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41
docs/pyerrors/fits.html
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@ -262,6 +262,8 @@
<span class="sd"> This can take a while as the full correlation matrix</span>
<span class="sd"> has to be calculated (default False).</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> Based on the orthogonal distance regression module of scipy</span>
<span class="sd"> &#39;&#39;&#39;</span>
@ -681,9 +683,13 @@
<span class="k">def</span> <span class="nf">fit_lin</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="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Performs a linear fit to y = n + m * x and returns two Obs n, m.</span>
<span class="sd"> y has to be a list of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
<span class="sd"> x can either be a list of floats in which case no xerror is assumed, or</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> x : list</span>
<span class="sd"> Can either be a list of floats in which case no xerror is assumed, or</span>
<span class="sd"> a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</span>
<span class="sd"> y : list</span>
<span class="sd"> List of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
@ -701,7 +707,7 @@
<span class="k">def</span> <span class="nf">qqplot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">o_y</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">p</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Generates a quantile-quantile plot of the fit result which can be used to</span>
<span class="sd">&quot;&quot;&quot;Generates a quantile-quantile plot of the fit result which can be used to</span>
<span class="sd"> check if the residuals of the fit are gaussian distributed.</span>
<span class="sd"> &quot;&quot;&quot;</span>
@ -1119,6 +1125,8 @@ If True, a quantile-quantile plot of the fit result is generated (default False)
<span class="sd"> This can take a while as the full correlation matrix</span>
<span class="sd"> has to be calculated (default False).</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> Based on the orthogonal distance regression module of scipy</span>
<span class="sd"> &#39;&#39;&#39;</span>
@ -1294,8 +1302,11 @@ If true prints the expected chisquare which is
corrected by effects caused by correlated input data.
This can take a while as the full correlation matrix
has to be calculated (default False).</li>
<li><strong>Based on the orthogonal distance regression module of scipy</strong></li>
</ul>
<h6 id="notes">Notes</h6>
<p>Based on the orthogonal distance regression module of scipy</p>
</div>
@ -1313,9 +1324,13 @@ has to be calculated (default False).</li>
<div class="pdoc-code codehilite"><pre><span></span><span class="k">def</span> <span class="nf">fit_lin</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="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Performs a linear fit to y = n + m * x and returns two Obs n, m.</span>
<span class="sd"> y has to be a list of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
<span class="sd"> x can either be a list of floats in which case no xerror is assumed, or</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> x : list</span>
<span class="sd"> Can either be a list of floats in which case no xerror is assumed, or</span>
<span class="sd"> a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</span>
<span class="sd"> y : list</span>
<span class="sd"> List of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
@ -1336,9 +1351,15 @@ has to be calculated (default False).</li>
<div class="docstring"><p>Performs a linear fit to y = n + m * x and returns two Obs n, m.</p>
<p>y has to be a list of Obs, the dvalues of the Obs are used as yerror for the fit.
x can either be a list of floats in which case no xerror is assumed, or
a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>x</strong> (list):
Can either be a list of floats in which case no xerror is assumed, or
a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</li>
<li><strong>y</strong> (list):
List of Obs, the dvalues of the Obs are used as yerror for the fit.</li>
</ul>
</div>
@ -1354,7 +1375,7 @@ a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</p>
<details>
<summary>View Source</summary>
<div class="pdoc-code codehilite"><pre><span></span><span class="k">def</span> <span class="nf">qqplot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">o_y</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">p</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Generates a quantile-quantile plot of the fit result which can be used to</span>
<span class="sd">&quot;&quot;&quot;Generates a quantile-quantile plot of the fit result which can be used to</span>
<span class="sd"> check if the residuals of the fit are gaussian distributed.</span>
<span class="sd"> &quot;&quot;&quot;</span>

22
docs/pyerrors/obs.html
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@ -1611,6 +1611,8 @@
<span class="sd"> obs_b : Obs</span>
<span class="sd"> Second observable</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</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>
@ -1807,6 +1809,8 @@
<span class="sd"> list_of_obs : list</span>
<span class="sd"> list of the Obs object to be combined</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</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>
@ -4778,6 +4782,8 @@ on the configurations in obs[i].idl.</li>
<span class="sd"> obs_b : Obs</span>
<span class="sd"> Second observable</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</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>
@ -4821,10 +4827,13 @@ on the configurations in obs[i].idl.</li>
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>
<h6 id="notes">Notes</h6>
<p>Keep in mind to only correlate primary observables which have not been reweighted
yet. The reweighting has to be applied after correlating the observables.
Currently only works if ensembles are identical (this is not strictly necessary).</p>
</div>
@ -4987,6 +4996,8 @@ name of the ensemble the samples are defined on.</li>
<span class="sd"> list_of_obs : list</span>
<span class="sd"> list of the Obs object to be combined</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</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>
@ -5017,8 +5028,11 @@ name of the ensemble the samples are defined on.</li>
<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>
<h6 id="notes">Notes</h6>
<p>It is not possible to combine obs which are based on the same replicum</p>
</div>

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docs/search.js
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