</span><span class="o">.</span><span class="n">dvalue</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mf">1.0</span><span class="p">:</span>
<span class="n">dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="n">dvalue</span><span class="p">)</span> <span class="o">*</span> <span class="n">obs1</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">*</span> <span class="n">obs2</span><span class="o">.</span><span class="n">dvalue</span>
<span class="k">if</span> <span class="n">correlation</span><span class="p">:</span>
<span class="n">dvalue</span> <span class="o">=</span> <span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs1</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs2</span><span class="o">.</span><span class="n">dvalue</span>
<span class="k">return</span> <span class="n">dvalue</span>
<span class="k">def</span> <span class="nf">import_jackknife</span><span class="p">(</span><span class="n">jacks</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Imports jackknife samples and returns an Obs</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> jacks : numpy.ndarray</span>
<span class="sd"> numpy array containing the mean value as zeroth entry and</span>
<span class="sd"> the N jackknife samples as first to Nth entry.</span>
<span class="sd"> name : str</span>
<span class="sd"> name of the ensemble the samples are defined on.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">jacks</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span>
<span class="n">prj</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="n">length</span><span class="p">,</span> <span class="n">length</span><span class="p">))</span> <span class="o">-</span> <span class="p">(</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">identity</span><span class="p">(</span><span class="n">length</span><span class="p">))</span>
<span class="n">samples</span> <span class="o">=</span> <span class="n">jacks</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span> <span class="o">@</span> <span class="n">prj</span>
<span class="n">new_obs</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([</span><span class="n">samples</span><span class="p">],</span> <span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">idl</span><span class="o">=</span><span class="n">idl</span><span class="p">)</span>
<span class="n">new_obs</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="n">jacks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">return</span> <span class="n">new_obs</span>
<span class="k">def</span> <span class="nf">merge_obs</span><span class="p">(</span><span class="n">list_of_obs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Combine all observables in list_of_obs into one new observable</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> list_of_obs : list</span>
<span class="sd"> list of the Obs object to be combined</span>
<span class="sd"> It is not possible to combine obs which are based on the same replicum</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">replist</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span> <span class="k">for</span> <span class="n">obs</span> <span class="ow">in</span> <span class="n">list_of_obs</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">obs</span><span class="o">.</span><span class="n">names</span><span class="p">]</span>
<span class="k">if</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">replist</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">replist</span><span class="p">)))</span> <span class="ow">is</span> <span class="kc">False</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;list_of_obs contains duplicate replica: </span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">replist</span><span class="p">)))</span>
<span class="k">if</span> <span class="nb">any</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">cov_names</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">]):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Not possible to merge data that contains covobs!&#39;</span><span class="p">)</span>
<span class="n">new_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">idl_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">:</span>
<span class="n">new_dict</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="n">key</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">+</span> <span class="n">o</span><span class="o">.</span><span class="n">r_values</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="p">)</span> <span class="o">|</span> <span class="nb">set</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">r_values</span><span class="p">)})</span>
<span class="n">idl_dict</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="n">key</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">idl</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="p">)})</span>
<span class="n">names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">new_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
<span class="n">o</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([</span><span class="n">new_dict</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">names</span><span class="p">],</span> <span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="n">idl_dict</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">names</span><span class="p">])</span>
<span class="n">o</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">any</span><span class="p">([</span><span class="n">oi</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="k">for</span> <span class="n">oi</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">])</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">names</span><span class="p">}</span>
<span class="n">o</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">([</span><span class="n">oi</span><span class="o">.</span><span class="n">reweighted</span> <span class="k">for</span> <span class="n">oi</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">])</span>
<span class="k">return</span> <span class="n">o</span>
<span class="k">def</span> <span class="nf">cov_Obs</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="n">cov</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">grad</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Create an Obs based on mean(s) and a covariance matrix</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> mean : list of floats or float</span>
<span class="sd"> N mean value(s) of the new Obs</span>
<span class="sd"> cov : list or array</span>
<span class="sd"> 2d (NxN) Covariance matrix, 1d diagonal entries or 0d covariance</span>
<span class="sd"> name : str</span>
<span class="sd"> identifier for the covariance matrix</span>
<span class="sd"> grad : list or array</span>
<span class="sd"> Gradient of the Covobs wrt. the means belonging to cov.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">covobs_to_obs</span><span class="p">(</span><span class="n">co</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Make an Obs out of a Covobs</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> co : Covobs</span>
<span class="sd"> Covobs to be embedded into the Obs</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">o</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([],</span> <span class="p">[])</span>
<span class="n">o</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="n">co</span><span class="o">.</span><span class="n">value</span>
<span class="n">o</span><span class="o">.</span><span class="n">names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">co</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
<span class="n">o</span><span class="o">.</span><span class="n">_covobs</span><span class="p">[</span><span class="n">co</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">co</span>
<span class="n">o</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">co</span><span class="o">.</span><span class="n">errsq</span><span class="p">())</span>
<span class="k">return</span> <span class="n">o</span>
<span class="n">ol</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="p">(</span><span class="nb">float</span><span class="p">,</span> <span class="nb">int</span><span class="p">)):</span>
<span class="n">means</span> <span class="o">=</span> <span class="p">[</span><span class="n">means</span><span class="p">]</span>
<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="nb">len</span><span class="p">(</span><span class="n">means</span><span class="p">)):</span>
<span class="n">ol</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">covobs_to_obs</span><span class="p">(</span><span class="n">Covobs</span><span class="p">(</span><span class="n">means</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">cov</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="n">i</span><span class="p">,</span> <span class="n">grad</span><span class="o">=</span><span class="n">grad</span><span class="p">)))</span>
<span class="k">if</span> <span class="n">ol</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">N</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">means</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;You have to provide </span><span class="si">%d</span><span class="s1"> mean values!&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">ol</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">N</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ol</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">return</span> <span class="n">ol</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">return</span> <span class="n">ol</span>
</pre></div>
</details>
</section>
<section id="Obs">
<div class="attr class">
<a class="headerlink" href="#Obs">#&nbsp;&nbsp</a>
<span class="def">class</span>
<span class="name">Obs</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">class</span> <span class="nc">Obs</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;Class for a general observable.</span>
<span class="sd"> Instances of Obs are the basic objects of a pyerrors error analysis.</span>
<span class="sd"> They are initialized with a list which contains arrays of samples for</span>
<span class="sd"> different ensembles/replica and another list of same length which contains</span>
<span class="sd"> the names of the ensembles/replica. Mathematical operations can be</span>
<span class="sd"> performed on instances. The result is another instance of Obs. The error of</span>
<span class="sd"> an instance can be computed with the gamma_method. Also contains additional</span>
<span class="sd"> methods for output and visualization of the error calculation.</span>
<span class="sd"> Attributes</span>
<span class="sd"> ----------</span>
<span class="sd"> S_global : float</span>
<span class="sd"> Standard value for S (default 2.0)</span>
<span class="sd"> S_dict : dict</span>
<span class="sd"> Dictionary for S values. If an entry for a given ensemble</span>
<span class="sd"> exists this overwrites the standard value for that ensemble.</span>
<span class="sd"> tau_exp_global : float</span>
<span class="sd"> Standard value for tau_exp (default 0.0)</span>
<span class="sd"> tau_exp_dict : dict</span>
<span class="sd"> Dictionary for tau_exp values. If an entry for a given ensemble exists</span>
<span class="sd"> this overwrites the standard value for that ensemble.</span>
<span class="sd"> N_sigma_global : float</span>
<span class="sd"> Standard value for N_sigma (default 1.0)</span>
<span class="sd"> N_sigma_dict : dict</span>
<span class="sd"> Dictionary for N_sigma values. If an entry for a given ensemble exists</span>
<span class="sd"> this overwrites the standard value for that ensemble.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;names&#39;</span><span class="p">,</span> <span class="s1">&#39;shape&#39;</span><span class="p">,</span> <span class="s1">&#39;r_values&#39;</span><span class="p">,</span> <span class="s1">&#39;deltas&#39;</span><span class="p">,</span> <span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;_value&#39;</span><span class="p">,</span> <span class="s1">&#39;_dvalue&#39;</span><span class="p">,</span>
<span class="s1">&#39;ddvalue&#39;</span><span class="p">,</span> <span class="s1">&#39;reweighted&#39;</span><span class="p">,</span> <span class="s1">&#39;S&#39;</span><span class="p">,</span> <span class="s1">&#39;tau_exp&#39;</span><span class="p">,</span> <span class="s1">&#39;N_sigma&#39;</span><span class="p">,</span>
<span class="s1">&#39;e_dvalue&#39;</span><span class="p">,</span> <span class="s1">&#39;e_ddvalue&#39;</span><span class="p">,</span> <span class="s1">&#39;e_tauint&#39;</span><span class="p">,</span> <span class="s1">&#39;e_dtauint&#39;</span><span class="p">,</span>
<span class="s1">&#39;e_windowsize&#39;</span><span class="p">,</span> <span class="s1">&#39;e_rho&#39;</span><span class="p">,</span> <span class="s1">&#39;e_drho&#39;</span><span class="p">,</span> <span class="s1">&#39;e_n_tauint&#39;</span><span class="p">,</span> <span class="s1">&#39;e_n_dtauint&#39;</span><span class="p">,</span>
<span class="s1">&#39;idl&#39;</span><span class="p">,</span> <span class="s1">&#39;is_merged&#39;</span><span class="p">,</span> <span class="s1">&#39;tag&#39;</span><span class="p">,</span> <span class="s1">&#39;_covobs&#39;</span><span class="p">,</span> <span class="s1">&#39;__dict__&#39;</span><span class="p">]</span>
<span class="n">S_global</span> <span class="o">=</span> <span class="mf">2.0</span>
<span class="n">S_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">tau_exp_global</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="n">tau_exp_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">N_sigma_global</span> <span class="o">=</span> <span class="mf">1.0</span>
<span class="n">N_sigma_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">filter_eps</span> <span class="o">=</span> <span class="mf">1e-10</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">samples</span><span class="p">,</span> <span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">means</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Initialize Obs object.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> samples : list</span>
<span class="sd"> list of numpy arrays containing the Monte Carlo samples</span>
<span class="sd"> names : list</span>
<span class="sd"> list of strings labeling the individual samples</span>
<span class="sd"> idl : list, optional</span>
<span class="sd"> list of ranges or lists on which the samples are defined</span>
<span class="sd"> means : list, optional</span>
<span class="sd"> list of mean values for the case that the mean values were</span>
<span class="sd"> already subtracted from the samples</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">means</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of samples and names incompatible.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">idl</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of idl incompatible with samples and names.&#39;</span><span class="p">)</span>
<span class="n">name_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="k">if</span> <span class="n">name_length</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name_length</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">names</span><span class="p">)):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;names are not unique.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">&#39;All names have to be strings.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">str</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">&#39;All names have to be strings.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">min</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">samples</span><span class="p">)</span> <span class="o">&lt;=</span> <span class="mi">4</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Samples have to have at least 5 entries.&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">r_values</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_covobs</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">):</span>
<span class="k">if</span> <span class="n">idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="nb">range</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">idx</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
<span class="n">dc</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">idx</span><span class="p">))</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">any</span><span class="p">(</span><span class="n">dc</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Unsorted idx for idl[</span><span class="si">%s</span><span class="s2">]&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">dc</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">dc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">dc</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;incompatible type for idl[</span><span class="si">%s</span><span class="s1">].&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">if</span> <span class="n">means</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">mean</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">,</span> <span class="n">means</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</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> <span class="o">=</span> <span class="n">mean</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="n">sample</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Incompatible samples and idx for </span><span class="si">%s</span><span class="s1">: </span><span class="si">%d</span><span class="s1"> vs. </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]))</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> <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">sample</span><span class="p">)</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="n">sample</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>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</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>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">/=</span> <span class="bp">self</span><span class="o">.</span><span class="n">N</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">=</span> <span class="mi">0</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="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">value</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">dvalue</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">e_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;|&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">names</span><span class="p">]))</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">cov_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="o">.</span><span class="n">keys</span><span class="p">()]))</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">mc_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;|&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">names</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">cov_names</span><span class="p">]))</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">e_content</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">res</span> <span class="o">=</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">res</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;|&#39;</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="k">if</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="n">res</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">e_name</span><span class="p">)</span>
<span class="k">return</span> <span class="n">res</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">covobs</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_covobs</span>
<span class="k">def</span> <span class="nf">gamma_method</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Estimate the error and related properties of the Obs.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> S : float</span>
<span class="sd"> specifies a custom value for the parameter S (default 2.0).</span>
<span class="sd"> If set to 0 it is assumed that the data exhibits no</span>
<span class="sd"> autocorrelation. In this case the error estimates coincides</span>
<span class="sd"> with the sample standard error.</span>
<span class="sd"> tau_exp : float</span>
<span class="sd"> positive value triggers the critical slowing down analysis</span>
<span class="sd"> (default 0.0).</span>
<span class="sd"> N_sigma : float</span>
<span class="sd"> number of standard deviations from zero until the tail is</span>
<span class="sd"> attached to the autocorrelation function (default 1).</span>
<span class="sd"> fft : bool</span>
<span class="sd"> determines whether the fft algorithm is used for the computation</span>
<span class="sd"> of the autocorrelation function (default True)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">e_content</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_content</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_gamma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span> <span class="o">=</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="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">S</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fft&#39;</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">False</span><span class="p">:</span>
<span class="n">fft</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">fft</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">_parse_kwarg</span><span class="p">(</span><span class="n">kwarg_name</span><span class="p">):</span>
<span class="k">if</span> <span class="n">kwarg_name</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">kwarg_name</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">)):</span>
<span class="k">if</span> <span class="n">tmp</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39; has to be larger or equal to 0.&#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="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39; is not in proper format.&#39;</span><span class="p">)</span>
<span class="k">else</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="n">e_name</span> <span class="ow">in</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_dict&#39;</span><span class="p">):</span>
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_dict&#39;</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_global&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;S&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;tau_exp&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;N_sigma&#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">mc_names</span><span class="p">):</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]])</span>
<span class="n">w_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calc_gamma</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">)</span>
<span class="n">gamma_div</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="n">gamma_div</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calc_gamma</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">])),</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">)</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/=</span> <span class="n">gamma_div</span><span class="p">[:</span><span class="n">w_max</span><span class="p">]</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mi">10</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">finfo</span><span class="p">(</span><span class="nb">float</span><span class="p">)</span><span class="o">.</span><span class="n">tiny</span><span class="p">:</span> <span class="c1"># Prevent division by zero</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">continue</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">w_max</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(([</span><span class="mf">0.5</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:])))</span>
<span class="c1"># Make sure no entry of tauint is smaller than 0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">finfo</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span><span class="o">.</span><span class="n">eps</span>
<span class="c1"># hep-lat/0306017 eq. (42)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">w_max</span><span class="p">)</span> <span class="o">+</span> <span class="mf">0.5</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="k">def</span> <span class="nf">_compute_drho</span><span class="p">(</span><span class="n">i</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</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="n">w_max</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</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="mi">1</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="n">w_max</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">i</span><span class="p">]])</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="n">w_max</span> <span class="o">-</span> <span class="n">i</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">tmp</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">texp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span>
<span class="c1"># Critical slowing down analysis</span>
<span class="k">if</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">&lt;=</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Need at least 8 samples for tau_exp error analysis&quot;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span><span class="p">):</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
<span class="c1"># Bias correction hep-lat/0306017 eq. (49) included</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">+</span> <span class="n">texp</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">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> <span class="c1"># The absolute makes sure, that the tail contribution is always positive</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">texp</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span>
<span class="c1"># Error of tau_exp neglected so far, missing term: self.e_rho[e_name][n + 1] ** 2 * d_tau_exp ** 2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">n</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">n</span>
<span class="k">break</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">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="p">(</span><span class="n">e_N</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mf">0.5</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Standard automatic windowing procedure</span>
<span class="n">tau</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">((</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">g_w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span> <span class="o">/</span> <span class="n">tau</span><span class="p">)</span> <span class="o">-</span> <span class="n">tau</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span> <span class="o">*</span> <span class="n">e_N</span><span class="p">)</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">):</span>
<span class="k">if</span> <span class="n">n</span> <span class="o">&lt;</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">g_w</span><span class="p">[</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="n">w_max</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="c1"># Bias correction hep-lat/0306017 eq. (49)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">n</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">n</span>
<span class="k">break</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">+=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</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">cov_names</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">errsq</span><span class="p">())</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">**</span><span class="mi">2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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="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="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span>
<span class="k">return</span>
<span class="k">def</span> <span class="nf">_calc_gamma</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Calculate Gamma_{AA} from the deltas, which are defined on idx.</span>
<span class="sd"> idx is assumed to be a contiguous range (possibly with a stepsize != 1)</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas : list</span>
<span class="sd"> List of fluctuations</span>
<span class="sd"> idx : list</span>
<span class="sd"> List or range of configurations on which the deltas are defined.</span>
<span class="sd"> shape : int</span>
<span class="sd"> Number of configurations in idx.</span>
<span class="sd"> w_max : int</span>
<span class="sd"> Upper bound for the summation window.</span>
<span class="sd"> fft : bool</span>
<span class="sd"> determines whether the fft algorithm is used for the computation</span>
<span class="sd"> of the autocorrelation function.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">gamma</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">w_max</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">=</span> <span class="n">_expand_deltas</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">)</span>
<span class="n">new_shape</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span>
<span class="k">if</span> <span class="n">fft</span><span class="p">:</span>
<span class="n">max_gamma</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">new_shape</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span>
<span class="c1"># The padding for the fft has to be even</span>
<span class="n">padding</span> <span class="o">=</span> <span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span> <span class="o">+</span> <span class="p">(</span><span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span><span class="p">)</span> <span class="o">%</span> <span class="mi">2</span>
<span class="n">gamma</span><span class="p">[:</span><span class="n">max_gamma</span><span class="p">]</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">padding</span><span class="p">))</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)[:</span><span class="n">max_gamma</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">w_max</span><span class="p">):</span>
<span class="k">if</span> <span class="n">new_shape</span> <span class="o">-</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">gamma</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="o">+=</span> <span class="n">deltas</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="n">new_shape</span> <span class="o">-</span> <span class="n">n</span><span class="p">]</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">deltas</span><span class="p">[</span><span class="n">n</span><span class="p">:</span><span class="n">new_shape</span><span class="p">])</span>
<span class="k">return</span> <span class="n">gamma</span>
<span class="k">def</span> <span class="nf">details</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ens_content</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Output detailed properties of the Obs.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> ens_content : bool</span>
<span class="sd"> print details about the ensembles and replica if true.</span>
<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">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">mc_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_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;&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;</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">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; t_int</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"> tau_exp = </span><span class="si">%3.2f</span><span class="s1">, N_sigma = </span><span class="si">%1.0i</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">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; t_int</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"> S = </span><span class="si">%3.2f</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">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</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">cov_names</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="n">ens_content</span> <span class="ow">is</span> <span class="kc">True</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">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">N</span><span class="p">,</span> <span class="s1">&#39;samples in&#39;</span><span class="p">,</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="s1">&#39;ensemble:&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">N</span><span class="p">,</span> <span class="s1">&#39;samples in&#39;</span><span class="p">,</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="s1">&#39;ensembles:&#39;</span><span class="p">)</span>
<span class="n">my_string_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_content</span><span class="o">.</span><span class="n">items</span><span class="p">()):</span>
<span class="k">if</span> <span class="n">key</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Ensemble &#39;&quot;</span> <span class="o">+</span> <span class="n">key</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39;: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="si">}</span><span class="s1"> configurations&#39;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39; (from </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">start</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">step</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="sa">f</span><span class="s1">&#39; in steps of </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">step</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="s1">&#39; (irregular range)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">sublist</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">value</span><span class="p">:</span>
<span class="n">my_substring</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Replicum &#39;&quot;</span> <span class="o">+</span> <span class="n">v</span><span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">key</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39;: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="si">}</span><span class="s1"> configurations&#39;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39; (from </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">start</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">step</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="sa">f</span><span class="s1">&#39; in steps of </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">step</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="s1">&#39; (irregular range)&#39;</span>
<span class="n">sublist</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_substring</span><span class="p">)</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">sublist</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Covobs &#39;&quot;</span> <span class="o">+</span> <span class="n">key</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="n">my_string_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_string</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">my_string_list</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">is_zero_within_error</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Checks whether the observable is zero within &#39;sigma&#39; standard errors.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> sigma : int</span>
<span class="sd"> Number of standard errors used for the check.</span>
<span class="sd"> Works only properly when the gamma method was run.</span>
<span class="sd"> &quot;&quot;&quot;</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">&lt;=</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="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">&quot;&quot;&quot;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"> &quot;&quot;&quot;</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="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="o">.</span><span class="n">errsq</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">covobs</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">&quot;&quot;&quot;Plot integrated autocorrelation time for each ensemble.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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_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">mc_names</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>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;$W$&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;$\tau_\mathrm</span><span class="si">{int}</span><span class="s1">$&#39;</span><span class="p">)</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]]</span>
<span class="n">x_help</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="n">y_help</span> <span class="o">=</span> <span class="p">(</span><span class="n">x_help</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</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">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">x_help</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</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> <span class="o">+</span> <span class="n">base</span>
<span class="n">x_arr</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x_arr</span><span class="p">,</span> <span class="n">y_help</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span>
<span class="n">yerr</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span> <span class="n">fmt</span><span class="o">=</span><span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">mfc</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">&#39;axes.facecolor&#39;</span><span class="p">])</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.5</span>
<span class="n">label</span> <span class="o">=</span> <span class="n">e_name</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;, $\tau_\mathrm</span><span class="si">{exp}</span><span class="s1">$=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">label</span> <span class="o">=</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;, S=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mf">10.5</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">length</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">yerr</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">(</span><span class="n">bottom</span><span class="o">=</span><span class="mf">0.0</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">))</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="n">save</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot normalized autocorrelation function time for each ensemble.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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_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">mc_names</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>
<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>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;rho&#39;</span><span class="p">)</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">length</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">length</span><span class="p">],</span> <span class="n">yerr</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;r&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="mi">0</span><span class="p">],</span> <span class="s1">&#39;k-&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.5</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Rho &#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;, tau\_exp=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">)))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mf">10.5</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Rho &#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;, S=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">)))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">],</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="s1">&#39;k--&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">))</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_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">mc_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>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;No replica distribution for a single replicum (&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;)&#39;</span><span class="p">)</span>
<span class="k">continue</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">sub_r_mean</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="n">sub_r_mean</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">]</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span>
<span class="n">sub_r_mean</span> <span class="o">/=</span> <span class="n">e_N</span>
<span class="n">arr</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="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="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">arr</span><span class="p">[</span><span class="n">r</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">-</span> <span class="n">sub_r_mean</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">e_N</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">rwidth</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</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="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Replica distribution&#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39; (mean=0, var=1)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">plot_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot derived Monte Carlo history for each ensemble</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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">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">mc_names</span><span class="p">):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp_expanded</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">])</span>
<span class="k">if</span> <span class="n">expand</span><span class="p">:</span>
<span class="n">tmp_expanded</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_expand_deltas</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">])</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tmp_expanded</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">e_N</span><span class="p">)</span>
<span class="n">y_test</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="n">expand</span><span class="p">:</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">tmp_expanded</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">y_test</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">fmt</span><span class="o">=</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">e_N</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">e_name</span> <span class="o">+</span> <span class="sa">f</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">skew: </span><span class="si">{</span><span class="n">skew</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> (p=</span><span class="si">{</span><span class="n">skewtest</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="o">.</span><span class="n">pvalue</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">), kurtosis: </span><span class="si">{</span><span class="n">kurtosis</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> (p=</span><span class="si">{</span><span class="n">kurtosistest</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="o">.</span><span class="n">pvalue</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</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_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>
<span class="n">labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_names</span>
<span class="n">sizes</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">**</span> <span class="mi">2</span>
<span class="n">fig1</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">pie</span><span class="p">(</span><span class="n">sizes</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">,</span> <span class="n">startangle</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span> <span class="n">normalize</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">&#39;equal&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">return</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">zip</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">sizes</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">,</span> <span class="n">datatype</span><span class="o">=</span><span class="s2">&quot;json.gz&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Dump the Obs to a file &#39;name&#39; of chosen format.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> filename : str</span>
<span class="sd"> name of the file to be saved.</span>
<span class="sd"> datatype : str</span>
<span class="sd"> Format of the exported file. Supported formats include</span>
<span class="sd"> &quot;json.gz&quot; and &quot;pickle&quot;</span>
<span class="sd"> path : str</span>
<span class="sd"> specifies a custom path for the file (default &#39;.&#39;)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="s1">&#39;path&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">file_name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;path&#39;</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">filename</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">file_name</span> <span class="o">=</span> <span class="n">filename</span>
<span class="k">if</span> <span class="n">datatype</span> <span class="o">==</span> <span class="s2">&quot;json.gz&quot;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">.input.json</span> <span class="kn">import</span> <span class="n">dump_to_json</span>
<span class="n">dump_to_json</span><span class="p">([</span><span class="bp">self</span><span class="p">],</span> <span class="n">file_name</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">datatype</span> <span class="o">==</span> <span class="s2">&quot;pickle&quot;</span><span class="p">:</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file_name</span> <span class="o">+</span> <span class="s1">&#39;.p&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">fb</span><span class="p">:</span>
<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>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Unknown datatype &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">datatype</span><span class="p">))</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>
<span class="sd">&quot;&quot;&quot;Export jackknife samples from the Obs</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> numpy.ndarray</span>
<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
<span class="sd"> derived from the Obs. The current implementation only works for observables</span>
<span class="sd"> defined on exactly one ensemble and replicum. The derived jackknife samples</span>
<span class="sd"> should agree with samples from a full jackknife analysis up to O(1/N).</span>
<span class="sd"> &quot;&quot;&quot;</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">names</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;&#39;export_jackknife&#39; is only implemented for Obs defined on one ensemble and replicum.&quot;</span><span class="p">)</span>
<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>
<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>
<span class="n">n</span> <span class="o">=</span> <span class="n">full_data</span><span class="o">.</span><span class="n">size</span>
<span class="n">mean</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span>
<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>
<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="n">mean</span>
<span class="n">tmp_jacks</span><span class="p">[</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="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">return</span> <span class="n">tmp_jacks</span>
<span class="k">def</span> <span class="fm">__float__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<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>
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;Obs[&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;]&#39;</span>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</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">return</span> <span class="nb">str</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">fexp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">floor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">log10</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="k">if</span> <span class="n">fexp</span> <span class="o">&lt;</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="s1">&#39;{:</span><span class="si">{form}</span><span class="s1">}(</span><span class="si">{:2.0f}</span><span class="s1">)&#39;</span><span class="o">.</span><span class="n">format</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="o">*</span> <span class="mi">10</span> <span class="o">**</span> <span class="p">(</span><span class="o">-</span><span class="n">fexp</span> <span class="o">+</span> <span class="mi">1</span><span class="p">),</span> <span class="n">form</span><span class="o">=</span><span class="s1">&#39;.&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="o">-</span><span class="nb">int</span><span class="p">(</span><span class="n">fexp</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;f&#39;</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">fexp</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="s1">&#39;</span><span class="si">{:.1f}</span><span class="s1">(</span><span class="si">{:1.1f}</span><span class="s1">)&#39;</span><span class="o">.</span><span class="n">format</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="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="s1">&#39;</span><span class="si">{:.0f}</span><span class="s1">(</span><span class="si">{:2.0f}</span><span class="s1">)&#39;</span><span class="o">.</span><span class="n">format</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="c1"># Overload comparisons</span>
<span class="k">def</span> <span class="fm">__lt__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&lt;</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__le__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&lt;=</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__gt__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&gt;</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__ge__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">&gt;=</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">is_zero</span><span class="p">()</span>
<span class="k">def</span> <span class="fm">__ne__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="ow">not</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">is_zero</span><span class="p">()</span>
<span class="c1"># Overload math operations</span>
<span class="k">def</span> <span class="fm">__add__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">+</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__radd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">+</span> <span class="n">y</span>
<span class="k">def</span> <span class="fm">__mul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">y</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">value</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">*</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="nb">complex</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span> <span class="o">*</span> <span class="n">y</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span> <span class="o">*</span> <span class="n">y</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">y</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rmul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">*</span> <span class="n">y</span>
<span class="k">def</span> <span class="fm">__sub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">-</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rsub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">y</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__neg__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="bp">self</span>
<span class="k">def</span> <span class="fm">__truediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">y</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">/</span> <span class="n">y</span><span class="o">.</span><span class="n">value</span> <span class="o">**</span> <span class="mi">2</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span> <span class="o">/</span> <span class="n">o</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">y</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rtruediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</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="n">y</span><span class="o">.</span><span class="n">value</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">**</span> <span class="mi">2</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">o</span> <span class="o">/</span> <span class="bp">self</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">y</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">y</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Corr&#39;</span><span class="p">,</span> <span class="s1">&#39;CObs&#39;</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">NotImplemented</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">y</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="n">y</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">**</span> <span class="mi">2</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__pow__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">**</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">**</span> <span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__rpow__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">**</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span> <span class="bp">self</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">y</span> <span class="o">**</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="fm">__abs__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="c1"># Overload numpy functions</span>
<span class="k">def</span> <span class="nf">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="mi">2</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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">def</span> <span class="nf">log</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</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="k">def</span> <span class="nf">exp</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">exp</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">def</span> <span class="nf">sin</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">cos</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">def</span> <span class="nf">cos</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">sin</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">def</span> <span class="nf">tan</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">tan</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</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="mi">2</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arcsin</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arcsin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arccos</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arccos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arctan</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arctan</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">sinh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sinh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">cosh</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">def</span> <span class="nf">cosh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">cosh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">sinh</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">def</span> <span class="nf">tanh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">cosh</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="mi">2</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arcsinh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arcsinh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arccosh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arccosh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
<span class="k">def</span> <span class="nf">arctanh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arctanh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
<div class="docstring"><p>Class for a general observable.</p>
<p>Instances of Obs are the basic objects of a pyerrors error analysis.
They are initialized with a list which contains arrays of samples for
different ensembles/replica and another list of same length which contains
the names of the ensembles/replica. Mathematical operations can be
performed on instances. The result is another instance of Obs. The error of
an instance can be computed with the gamma_method. Also contains additional
methods for output and visualization of the error calculation.</p>
<h6 id="attributes">Attributes</h6>
<ul>
<li><strong>S_global</strong> (float):
Standard value for S (default 2.0)</li>
<li><strong>S_dict</strong> (dict):
Dictionary for S values. If an entry for a given ensemble
exists this overwrites the standard value for that ensemble.</li>
<li><strong>tau_exp_global</strong> (float):
Standard value for tau_exp (default 0.0)</li>
<li><strong>tau_exp_dict</strong> (dict):
Dictionary for tau_exp values. If an entry for a given ensemble exists
this overwrites the standard value for that ensemble.</li>
<li><strong>N_sigma_global</strong> (float):
Standard value for N_sigma (default 1.0)</li>
<li><strong>N_sigma_dict</strong> (dict):
Dictionary for N_sigma values. If an entry for a given ensemble exists
this overwrites the standard value for that ensemble.</li>
</ul>
</div>
<div id="Obs.__init__" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.__init__">#&nbsp;&nbsp</a>
<span class="name">Obs</span><span class="signature">(samples, names, idl=None, means=None, **kwargs)</span>
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">samples</span><span class="p">,</span> <span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">means</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Initialize Obs object.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> samples : list</span>
<span class="sd"> list of numpy arrays containing the Monte Carlo samples</span>
<span class="sd"> names : list</span>
<span class="sd"> list of strings labeling the individual samples</span>
<span class="sd"> idl : list, optional</span>
<span class="sd"> list of ranges or lists on which the samples are defined</span>
<span class="sd"> means : list, optional</span>
<span class="sd"> list of mean values for the case that the mean values were</span>
<span class="sd"> already subtracted from the samples</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">means</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of samples and names incompatible.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">idl</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Length of idl incompatible with samples and names.&#39;</span><span class="p">)</span>
<span class="n">name_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="k">if</span> <span class="n">name_length</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name_length</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">names</span><span class="p">)):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;names are not unique.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">&#39;All names have to be strings.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">names</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">str</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">&#39;All names have to be strings.&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">min</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">samples</span><span class="p">)</span> <span class="o">&lt;=</span> <span class="mi">4</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Samples have to have at least 5 entries.&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">names</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">r_values</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_covobs</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">samples</span><span class="p">):</span>
<span class="k">if</span> <span class="n">idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="nb">range</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">idx</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idx</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
<span class="n">dc</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">idx</span><span class="p">))</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">any</span><span class="p">(</span><span class="n">dc</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Unsorted idx for idl[</span><span class="si">%s</span><span class="s2">]&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">dc</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">dc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">dc</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;incompatible type for idl[</span><span class="si">%s</span><span class="s1">].&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">if</span> <span class="n">means</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">mean</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">,</span> <span class="n">means</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</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> <span class="o">=</span> <span class="n">mean</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="n">sample</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">sample</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">names</span><span class="p">,</span> <span class="n">samples</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Incompatible samples and idx for </span><span class="si">%s</span><span class="s1">: </span><span class="si">%d</span><span class="s1"> vs. </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sample</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]))</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> <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">sample</span><span class="p">)</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="n">sample</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>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</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>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">/=</span> <span class="bp">self</span><span class="o">.</span><span class="n">N</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">=</span> <span class="mi">0</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="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
</pre></div>
</details>
<div class="docstring"><p>Initialize Obs object.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>samples</strong> (list):
list of numpy arrays containing the Monte Carlo samples</li>
<li><strong>names</strong> (list):
list of strings labeling the individual samples</li>
<li><strong>idl</strong> (list, optional):
list of ranges or lists on which the samples are defined</li>
<li><strong>means</strong> (list, optional):
list of mean values for the case that the mean values were
already subtracted from the samples</li>
</ul>
</div>
</div>
<div id="Obs.S_global" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.S_global">#&nbsp;&nbsp</a>
<span class="name">S_global</span><span class="default_value"> = 2.0</span>
</div>
</div>
<div id="Obs.S_dict" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.S_dict">#&nbsp;&nbsp</a>
<span class="name">S_dict</span><span class="default_value"> = {}</span>
</div>
</div>
<div id="Obs.tau_exp_global" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.tau_exp_global">#&nbsp;&nbsp</a>
<span class="name">tau_exp_global</span><span class="default_value"> = 0.0</span>
</div>
</div>
<div id="Obs.tau_exp_dict" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.tau_exp_dict">#&nbsp;&nbsp</a>
<span class="name">tau_exp_dict</span><span class="default_value"> = {}</span>
</div>
</div>
<div id="Obs.N_sigma_global" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.N_sigma_global">#&nbsp;&nbsp</a>
<span class="name">N_sigma_global</span><span class="default_value"> = 1.0</span>
</div>
</div>
<div id="Obs.N_sigma_dict" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.N_sigma_dict">#&nbsp;&nbsp</a>
<span class="name">N_sigma_dict</span><span class="default_value"> = {}</span>
</div>
</div>
<div id="Obs.filter_eps" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.filter_eps">#&nbsp;&nbsp</a>
<span class="name">filter_eps</span><span class="default_value"> = 1e-10</span>
</div>
</div>
<div id="Obs.names" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.names">#&nbsp;&nbsp</a>
<span class="name">names</span>
</div>
</div>
<div id="Obs.shape" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.shape">#&nbsp;&nbsp</a>
<span class="name">shape</span>
</div>
</div>
<div id="Obs.r_values" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.r_values">#&nbsp;&nbsp</a>
<span class="name">r_values</span>
</div>
</div>
<div id="Obs.deltas" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.deltas">#&nbsp;&nbsp</a>
<span class="name">deltas</span>
</div>
</div>
<div id="Obs.idl" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.idl">#&nbsp;&nbsp</a>
<span class="name">idl</span>
</div>
</div>
<div id="Obs.ddvalue" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.ddvalue">#&nbsp;&nbsp</a>
<span class="name">ddvalue</span>
</div>
</div>
<div id="Obs.reweighted" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.reweighted">#&nbsp;&nbsp</a>
<span class="name">reweighted</span>
</div>
</div>
<div id="Obs.tag" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.tag">#&nbsp;&nbsp</a>
<span class="name">tag</span>
</div>
</div>
<div id="Obs.value" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.value">#&nbsp;&nbsp</a>
<span class="name">value</span>
</div>
</div>
<div id="Obs.dvalue" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.dvalue">#&nbsp;&nbsp</a>
<span class="name">dvalue</span>
</div>
</div>
<div id="Obs.e_names" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_names">#&nbsp;&nbsp</a>
<span class="name">e_names</span>
</div>
</div>
<div id="Obs.cov_names" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.cov_names">#&nbsp;&nbsp</a>
<span class="name">cov_names</span>
</div>
</div>
<div id="Obs.mc_names" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.mc_names">#&nbsp;&nbsp</a>
<span class="name">mc_names</span>
</div>
</div>
<div id="Obs.e_content" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_content">#&nbsp;&nbsp</a>
<span class="name">e_content</span>
</div>
</div>
<div id="Obs.covobs" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.covobs">#&nbsp;&nbsp</a>
<span class="name">covobs</span>
</div>
</div>
<div id="Obs.gamma_method" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.gamma_method">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">gamma_method</span><span class="signature">(self, **kwargs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">gamma_method</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Estimate the error and related properties of the Obs.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> S : float</span>
<span class="sd"> specifies a custom value for the parameter S (default 2.0).</span>
<span class="sd"> If set to 0 it is assumed that the data exhibits no</span>
<span class="sd"> autocorrelation. In this case the error estimates coincides</span>
<span class="sd"> with the sample standard error.</span>
<span class="sd"> tau_exp : float</span>
<span class="sd"> positive value triggers the critical slowing down analysis</span>
<span class="sd"> (default 0.0).</span>
<span class="sd"> N_sigma : float</span>
<span class="sd"> number of standard deviations from zero until the tail is</span>
<span class="sd"> attached to the autocorrelation function (default 1).</span>
<span class="sd"> fft : bool</span>
<span class="sd"> determines whether the fft algorithm is used for the computation</span>
<span class="sd"> of the autocorrelation function (default True)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">e_content</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_content</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_gamma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span> <span class="o">=</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="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">S</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fft&#39;</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">False</span><span class="p">:</span>
<span class="n">fft</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">fft</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">_parse_kwarg</span><span class="p">(</span><span class="n">kwarg_name</span><span class="p">):</span>
<span class="k">if</span> <span class="n">kwarg_name</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">kwarg_name</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">)):</span>
<span class="k">if</span> <span class="n">tmp</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39; has to be larger or equal to 0.&#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="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39; is not in proper format.&#39;</span><span class="p">)</span>
<span class="k">else</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="n">e_name</span> <span class="ow">in</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_dict&#39;</span><span class="p">):</span>
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_dict&#39;</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwarg_name</span><span class="p">)[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">Obs</span><span class="p">,</span> <span class="n">kwarg_name</span> <span class="o">+</span> <span class="s1">&#39;_global&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;S&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;tau_exp&#39;</span><span class="p">)</span>
<span class="n">_parse_kwarg</span><span class="p">(</span><span class="s1">&#39;N_sigma&#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">mc_names</span><span class="p">):</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]])</span>
<span class="n">w_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calc_gamma</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">)</span>
<span class="n">gamma_div</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">e_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]:</span>
<span class="n">gamma_div</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calc_gamma</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">])),</span> <span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">,</span> <span class="n">fft</span><span class="p">)</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/=</span> <span class="n">gamma_div</span><span class="p">[:</span><span class="n">w_max</span><span class="p">]</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mi">10</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">finfo</span><span class="p">(</span><span class="nb">float</span><span class="p">)</span><span class="o">.</span><span class="n">tiny</span><span class="p">:</span> <span class="c1"># Prevent division by zero</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">continue</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">w_max</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(([</span><span class="mf">0.5</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:])))</span>
<span class="c1"># Make sure no entry of tauint is smaller than 0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">finfo</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span><span class="o">.</span><span class="n">eps</span>
<span class="c1"># hep-lat/0306017 eq. (42)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">w_max</span><span class="p">)</span> <span class="o">+</span> <span class="mf">0.5</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="k">def</span> <span class="nf">_compute_drho</span><span class="p">(</span><span class="n">i</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</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="n">w_max</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</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="mi">1</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="n">w_max</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">i</span><span class="p">]])</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="n">w_max</span> <span class="o">-</span> <span class="n">i</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">tmp</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">texp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span>
<span class="c1"># Critical slowing down analysis</span>
<span class="k">if</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">&lt;=</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Need at least 8 samples for tau_exp error analysis&quot;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span><span class="p">):</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">])</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
<span class="c1"># Bias correction hep-lat/0306017 eq. (49) included</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">+</span> <span class="n">texp</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">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> <span class="c1"># The absolute makes sure, that the tail contribution is always positive</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">texp</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span>
<span class="c1"># Error of tau_exp neglected so far, missing term: self.e_rho[e_name][n + 1] ** 2 * d_tau_exp ** 2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">n</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">n</span>
<span class="k">break</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">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="p">(</span><span class="n">e_N</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mf">0.5</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Standard automatic windowing procedure</span>
<span class="n">tau</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">((</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">g_w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span> <span class="o">/</span> <span class="n">tau</span><span class="p">)</span> <span class="o">-</span> <span class="n">tau</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span> <span class="o">*</span> <span class="n">e_N</span><span class="p">)</span>
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">w_max</span><span class="p">):</span>
<span class="k">if</span> <span class="n">n</span> <span class="o">&lt;</span> <span class="n">w_max</span> <span class="o">//</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">2</span><span class="p">:</span>
<span class="n">_compute_drho</span><span class="p">(</span><span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">g_w</span><span class="p">[</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">&gt;=</span> <span class="n">w_max</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">n</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="c1"># Bias correction hep-lat/0306017 eq. (49)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">n</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">n</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">n</span>
<span class="k">break</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">+=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</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">cov_names</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">errsq</span><span class="p">())</span>
<span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">**</span><span class="mi">2</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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="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="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ddvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</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="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span>
<span class="k">return</span>
</pre></div>
</details>
<div class="docstring"><p>Estimate the error and related properties of the Obs.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>S</strong> (float):
specifies a custom value for the parameter S (default 2.0).
If set to 0 it is assumed that the data exhibits no
autocorrelation. In this case the error estimates coincides
with the sample standard error.</li>
<li><strong>tau_exp</strong> (float):
positive value triggers the critical slowing down analysis
(default 0.0).</li>
<li><strong>N_sigma</strong> (float):
number of standard deviations from zero until the tail is
attached to the autocorrelation function (default 1).</li>
<li><strong>fft</strong> (bool):
determines whether the fft algorithm is used for the computation
of the autocorrelation function (default True)</li>
</ul>
</div>
</div>
<div id="Obs.details" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.details">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">details</span><span class="signature">(self, ens_content=True)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">details</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ens_content</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Output detailed properties of the Obs.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> ens_content : bool</span>
<span class="sd"> print details about the ensembles and replica if true.</span>
<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">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">mc_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_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;&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;</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">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_ddvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; t_int</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"> tau_exp = </span><span class="si">%3.2f</span><span class="s1">, N_sigma = </span><span class="si">%1.0i</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">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">N_sigma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; t_int</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"> S = </span><span class="si">%3.2f</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">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</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">cov_names</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;</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">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="n">ens_content</span> <span class="ow">is</span> <span class="kc">True</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">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">N</span><span class="p">,</span> <span class="s1">&#39;samples in&#39;</span><span class="p">,</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="s1">&#39;ensemble:&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">N</span><span class="p">,</span> <span class="s1">&#39;samples in&#39;</span><span class="p">,</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="s1">&#39;ensembles:&#39;</span><span class="p">)</span>
<span class="n">my_string_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_content</span><span class="o">.</span><span class="n">items</span><span class="p">()):</span>
<span class="k">if</span> <span class="n">key</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">covobs</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Ensemble &#39;&quot;</span> <span class="o">+</span> <span class="n">key</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39;: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="si">}</span><span class="s1"> configurations&#39;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39; (from </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">start</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">step</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="sa">f</span><span class="s1">&#39; in steps of </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">value</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">step</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="s1">&#39; (irregular range)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">sublist</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">value</span><span class="p">:</span>
<span class="n">my_substring</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Replicum &#39;&quot;</span> <span class="o">+</span> <span class="n">v</span><span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">key</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39;: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="si">}</span><span class="s1"> configurations&#39;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="sa">f</span><span class="s1">&#39; (from </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">start</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">step</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="sa">f</span><span class="s1">&#39; in steps of </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">v</span><span class="p">]</span><span class="o">.</span><span class="n">step</span><span class="si">}</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_substring</span> <span class="o">+=</span> <span class="s1">&#39; (irregular range)&#39;</span>
<span class="n">sublist</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_substring</span><span class="p">)</span>
<span class="n">my_string</span> <span class="o">+=</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">sublist</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">my_string</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\u00B7</span><span class="s2"> Covobs &#39;&quot;</span> <span class="o">+</span> <span class="n">key</span> <span class="o">+</span> <span class="s2">&quot;&#39; &quot;</span>
<span class="n">my_string_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">my_string</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">my_string_list</span><span class="p">))</span>
</pre></div>
</details>
<div class="docstring"><p>Output detailed properties of the Obs.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>ens_content</strong> (bool):
print details about the ensembles and replica if true.</li>
</ul>
</div>
</div>
<div id="Obs.is_zero_within_error" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.is_zero_within_error">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">is_zero_within_error</span><span class="signature">(self, sigma=1)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">is_zero_within_error</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Checks whether the observable is zero within &#39;sigma&#39; standard errors.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> sigma : int</span>
<span class="sd"> Number of standard errors used for the check.</span>
<span class="sd"> Works only properly when the gamma method was run.</span>
<span class="sd"> &quot;&quot;&quot;</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">&lt;=</span> <span class="n">sigma</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span>
</pre></div>
</details>
<div class="docstring"><p>Checks whether the observable is zero within 'sigma' standard errors.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>sigma</strong> (int):
Number of standard errors used for the check.</li>
<li><strong>Works only properly when the gamma method was run.</strong></li>
</ul>
</div>
</div>
<div id="Obs.is_zero" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.is_zero">#&nbsp;&nbsp</a>
<span class="def">def</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="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">&quot;&quot;&quot;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"> &quot;&quot;&quot;</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="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="o">.</span><span class="n">errsq</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">covobs</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 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>
</div>
<div id="Obs.plot_tauint" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.plot_tauint">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">plot_tauint</span><span class="signature">(self, save=None)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></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">&quot;&quot;&quot;Plot integrated autocorrelation time for each ensemble.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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_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">mc_names</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>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;$W$&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">&#39;$\tau_\mathrm</span><span class="si">{int}</span><span class="s1">$&#39;</span><span class="p">)</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]]</span>
<span class="n">x_help</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="n">y_help</span> <span class="o">=</span> <span class="p">(</span><span class="n">x_help</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</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">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">x_help</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</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> <span class="o">+</span> <span class="n">base</span>
<span class="n">x_arr</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x_arr</span><span class="p">,</span> <span class="n">y_help</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span>
<span class="n">yerr</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span> <span class="n">fmt</span><span class="o">=</span><span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;o&#39;</span><span class="p">,</span> <span class="n">mfc</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">&#39;axes.facecolor&#39;</span><span class="p">])</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.5</span>
<span class="n">label</span> <span class="o">=</span> <span class="n">e_name</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;, $\tau_\mathrm</span><span class="si">{exp}</span><span class="s1">$=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">label</span> <span class="o">=</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;, S=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mf">10.5</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">length</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">yerr</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_n_dtauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;C&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">),</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">(</span><span class="n">bottom</span><span class="o">=</span><span class="mf">0.0</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">))</span>
</pre></div>
</details>
<div class="docstring"><p>Plot integrated autocorrelation time for each ensemble.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>save</strong> (str):
saves the figure to a file named 'save' if.</li>
</ul>
</div>
</div>
<div id="Obs.plot_rho" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.plot_rho">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">plot_rho</span><span class="signature">(self, save=None)</span>:
</div>
<details>
<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="n">save</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot normalized autocorrelation function time for each ensemble.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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_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">mc_names</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>
<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>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;rho&#39;</span><span class="p">)</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">length</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">length</span><span class="p">],</span> <span class="n">yerr</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_drho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:],</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">capsize</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axvline</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;r&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</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> <span class="mi">0</span><span class="p">],</span> <span class="s1">&#39;k-&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.5</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Rho &#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="sa">r</span><span class="s1">&#39;, tau\_exp=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">)))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">xmax</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mf">10.5</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Rho &#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39;, S=&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">around</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">S</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">decimals</span><span class="o">=</span><span class="mi">2</span><span class="p">)))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">],</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="s1">&#39;k--&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">xmax</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span> <span class="o">+</span> <span class="s2">&quot;_&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="p">))</span>
</pre></div>
</details>
<div class="docstring"><p>Plot normalized autocorrelation function time for each ensemble.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>save</strong> (str):
saves the figure to a file named 'save' if.</li>
</ul>
</div>
</div>
<div id="Obs.plot_rep_dist" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.plot_rep_dist">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">plot_rep_dist</span><span class="signature">(self)</span>:
</div>
<details>
<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_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">mc_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>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;No replica distribution for a single replicum (&#39;</span><span class="p">,</span> <span class="n">e_name</span><span class="p">,</span> <span class="s1">&#39;)&#39;</span><span class="p">)</span>
<span class="k">continue</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">sub_r_mean</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="n">sub_r_mean</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">]</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span>
<span class="n">sub_r_mean</span> <span class="o">/=</span> <span class="n">e_N</span>
<span class="n">arr</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="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="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">arr</span><span class="p">[</span><span class="n">r</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">-</span> <span class="n">sub_r_mean</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">e_N</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">rwidth</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</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="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Replica distribution&#39;</span> <span class="o">+</span> <span class="n">e_name</span> <span class="o">+</span> <span class="s1">&#39; (mean=0, var=1)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
</pre></div>
</details>
<div class="docstring"><p>Plot replica distribution for each ensemble with more than one replicum.</p>
</div>
</div>
<div id="Obs.plot_history" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.plot_history">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">plot_history</span><span class="signature">(self, expand=True)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">plot_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Plot derived Monte Carlo history for each ensemble</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<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">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">mc_names</span><span class="p">):</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp_expanded</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r</span><span class="p">,</span> <span class="n">r_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_content</span><span class="p">[</span><span class="n">e_name</span><span class="p">]):</span>
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">])</span>
<span class="k">if</span> <span class="n">expand</span><span class="p">:</span>
<span class="n">tmp_expanded</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_expand_deltas</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_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">r_name</span><span class="p">])</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tmp_expanded</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]))</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">e_N</span><span class="p">)</span>
<span class="n">y_test</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="n">expand</span><span class="p">:</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">tmp_expanded</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">y_test</span>
<span class="n">plt</span><span class="o">.</span><span class="n">errorbar</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">fmt</span><span class="o">=</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">e_N</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">e_name</span> <span class="o">+</span> <span class="sa">f</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">skew: </span><span class="si">{</span><span class="n">skew</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> (p=</span><span class="si">{</span><span class="n">skewtest</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="o">.</span><span class="n">pvalue</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">), kurtosis: </span><span class="si">{</span><span class="n">kurtosis</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1"> (p=</span><span class="si">{</span><span class="n">kurtosistest</span><span class="p">(</span><span class="n">y_test</span><span class="p">)</span><span class="o">.</span><span class="n">pvalue</span><span class="si">:</span><span class="s1">.3f</span><span class="si">}</span><span class="s1">)&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
</pre></div>
</details>
<div class="docstring"><p>Plot derived Monte Carlo history for each ensemble</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>expand</strong> (bool):
show expanded history for irregular Monte Carlo chains (default: True).</li>
</ul>
</div>
</div>
<div id="Obs.plot_piechart" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.plot_piechart">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">plot_piechart</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<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_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>
<span class="n">labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">e_names</span>
<span class="n">sizes</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">e_dvalue</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">**</span> <span class="mi">2</span>
<span class="n">fig1</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">pie</span><span class="p">(</span><span class="n">sizes</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">,</span> <span class="n">startangle</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span> <span class="n">normalize</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">&#39;equal&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
<span class="k">return</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">zip</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">sizes</span><span class="p">))</span>
</pre></div>
</details>
<div class="docstring"><p>Plot piechart which shows the fractional contribution of each
ensemble to the error and returns a dictionary containing the fractions.</p>
</div>
</div>
<div id="Obs.dump" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.dump">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">dump</span><span class="signature">(self, filename, datatype=&#39;json.gz&#39;, **kwargs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">,</span> <span class="n">datatype</span><span class="o">=</span><span class="s2">&quot;json.gz&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Dump the Obs to a file &#39;name&#39; of chosen format.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> filename : str</span>
<span class="sd"> name of the file to be saved.</span>
<span class="sd"> datatype : str</span>
<span class="sd"> Format of the exported file. Supported formats include</span>
<span class="sd"> &quot;json.gz&quot; and &quot;pickle&quot;</span>
<span class="sd"> path : str</span>
<span class="sd"> specifies a custom path for the file (default &#39;.&#39;)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="s1">&#39;path&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">file_name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;path&#39;</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">filename</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">file_name</span> <span class="o">=</span> <span class="n">filename</span>
<span class="k">if</span> <span class="n">datatype</span> <span class="o">==</span> <span class="s2">&quot;json.gz&quot;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">.input.json</span> <span class="kn">import</span> <span class="n">dump_to_json</span>
<span class="n">dump_to_json</span><span class="p">([</span><span class="bp">self</span><span class="p">],</span> <span class="n">file_name</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">datatype</span> <span class="o">==</span> <span class="s2">&quot;pickle&quot;</span><span class="p">:</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file_name</span> <span class="o">+</span> <span class="s1">&#39;.p&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">fb</span><span class="p">:</span>
<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>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;Unknown datatype &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">datatype</span><span class="p">))</span>
</pre></div>
</details>
<div class="docstring"><p>Dump the Obs to a file 'name' of chosen format.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>filename</strong> (str):
name of the file to be saved.</li>
<li><strong>datatype</strong> (str):
Format of the exported file. Supported formats include
"json.gz" and "pickle"</li>
<li><strong>path</strong> (str):
specifies a custom path for the file (default '.')</li>
</ul>
</div>
</div>
<div id="Obs.export_jackknife" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.export_jackknife">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">export_jackknife</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<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>
<span class="sd">&quot;&quot;&quot;Export jackknife samples from the Obs</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> numpy.ndarray</span>
<span class="sd"> Returns a numpy array of length N + 1 where N is the number of samples</span>
<span class="sd"> for the given ensemble and replicum. The zeroth entry of the array contains</span>
<span class="sd"> the mean value of the Obs, entries 1 to N contain the N jackknife samples</span>
<span class="sd"> derived from the Obs. The current implementation only works for observables</span>
<span class="sd"> defined on exactly one ensemble and replicum. The derived jackknife samples</span>
<span class="sd"> should agree with samples from a full jackknife analysis up to O(1/N).</span>
<span class="sd"> &quot;&quot;&quot;</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">names</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">&quot;&#39;export_jackknife&#39; is only implemented for Obs defined on one ensemble and replicum.&quot;</span><span class="p">)</span>
<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>
<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>
<span class="n">n</span> <span class="o">=</span> <span class="n">full_data</span><span class="o">.</span><span class="n">size</span>
<span class="n">mean</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span>
<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>
<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="n">mean</span>
<span class="n">tmp_jacks</span><span class="p">[</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="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">return</span> <span class="n">tmp_jacks</span>
</pre></div>
</details>
<div class="docstring"><p>Export jackknife samples from the Obs</p>
<h6 id="returns">Returns</h6>
<ul>
<li><strong>numpy.ndarray</strong>: Returns a numpy array of length N + 1 where N is the number of samples
for the given ensemble and replicum. The zeroth entry of the array contains
the mean value of the Obs, entries 1 to N contain the N jackknife samples
derived from the Obs. The current implementation only works for observables
defined on exactly one ensemble and replicum. The derived jackknife samples
should agree with samples from a full jackknife analysis up to O(1/N).</li>
</ul>
</div>
</div>
<div id="Obs.sqrt" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.sqrt">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">sqrt</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="mi">2</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)])</span>
</pre></div>
</details>
</div>
<div id="Obs.log" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.log">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">log</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">log</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.exp" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.exp">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">exp</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">exp</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)])</span>
</pre></div>
</details>
</div>
<div id="Obs.sin" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.sin">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">sin</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">sin</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)])</span>
</pre></div>
</details>
</div>
<div id="Obs.cos" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.cos">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">cos</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">cos</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)])</span>
</pre></div>
</details>
</div>
<div id="Obs.tan" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.tan">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">tan</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">tan</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">tan</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</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="mi">2</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.arcsin" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.arcsin">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">arcsin</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">arcsin</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arcsin</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.arccos" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.arccos">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">arccos</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">arccos</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arccos</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.arctan" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.arctan">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">arctan</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">arctan</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arctan</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.sinh" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.sinh">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">sinh</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">sinh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">sinh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">cosh</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)])</span>
</pre></div>
</details>
</div>
<div id="Obs.cosh" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.cosh">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">cosh</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">cosh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">cosh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">sinh</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)])</span>
</pre></div>
</details>
</div>
<div id="Obs.tanh" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.tanh">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">tanh</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">tanh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">],</span> <span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">cosh</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="mi">2</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.arcsinh" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.arcsinh">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">arcsinh</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">arcsinh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arcsinh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.arccosh" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.arccosh">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">arccosh</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">arccosh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arccosh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.arctanh" class="classattr">
<div class="attr function"><a class="headerlink" href="#Obs.arctanh">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">arctanh</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">arctanh</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">anp</span><span class="o">.</span><span class="n">arctanh</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="p">[</span><span class="bp">self</span><span class="p">])</span>
</pre></div>
</details>
</div>
<div id="Obs.N" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.N">#&nbsp;&nbsp</a>
<span class="name">N</span>
</div>
</div>
<div id="Obs.N_sigma" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.N_sigma">#&nbsp;&nbsp</a>
<span class="name">N_sigma</span>
</div>
</div>
<div id="Obs.S" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.S">#&nbsp;&nbsp</a>
<span class="name">S</span>
</div>
</div>
<div id="Obs.e_ddvalue" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_ddvalue">#&nbsp;&nbsp</a>
<span class="name">e_ddvalue</span>
</div>
</div>
<div id="Obs.e_drho" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_drho">#&nbsp;&nbsp</a>
<span class="name">e_drho</span>
</div>
</div>
<div id="Obs.e_dtauint" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_dtauint">#&nbsp;&nbsp</a>
<span class="name">e_dtauint</span>
</div>
</div>
<div id="Obs.e_dvalue" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_dvalue">#&nbsp;&nbsp</a>
<span class="name">e_dvalue</span>
</div>
</div>
<div id="Obs.e_n_dtauint" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_n_dtauint">#&nbsp;&nbsp</a>
<span class="name">e_n_dtauint</span>
</div>
</div>
<div id="Obs.e_n_tauint" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_n_tauint">#&nbsp;&nbsp</a>
<span class="name">e_n_tauint</span>
</div>
</div>
<div id="Obs.e_rho" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_rho">#&nbsp;&nbsp</a>
<span class="name">e_rho</span>
</div>
</div>
<div id="Obs.e_tauint" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_tauint">#&nbsp;&nbsp</a>
<span class="name">e_tauint</span>
</div>
</div>
<div id="Obs.e_windowsize" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.e_windowsize">#&nbsp;&nbsp</a>
<span class="name">e_windowsize</span>
</div>
</div>
<div id="Obs.is_merged" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.is_merged">#&nbsp;&nbsp</a>
<span class="name">is_merged</span>
</div>
</div>
<div id="Obs.tau_exp" class="classattr">
<div class="attr variable"><a class="headerlink" href="#Obs.tau_exp">#&nbsp;&nbsp</a>
<span class="name">tau_exp</span>
</div>
</div>
</section>
<section id="CObs">
<div class="attr class">
<a class="headerlink" href="#CObs">#&nbsp;&nbsp</a>
<span class="def">class</span>
<span class="name">CObs</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">class</span> <span class="nc">CObs</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;Class for a complex valued observable.&quot;&quot;&quot;</span>
<span class="vm">__slots__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;_real&#39;</span><span class="p">,</span> <span class="s1">&#39;_imag&#39;</span><span class="p">,</span> <span class="s1">&#39;tag&#39;</span><span class="p">]</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">real</span><span class="p">,</span> <span class="n">imag</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_real</span> <span class="o">=</span> <span class="n">real</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imag</span> <span class="o">=</span> <span class="n">imag</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">real</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_real</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">imag</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imag</span>
<span class="k">def</span> <span class="nf">gamma_method</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Executes the gamma_method for the real and the imaginary part.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</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="sd">&quot;&quot;&quot;Checks whether both real and imaginary part are zero within machine precision.&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">==</span> <span class="mf">0.0</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">==</span> <span class="mf">0.0</span>
<span class="k">def</span> <span class="nf">conjugate</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__add__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">other</span> <span class="o">+</span> <span class="bp">self</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">+</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__radd__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">+</span> <span class="n">y</span>
<span class="k">def</span> <span class="fm">__sub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="n">other</span> <span class="o">-</span> <span class="bp">self</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">-</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__rsub__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span> <span class="o">-</span> <span class="n">other</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__mul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">other</span> <span class="o">*</span> <span class="bp">self</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">Obs</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">]):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">],</span>
<span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">other</span><span class="o">.</span><span class="n">real</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">real</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">-</span><span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">value</span><span class="p">]),</span>
<span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span>
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">],</span>
<span class="n">man_grad</span><span class="o">=</span><span class="p">[</span><span class="n">other</span><span class="o">.</span><span class="n">imag</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">imag</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">other</span><span class="o">.</span><span class="n">real</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">real</span><span class="o">.</span><span class="n">value</span><span class="p">]))</span>
<span class="k">elif</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__rmul__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span> <span class="o">*</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__truediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="mi">1</span> <span class="o">/</span> <span class="p">(</span><span class="n">other</span> <span class="o">/</span> <span class="bp">self</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="n">r</span> <span class="o">=</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span> <span class="o">**</span> <span class="mi">2</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">/</span> <span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">/</span> <span class="n">other</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__rtruediv__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="n">r</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">**</span> <span class="mi">2</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">**</span> <span class="mi">2</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;real&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="s1">&#39;imag&#39;</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span><span class="p">)</span> <span class="o">/</span> <span class="n">r</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">*</span> <span class="n">other</span> <span class="o">/</span> <span class="n">r</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">*</span> <span class="n">other</span> <span class="o">/</span> <span class="n">r</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__abs__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__neg__</span><span class="p">(</span><span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="n">other</span>
<span class="k">def</span> <span class="fm">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">real</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">imag</span>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;(&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">)</span> <span class="o">+</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">&gt;=</span> <span class="mf">0.0</span><span class="p">)</span> <span class="o">*</span> <span class="s1">&#39;+&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;j)&#39;</span>
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;CObs[&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;]&#39;</span>
</pre></div>
</details>
<div class="docstring"><p>Class for a complex valued observable.</p>
</div>
<div id="CObs.__init__" class="classattr">
<div class="attr function"><a class="headerlink" href="#CObs.__init__">#&nbsp;&nbsp</a>
<span class="name">CObs</span><span class="signature">(real, imag=0.0)</span>
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">real</span><span class="p">,</span> <span class="n">imag</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_real</span> <span class="o">=</span> <span class="n">real</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imag</span> <span class="o">=</span> <span class="n">imag</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tag</span> <span class="o">=</span> <span class="kc">None</span>
</pre></div>
</details>
</div>
<div id="CObs.tag" class="classattr">
<div class="attr variable"><a class="headerlink" href="#CObs.tag">#&nbsp;&nbsp</a>
<span class="name">tag</span>
</div>
</div>
<div id="CObs.real" class="classattr">
<div class="attr variable"><a class="headerlink" href="#CObs.real">#&nbsp;&nbsp</a>
<span class="name">real</span>
</div>
</div>
<div id="CObs.imag" class="classattr">
<div class="attr variable"><a class="headerlink" href="#CObs.imag">#&nbsp;&nbsp</a>
<span class="name">imag</span>
</div>
</div>
<div id="CObs.gamma_method" class="classattr">
<div class="attr function"><a class="headerlink" href="#CObs.gamma_method">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">gamma_method</span><span class="signature">(self, **kwargs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">gamma_method</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Executes the gamma_method for the real and the imaginary part.&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">,</span> <span class="n">Obs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</pre></div>
</details>
<div class="docstring"><p>Executes the gamma_method for the real and the imaginary part.</p>
</div>
</div>
<div id="CObs.is_zero" class="classattr">
<div class="attr function"><a class="headerlink" href="#CObs.is_zero">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">is_zero</span><span class="signature">(self)</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">&quot;&quot;&quot;Checks whether both real and imaginary part are zero within machine precision.&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">real</span> <span class="o">==</span> <span class="mf">0.0</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">imag</span> <span class="o">==</span> <span class="mf">0.0</span>
</pre></div>
</details>
<div class="docstring"><p>Checks whether both real and imaginary part are zero within machine precision.</p>
</div>
</div>
<div id="CObs.conjugate" class="classattr">
<div class="attr function"><a class="headerlink" href="#CObs.conjugate">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">conjugate</span><span class="signature">(self)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">conjugate</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">CObs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">real</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">imag</span><span class="p">)</span>
</pre></div>
</details>
</div>
</section>
<section id="derived_observable">
<div class="attr function"><a class="headerlink" href="#derived_observable">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">derived_observable</span><span class="signature">(func, data, array_mode=False, **kwargs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">derived_observable</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">array_mode</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Construct a derived Obs according to func(data, **kwargs) using automatic differentiation.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> func : object</span>
<span class="sd"> arbitrary function of the form func(data, **kwargs). For the</span>
<span class="sd"> automatic differentiation to work, all numpy functions have to have</span>
<span class="sd"> the autograd wrapper (use &#39;import autograd.numpy as anp&#39;).</span>
<span class="sd"> data : list</span>
<span class="sd"> list of Obs, e.g. [obs1, obs2, obs3].</span>
<span class="sd"> num_grad : bool</span>
<span class="sd"> if True, numerical derivatives are used instead of autograd</span>
<span class="sd"> (default False). To control the numerical differentiation the</span>
<span class="sd"> kwargs of numdifftools.step_generators.MaxStepGenerator</span>
<span class="sd"> can be used.</span>
<span class="sd"> man_grad : list</span>
<span class="sd"> manually supply a list or an array which contains the jacobian</span>
<span class="sd"> of func. Use cautiously, supplying the wrong derivative will</span>
<span class="sd"> not be intercepted.</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> For simple mathematical operations it can be practical to use anonymous</span>
<span class="sd"> functions. For the ratio of two observables one can e.g. use</span>
<span class="sd"> new_obs = derived_observable(lambda x: x[0] / x[1], [obs1, obs2])</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="n">raveled_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="c1"># Workaround for matrix operations containing non Obs data</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">Obs</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">):</span>
<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="nb">len</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">)):</span>
<span class="n">raveled_data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">cov_Obs</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="mf">0.0</span><span class="p">,</span> <span class="s2">&quot;###dummy_covobs###&quot;</span><span class="p">)</span>
<span class="n">allcov</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">allcov</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">allcov</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">cov</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Inconsistent covariance matrices for </span><span class="si">%s</span><span class="s1">!&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">name</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">allcov</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">cov</span>
<span class="n">n_obs</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">)</span>
<span class="n">new_names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">]</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]))</span>
<span class="n">new_cov_names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">cov_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">]</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]))</span>
<span class="n">new_sample_names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">new_names</span><span class="p">)</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">new_cov_names</span><span class="p">))</span>
<span class="n">is_merged</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="k">lambda</span> <span class="n">o</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">,</span> <span class="n">raveled_data</span><span class="p">)))</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">}</span>
<span class="n">reweighted</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="k">lambda</span> <span class="n">o</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">,</span> <span class="n">raveled_data</span><span class="p">)))</span> <span class="o">&gt;</span> <span class="mi">0</span>
<span class="k">if</span> <span class="n">data</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">value</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">data</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vectorize</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">value</span><span class="p">)(</span><span class="n">data</span><span class="p">)</span>
<span class="n">new_values</span> <span class="o">=</span> <span class="n">func</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">multi</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">new_values</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">))</span>
<span class="n">new_r_values</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">new_idl_d</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">:</span>
<span class="n">idl</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">tmp_values</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_obs</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">item</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">raveled_data</span><span class="p">):</span>
<span class="n">tmp_values</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">item</span><span class="o">.</span><span class="n">r_values</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">item</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
<span class="n">tmp_idl</span> <span class="o">=</span> <span class="n">item</span><span class="o">.</span><span class="n">idl</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="k">if</span> <span class="n">tmp_idl</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">idl</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp_idl</span><span class="p">)</span>
<span class="k">if</span> <span class="n">multi</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">tmp_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">tmp_values</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="n">new_r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">func</span><span class="p">(</span><span class="n">tmp_values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">_merge_idx</span><span class="p">(</span><span class="n">idl</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">is_merged</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="n">is_merged</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="p">[</span><span class="o">*</span><span class="n">idl</span><span class="p">,</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]]])))</span>
<span class="k">if</span> <span class="s1">&#39;man_grad&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;man_grad&#39;</span><span class="p">))</span>
<span class="k">if</span> <span class="n">new_values</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span> <span class="o">!=</span> <span class="n">deriv</span><span class="o">.</span><span class="n">shape</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Manual derivative does not have correct shape.&#39;</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;num_grad&#39;</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="k">if</span> <span class="n">multi</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Multi mode currently not supported for numerical derivative&#39;</span><span class="p">)</span>
<span class="n">options</span> <span class="o">=</span> <span class="p">{</span>
<span class="s1">&#39;base_step&#39;</span><span class="p">:</span> <span class="mf">0.1</span><span class="p">,</span>
<span class="s1">&#39;step_ratio&#39;</span><span class="p">:</span> <span class="mf">2.5</span><span class="p">}</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">options</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">kwarg</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">)</span>
<span class="k">if</span> <span class="n">kwarg</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">options</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">kwarg</span>
<span class="n">tmp_df</span> <span class="o">=</span> <span class="n">nd</span><span class="o">.</span><span class="n">Gradient</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="o">**</span><span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">options</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">v</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">})(</span><span class="n">values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="n">tmp_df</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">tmp_df</span><span class="o">.</span><span class="n">real</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">tmp_df</span><span class="o">.</span><span class="n">real</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">deriv</span> <span class="o">=</span> <span class="n">jacobian</span><span class="p">(</span><span class="n">func</span><span class="p">)(</span><span class="n">values</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">final_result</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">new_values</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">object</span><span class="p">)</span>
<span class="k">if</span> <span class="n">array_mode</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="k">class</span> <span class="nc">_Zero_grad</span><span class="p">():</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">N</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">grad</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="p">,</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">new_covobs_lengths</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">y</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">[[(</span><span class="n">n</span><span class="p">,</span> <span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">n</span><span class="p">]</span><span class="o">.</span><span class="n">N</span><span class="p">)</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">cov_names</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">raveled_data</span><span class="p">]</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]))</span>
<span class="n">d_extracted</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">g_extracted</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">:</span>
<span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">ens_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
<span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">_expand_deltas_for_merge</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">ens_length</span><span class="p">)),</span> <span class="n">o</span><span class="o">.</span><span class="n">idl</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]),</span> <span class="n">o</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">ens_length</span><span class="p">),</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">dat</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span><span class="p">))])</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="p">(</span><span class="n">ens_length</span><span class="p">,</span> <span class="p">)))</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_cov_names</span><span class="p">:</span>
<span class="n">g_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">zero_grad</span> <span class="o">=</span> <span class="n">_Zero_grad</span><span class="p">(</span><span class="n">new_covobs_lengths</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
<span class="n">g_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">o</span><span class="o">.</span><span class="n">covobs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">zero_grad</span><span class="p">)</span><span class="o">.</span><span class="n">grad</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">dat</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span><span class="p">))])</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">dat</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="p">(</span><span class="n">new_covobs_lengths</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="mi">1</span><span class="p">)))</span>
<span class="k">for</span> <span class="n">i_val</span><span class="p">,</span> <span class="n">new_val</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">new_values</span><span class="p">):</span>
<span class="n">new_deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">new_grad</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">if</span> <span class="n">array_mode</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_sample_names</span><span class="p">:</span>
<span class="n">ens_length</span> <span class="o">=</span> <span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
<span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</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">ens_length</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">d_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]):</span>
<span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">tensordot</span><span class="p">(</span><span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="p">(</span><span class="n">i_dat</span><span class="p">,</span> <span class="p">)],</span> <span class="n">dat</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_cov_names</span><span class="p">:</span>
<span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">i_dat</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">g_extracted</span><span class="p">[</span><span class="n">name</span><span class="p">]):</span>
<span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">tensordot</span><span class="p">(</span><span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="p">(</span><span class="n">i_dat</span><span class="p">,</span> <span class="p">)],</span> <span class="n">dat</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">j_obs</span><span class="p">,</span> <span class="n">obs</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">data</span><span class="p">):</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">new_grad</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">+</span> <span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="n">j_obs</span><span class="p">]</span> <span class="o">*</span> <span class="n">obs</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">new_deltas</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">+</span> <span class="n">deriv</span><span class="p">[</span><span class="n">i_val</span> <span class="o">+</span> <span class="n">j_obs</span><span class="p">]</span> <span class="o">*</span> <span class="n">_expand_deltas_for_merge</span><span class="p">(</span><span class="n">obs</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="n">obs</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">obs</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">new_covobs</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="n">Covobs</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">allcov</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">name</span><span class="p">,</span> <span class="n">grad</span><span class="o">=</span><span class="n">new_grad</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_grad</span><span class="p">}</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">new_covobs</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">.</span><span class="n">isdisjoint</span><span class="p">(</span><span class="n">new_deltas</span><span class="o">.</span><span class="n">keys</span><span class="p">()):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;The same name has been used for deltas and covobs!&#39;</span><span class="p">)</span>
<span class="n">new_samples</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_means</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_idl</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_names_obs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">new_covobs</span><span class="p">:</span>
<span class="k">if</span> <span class="n">is_merged</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="n">filtered_deltas</span><span class="p">,</span> <span class="n">filtered_idl_d</span> <span class="o">=</span> <span class="n">_filter_zeroes</span><span class="p">(</span><span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">filtered_deltas</span> <span class="o">=</span> <span class="n">new_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="n">filtered_idl_d</span> <span class="o">=</span> <span class="n">new_idl_d</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="n">new_samples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">filtered_deltas</span><span class="p">)</span>
<span class="n">new_idl</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">filtered_idl_d</span><span class="p">)</span>
<span class="n">new_means</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">new_r_values</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="n">i_val</span><span class="p">])</span>
<span class="n">new_names_obs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">new_samples</span><span class="p">,</span> <span class="n">new_names_obs</span><span class="p">,</span> <span class="n">means</span><span class="o">=</span><span class="n">new_means</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="n">new_idl</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">new_covobs</span><span class="p">:</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">_covobs</span> <span class="o">=</span> <span class="n">new_covobs</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="n">new_val</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="n">is_merged</span>
<span class="n">final_result</span><span class="p">[</span><span class="n">i_val</span><span class="p">]</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="n">reweighted</span>
<span class="k">if</span> <span class="n">multi</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">final_result</span> <span class="o">=</span> <span class="n">final_result</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="k">return</span> <span class="n">final_result</span>
</pre></div>
</details>
<div class="docstring"><p>Construct a derived Obs according to func(data, **kwargs) using automatic differentiation.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>func</strong> (object):
arbitrary function of the form func(data, **kwargs). For the
automatic differentiation to work, all numpy functions have to have
the autograd wrapper (use 'import autograd.numpy as anp').</li>
<li><strong>data</strong> (list):
list of Obs, e.g. [obs1, obs2, obs3].</li>
<li><strong>num_grad</strong> (bool):
if True, numerical derivatives are used instead of autograd
(default False). To control the numerical differentiation the
kwargs of numdifftools.step_generators.MaxStepGenerator
can be used.</li>
<li><strong>man_grad</strong> (list):
manually supply a list or an array which contains the jacobian
of func. Use cautiously, supplying the wrong derivative will
not be intercepted.</li>
</ul>
<h6 id="notes">Notes</h6>
<p>For simple mathematical operations it can be practical to use anonymous
functions. For the ratio of two observables one can e.g. use</p>
<p>new_obs = derived_observable(lambda x: x[0] / x[1], [obs1, obs2])</p>
</div>
</section>
<section id="reweight">
<div class="attr function"><a class="headerlink" href="#reweight">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">reweight</span><span class="signature">(weight, obs, **kwargs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">reweight</span><span class="p">(</span><span class="n">weight</span><span class="p">,</span> <span class="n">obs</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Reweight a list of observables.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> weight : Obs</span>
<span class="sd"> Reweighting factor. An Observable that has to be defined on a superset of the</span>
<span class="sd"> configurations in obs[i].idl for all i.</span>
<span class="sd"> obs : list</span>
<span class="sd"> list of Obs, e.g. [obs1, obs2, obs3].</span>
<span class="sd"> all_configs : bool</span>
<span class="sd"> if True, the reweighted observables are normalized by the average of</span>
<span class="sd"> the reweighting factor on all configurations in weight.idl and not</span>
<span class="sd"> on the configurations in obs[i].idl.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">result</span> <span class="o">=</span> <span class="p">[]</span>
<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="nb">len</span><span class="p">(</span><span class="n">obs</span><span class="p">)):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">cov_names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error: Not possible to reweight an Obs that contains covobs!&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)</span><span class="o">.</span><span class="n">issubset</span><span class="p">(</span><span class="n">weight</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error: Ensembles do not fit&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span><span class="o">.</span><span class="n">issubset</span><span class="p">(</span><span class="n">weight</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;obs[</span><span class="si">%d</span><span class="s1">] has to be defined on a subset of the configs in weight.idl[</span><span class="si">%s</span><span class="s1">]!&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">name</span><span class="p">))</span>
<span class="n">new_samples</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">w_deltas</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="n">w_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">_reduce_deltas</span><span class="p">(</span><span class="n">weight</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="n">weight</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">new_samples</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">w_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">weight</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="o">*</span> <span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</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="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]))</span>
<span class="n">tmp_obs</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">new_samples</span><span class="p">,</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">),</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)])</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;all_configs&#39;</span><span class="p">):</span>
<span class="n">new_weight</span> <span class="o">=</span> <span class="n">weight</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">new_weight</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([</span><span class="n">w_deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">weight</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)],</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">),</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">names</span><span class="p">)])</span>
<span class="n">result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">derived_observable</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="n">tmp_obs</span><span class="p">,</span> <span class="n">new_weight</span><span class="p">],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
<span class="n">result</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">result</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="n">obs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">is_merged</span>
<span class="k">return</span> <span class="n">result</span>
</pre></div>
</details>
<div class="docstring"><p>Reweight a list of observables.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>weight</strong> (Obs):
Reweighting factor. An Observable that has to be defined on a superset of the
configurations in obs[i].idl for all i.</li>
<li><strong>obs</strong> (list):
list of Obs, e.g. [obs1, obs2, obs3].</li>
<li><strong>all_configs</strong> (bool):
if True, the reweighted observables are normalized by the average of
the reweighting factor on all configurations in weight.idl and not
on the configurations in obs[i].idl.</li>
</ul>
</div>
</section>
<section id="correlate">
<div class="attr function"><a class="headerlink" href="#correlate">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">correlate</span><span class="signature">(obs_a, obs_b)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">correlate</span><span class="p">(</span><span class="n">obs_a</span><span class="p">,</span> <span class="n">obs_b</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Correlate two observables.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> obs_a : Obs</span>
<span class="sd"> First observable</span>
<span class="sd"> obs_b : Obs</span>
<span class="sd"> Second observable</span>
<span class="sd"> Keep in mind to only correlate primary observables which have not been reweighted</span>
<span class="sd"> yet. The reweighting has to be applied after correlating the observables.</span>
<span class="sd"> Currently only works if ensembles are identical (this is not strictly necessary).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_b</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Ensembles do not fit&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">cov_names</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="n">obs_b</span><span class="o">.</span><span class="n">cov_names</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Error: Not possible to correlate Obs that contain covobs!&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">!=</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Shapes of ensemble&#39;</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="s1">&#39;do not fit&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">!=</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;idl of ensemble&#39;</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="s1">&#39;do not fit&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s2">&quot;The first observable is already reweighted.&quot;</span><span class="p">,</span> <span class="ne">RuntimeWarning</span><span class="p">)</span>
<span class="k">if</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s2">&quot;The second observable is already reweighted.&quot;</span><span class="p">,</span> <span class="ne">RuntimeWarning</span><span class="p">)</span>
<span class="n">new_samples</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">new_idl</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">):</span>
<span class="n">new_samples</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">obs_a</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="n">obs_a</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">])</span> <span class="o">*</span> <span class="p">(</span><span class="n">obs_b</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="n">obs_b</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]))</span>
<span class="n">new_idl</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">o</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">new_samples</span><span class="p">,</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">names</span><span class="p">),</span> <span class="n">idl</span><span class="o">=</span><span class="n">new_idl</span><span class="p">)</span>
<span class="n">o</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="p">(</span><span class="n">obs_a</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="ow">or</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">))</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">names</span><span class="p">}</span>
<span class="n">o</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="n">obs_a</span><span class="o">.</span><span class="n">reweighted</span> <span class="ow">or</span> <span class="n">obs_b</span><span class="o">.</span><span class="n">reweighted</span>
<span class="k">return</span> <span class="n">o</span>
</pre></div>
</details>
<div class="docstring"><p>Correlate two observables.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>obs_a</strong> (Obs):
First observable</li>
<li><strong>obs_b</strong> (Obs):
Second observable</li>
<li><strong>Keep in mind to only correlate primary observables which have not been reweighted</strong></li>
<li><strong>yet. The reweighting has to be applied after correlating the observables.</strong></li>
<li><strong>Currently only works if ensembles are identical (this is not strictly necessary).</strong></li>
</ul>
</div>
</section>
<section id="covariance">
<div class="attr function"><a class="headerlink" href="#covariance">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">covariance</span><span class="signature">(obs1, obs2, correlation=False, **kwargs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">covariance</span><span class="p">(</span><span class="n">obs1</span><span class="p">,</span> <span class="n">obs2</span><span class="p">,</span> <span class="n">correlation</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Calculates the covariance of two observables.</span>
<span class="sd"> covariance(obs, obs) is equal to obs.dvalue ** 2</span>
<span class="sd"> The gamma method has to be applied first to both observables.</span>
<span class="sd"> If abs(covariance(obs1, obs2)) &gt; obs1.dvalue * obs2.dvalue, the covariance</span>
<span class="sd"> is constrained to the maximum value.</span>
<span class="sd"> Keyword arguments</span>
<span class="sd"> -----------------</span>
<span class="sd"> correlation -- if true the correlation instead of the covariance is</span>
<span class="sd"> returned (default False)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">expand_deltas</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="n">idx</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">new_idx</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Expand deltas defined on idx to a contiguous range [new_idx[0], new_idx[-1]].</span>
<span class="sd"> New, empy entries are filled by 0. If idx and new_idx are of type range, the smallest</span>
<span class="sd"> common divisor of the step sizes is used as new step size.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> deltas -- List of fluctuations</span>
<span class="sd"> idx -- List or range of configs on which the deltas are defined.</span>
<span class="sd"> Has to be a subset of new_idx.</span>
<span class="sd"> shape -- Number of configs in idx.</span>
<span class="sd"> new_idx -- List of configs that defines the new range.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span> <span class="ow">and</span> <span class="nb">type</span><span class="p">(</span><span class="n">new_idx</span><span class="p">)</span> <span class="ow">is</span> <span class="nb">range</span><span class="p">:</span>
<span class="k">if</span> <span class="n">idx</span> <span class="o">==</span> <span class="n">new_idx</span><span class="p">:</span>
<span class="k">return</span> <span class="n">deltas</span>
<span class="n">ret</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">new_idx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<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">shape</span><span class="p">):</span>
<span class="n">ret</span><span class="p">[</span><span class="n">idx</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">-</span> <span class="n">new_idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">=</span> <span class="n">deltas</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="k">return</span> <span class="n">ret</span>
<span class="k">def</span> <span class="nf">calc_gamma</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">deltas2</span><span class="p">,</span> <span class="n">idx1</span><span class="p">,</span> <span class="n">idx2</span><span class="p">,</span> <span class="n">new_idx</span><span class="p">,</span> <span class="n">w_max</span><span class="p">):</span>
<span class="n">gamma</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">w_max</span><span class="p">)</span>
<span class="n">deltas1</span> <span class="o">=</span> <span class="n">expand_deltas</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">idx1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx1</span><span class="p">),</span> <span class="n">new_idx</span><span class="p">)</span>
<span class="n">deltas2</span> <span class="o">=</span> <span class="n">expand_deltas</span><span class="p">(</span><span class="n">deltas2</span><span class="p">,</span> <span class="n">idx2</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">idx2</span><span class="p">),</span> <span class="n">new_idx</span><span class="p">)</span>
<span class="n">new_shape</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">deltas1</span><span class="p">)</span>
<span class="n">max_gamma</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">new_shape</span><span class="p">,</span> <span class="n">w_max</span><span class="p">)</span>
<span class="c1"># The padding for the fft has to be even</span>
<span class="n">padding</span> <span class="o">=</span> <span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span> <span class="o">+</span> <span class="p">(</span><span class="n">new_shape</span> <span class="o">+</span> <span class="n">max_gamma</span><span class="p">)</span> <span class="o">%</span> <span class="mi">2</span>
<span class="n">gamma</span><span class="p">[:</span><span class="n">max_gamma</span><span class="p">]</span> <span class="o">+=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">padding</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">conjugate</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas2</span><span class="p">,</span> <span class="n">padding</span><span class="p">)))[:</span><span class="n">max_gamma</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfft</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas2</span><span class="p">,</span> <span class="n">padding</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">conjugate</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfft</span><span class="p">(</span><span class="n">deltas1</span><span class="p">,</span> <span class="n">padding</span><span class="p">)))[:</span><span class="n">max_gamma</span><span class="p">])</span> <span class="o">/</span> <span class="mf">2.0</span>
<span class="k">return</span> <span class="n">gamma</span>
<span class="k">if</span> <span class="nb">set</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">names</span><span class="p">)</span><span class="o">.</span><span class="n">isdisjoint</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">obs2</span><span class="o">.</span><span class="n">names</span><span class="p">)):</span>
<span class="k">return</span> <span class="mf">0.</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">obs1</span><span class="p">,</span> <span class="s1">&#39;e_dvalue&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">obs2</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;The gamma method has to be applied to both Obs first.&#39;</span><span class="p">)</span>
<span class="n">dvalue</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">e_gamma</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_dvalue</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_n_tauint</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">e_rho</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="n">obs1</span><span class="o">.</span><span class="n">mc_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">e_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</span><span class="o">.</span><span class="n">mc_names</span><span class="p">:</span>
<span class="k">continue</span>
<span class="n">idl_d</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">r_length</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="k">if</span> <span class="n">r_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</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="k">continue</span>
<span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">_merge_idx</span><span class="p">([</span><span class="n">obs1</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">]])</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="nb">range</span><span class="p">):</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">r_length</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">r_length</span><span class="p">:</span>
<span class="k">return</span> <span class="mf">0.</span>
<span class="n">w_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">r_length</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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">w_max</span><span class="p">)</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="k">if</span> <span class="n">r_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</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="k">continue</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">+=</span> <span class="n">calc_gamma</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs1</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">)</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">):</span>
<span class="k">continue</span>
<span class="n">e_shapes</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="n">e_shapes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">])</span>
<span class="n">gamma_div</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">w_max</span><span class="p">)</span>
<span class="n">e_N</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">r_name</span> <span class="ow">in</span> <span class="n">obs1</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="k">if</span> <span class="n">r_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</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="k">continue</span>
<span class="n">gamma_div</span> <span class="o">+=</span> <span class="n">calc_gamma</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">obs2</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">r_name</span><span class="p">]),</span> <span class="n">obs1</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">idl</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">],</span> <span class="n">w_max</span><span class="p">)</span>
<span class="n">e_N</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="n">idl_d</span><span class="p">[</span><span class="n">r_name</span><span class="p">]))</span>
<span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">/=</span> <span class="n">gamma_div</span><span class="p">[:</span><span class="n">w_max</span><span class="p">]</span>
<span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][:</span><span class="n">w_max</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(([</span><span class="mf">0.5</span><span class="p">],</span> <span class="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">1</span><span class="p">:])))</span>
<span class="c1"># Make sure no entry of tauint is smaller than 0.5</span>
<span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.500000000001</span>
<span class="n">window</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">],</span> <span class="n">obs2</span><span class="o">.</span><span class="n">e_windowsize</span><span class="p">[</span><span class="n">e_name</span><span class="p">])</span>
<span class="c1"># Bias correction hep-lat/0306017 eq. (49)</span>
<span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="n">e_n_tauint</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">window</span><span class="p">]</span> <span class="o">+</span> <span class="n">obs1</span><span class="o">.</span><span class="n">tau_exp</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</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="n">e_rho</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="n">window</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]))</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">window</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="n">e_N</span><span class="p">)</span> <span class="o">*</span> <span class="n">e_gamma</span><span class="p">[</span><span class="n">e_name</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">e_N</span>
<span class="n">dvalue</span> <span class="o">+=</span> <span class="n">e_dvalue</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span>
<span class="k">for</span> <span class="n">e_name</span> <span class="ow">in</span> <span class="n">obs1</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="k">if</span> <span class="n">e_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">obs2</span><span class="o">.</span><span class="n">cov_names</span><span class="p">:</span>
<span class="k">continue</span>
<span class="n">dvalue</span> <span class="o">+=</span> <span class="nb">float</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">obs1</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">cov</span><span class="p">,</span> <span class="n">obs2</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">e_name</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span><span class="p">)))</span>
<span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs1</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs2</span><span class="o">.</span><span class="n">dvalue</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mf">1.0</span><span class="p">:</span>
<span class="n">dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="n">dvalue</span><span class="p">)</span> <span class="o">*</span> <span class="n">obs1</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">*</span> <span class="n">obs2</span><span class="o">.</span><span class="n">dvalue</span>
<span class="k">if</span> <span class="n">correlation</span><span class="p">:</span>
<span class="n">dvalue</span> <span class="o">=</span> <span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs1</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">/</span> <span class="n">obs2</span><span class="o">.</span><span class="n">dvalue</span>
<span class="k">return</span> <span class="n">dvalue</span>
</pre></div>
</details>
<div class="docstring"><p>Calculates the covariance of two observables.</p>
<p>covariance(obs, obs) is equal to obs.dvalue ** 2
The gamma method has to be applied first to both observables.</p>
<p>If abs(covariance(obs1, obs2)) &gt; obs1.dvalue * obs2.dvalue, the covariance
is constrained to the maximum value.</p>
<h6 id="keyword-arguments">Keyword arguments</h6>
<p>correlation -- if true the correlation instead of the covariance is
returned (default False)</p>
</div>
</section>
<section id="import_jackknife">
<div class="attr function"><a class="headerlink" href="#import_jackknife">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">import_jackknife</span><span class="signature">(jacks, name, idl=None)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">import_jackknife</span><span class="p">(</span><span class="n">jacks</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Imports jackknife samples and returns an Obs</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> jacks : numpy.ndarray</span>
<span class="sd"> numpy array containing the mean value as zeroth entry and</span>
<span class="sd"> the N jackknife samples as first to Nth entry.</span>
<span class="sd"> name : str</span>
<span class="sd"> name of the ensemble the samples are defined on.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">jacks</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span>
<span class="n">prj</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="n">length</span><span class="p">,</span> <span class="n">length</span><span class="p">))</span> <span class="o">-</span> <span class="p">(</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">identity</span><span class="p">(</span><span class="n">length</span><span class="p">))</span>
<span class="n">samples</span> <span class="o">=</span> <span class="n">jacks</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span> <span class="o">@</span> <span class="n">prj</span>
<span class="n">new_obs</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([</span><span class="n">samples</span><span class="p">],</span> <span class="p">[</span><span class="n">name</span><span class="p">],</span> <span class="n">idl</span><span class="o">=</span><span class="n">idl</span><span class="p">)</span>
<span class="n">new_obs</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="n">jacks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">return</span> <span class="n">new_obs</span>
</pre></div>
</details>
<div class="docstring"><p>Imports jackknife samples and returns an Obs</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>jacks</strong> (numpy.ndarray):
numpy array containing the mean value as zeroth entry and
the N jackknife samples as first to Nth entry.</li>
<li><strong>name</strong> (str):
name of the ensemble the samples are defined on.</li>
</ul>
</div>
</section>
<section id="merge_obs">
<div class="attr function"><a class="headerlink" href="#merge_obs">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">merge_obs</span><span class="signature">(list_of_obs)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">merge_obs</span><span class="p">(</span><span class="n">list_of_obs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Combine all observables in list_of_obs into one new observable</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> list_of_obs : list</span>
<span class="sd"> list of the Obs object to be combined</span>
<span class="sd"> It is not possible to combine obs which are based on the same replicum</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">replist</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span> <span class="k">for</span> <span class="n">obs</span> <span class="ow">in</span> <span class="n">list_of_obs</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">obs</span><span class="o">.</span><span class="n">names</span><span class="p">]</span>
<span class="k">if</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">replist</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">replist</span><span class="p">)))</span> <span class="ow">is</span> <span class="kc">False</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;list_of_obs contains duplicate replica: </span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">replist</span><span class="p">)))</span>
<span class="k">if</span> <span class="nb">any</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">cov_names</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">]):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Not possible to merge data that contains covobs!&#39;</span><span class="p">)</span>
<span class="n">new_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">idl_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">:</span>
<span class="n">new_dict</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="n">key</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="o">+</span> <span class="n">o</span><span class="o">.</span><span class="n">r_values</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="p">)</span> <span class="o">|</span> <span class="nb">set</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">r_values</span><span class="p">)})</span>
<span class="n">idl_dict</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="n">key</span><span class="p">:</span> <span class="n">o</span><span class="o">.</span><span class="n">idl</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">deltas</span><span class="p">)})</span>
<span class="n">names</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">new_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
<span class="n">o</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([</span><span class="n">new_dict</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">names</span><span class="p">],</span> <span class="n">names</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="p">[</span><span class="n">idl_dict</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">names</span><span class="p">])</span>
<span class="n">o</span><span class="o">.</span><span class="n">is_merged</span> <span class="o">=</span> <span class="p">{</span><span class="n">name</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">any</span><span class="p">([</span><span class="n">oi</span><span class="o">.</span><span class="n">is_merged</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="k">for</span> <span class="n">oi</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">])</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">o</span><span class="o">.</span><span class="n">names</span><span class="p">}</span>
<span class="n">o</span><span class="o">.</span><span class="n">reweighted</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">([</span><span class="n">oi</span><span class="o">.</span><span class="n">reweighted</span> <span class="k">for</span> <span class="n">oi</span> <span class="ow">in</span> <span class="n">list_of_obs</span><span class="p">])</span>
<span class="k">return</span> <span class="n">o</span>
</pre></div>
</details>
<div class="docstring"><p>Combine all observables in list_of_obs into one new observable</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>list_of_obs</strong> (list):
list of the Obs object to be combined</li>
<li><strong>It is not possible to combine obs which are based on the same replicum</strong></li>
</ul>
</div>
</section>
<section id="cov_Obs">
<div class="attr function"><a class="headerlink" href="#cov_Obs">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">cov_Obs</span><span class="signature">(means, cov, name, grad=None)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">cov_Obs</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="n">cov</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">grad</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Create an Obs based on mean(s) and a covariance matrix</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> mean : list of floats or float</span>
<span class="sd"> N mean value(s) of the new Obs</span>
<span class="sd"> cov : list or array</span>
<span class="sd"> 2d (NxN) Covariance matrix, 1d diagonal entries or 0d covariance</span>
<span class="sd"> name : str</span>
<span class="sd"> identifier for the covariance matrix</span>
<span class="sd"> grad : list or array</span>
<span class="sd"> Gradient of the Covobs wrt. the means belonging to cov.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">covobs_to_obs</span><span class="p">(</span><span class="n">co</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Make an Obs out of a Covobs</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> co : Covobs</span>
<span class="sd"> Covobs to be embedded into the Obs</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">o</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">([],</span> <span class="p">[])</span>
<span class="n">o</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="n">co</span><span class="o">.</span><span class="n">value</span>
<span class="n">o</span><span class="o">.</span><span class="n">names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">co</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
<span class="n">o</span><span class="o">.</span><span class="n">_covobs</span><span class="p">[</span><span class="n">co</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">co</span>
<span class="n">o</span><span class="o">.</span><span class="n">_dvalue</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">co</span><span class="o">.</span><span class="n">errsq</span><span class="p">())</span>
<span class="k">return</span> <span class="n">o</span>
<span class="n">ol</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="p">(</span><span class="nb">float</span><span class="p">,</span> <span class="nb">int</span><span class="p">)):</span>
<span class="n">means</span> <span class="o">=</span> <span class="p">[</span><span class="n">means</span><span class="p">]</span>
<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="nb">len</span><span class="p">(</span><span class="n">means</span><span class="p">)):</span>
<span class="n">ol</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">covobs_to_obs</span><span class="p">(</span><span class="n">Covobs</span><span class="p">(</span><span class="n">means</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">cov</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">pos</span><span class="o">=</span><span class="n">i</span><span class="p">,</span> <span class="n">grad</span><span class="o">=</span><span class="n">grad</span><span class="p">)))</span>
<span class="k">if</span> <span class="n">ol</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">covobs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">N</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">means</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;You have to provide </span><span class="si">%d</span><span class="s1"> mean values!&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">ol</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">N</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ol</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">return</span> <span class="n">ol</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">return</span> <span class="n">ol</span>
</pre></div>
</details>
<div class="docstring"><p>Create an Obs based on mean(s) and a covariance matrix</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>mean</strong> (list of floats or float):
N mean value(s) of the new Obs</li>
<li><strong>cov</strong> (list or array):
2d (NxN) Covariance matrix, 1d diagonal entries or 0d covariance</li>
<li><strong>name</strong> (str):
identifier for the covariance matrix</li>
<li><strong>grad</strong> (list or array):
Gradient of the Covobs wrt. the means belonging to cov.</li>
</ul>
</div>
</section>
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