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Documentation updated
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3 changed files with 54 additions and 19 deletions
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@ -262,6 +262,8 @@
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<span class="sd"> This can take a while as the full correlation matrix</span>
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<span class="sd"> has to be calculated (default False).</span>
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<span class="sd"> Notes</span>
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<span class="sd"> -----</span>
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<span class="sd"> Based on the orthogonal distance regression module of scipy</span>
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<span class="sd"> '''</span>
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@ -681,9 +683,13 @@
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<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>
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<span class="sd">"""Performs a linear fit to y = n + m * x and returns two Obs n, m.</span>
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<span class="sd"> y has to be a list of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
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<span class="sd"> x can either be a list of floats in which case no xerror is assumed, or</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> x : list</span>
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<span class="sd"> Can either be a list of floats in which case no xerror is assumed, or</span>
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<span class="sd"> a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</span>
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<span class="sd"> y : list</span>
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<span class="sd"> List of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
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<span class="sd"> """</span>
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<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>
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@ -701,7 +707,7 @@
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<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>
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<span class="sd">""" Generates a quantile-quantile plot of the fit result which can be used to</span>
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<span class="sd">"""Generates a quantile-quantile plot of the fit result which can be used to</span>
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<span class="sd"> check if the residuals of the fit are gaussian distributed.</span>
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<span class="sd"> """</span>
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@ -1119,6 +1125,8 @@ If True, a quantile-quantile plot of the fit result is generated (default False)
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<span class="sd"> This can take a while as the full correlation matrix</span>
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<span class="sd"> has to be calculated (default False).</span>
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<span class="sd"> Notes</span>
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<span class="sd"> -----</span>
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<span class="sd"> Based on the orthogonal distance regression module of scipy</span>
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<span class="sd"> '''</span>
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@ -1294,8 +1302,11 @@ If true prints the expected chisquare which is
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corrected by effects caused by correlated input data.
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This can take a while as the full correlation matrix
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has to be calculated (default False).</li>
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<li><strong>Based on the orthogonal distance regression module of scipy</strong></li>
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</ul>
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<h6 id="notes">Notes</h6>
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<p>Based on the orthogonal distance regression module of scipy</p>
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</div>
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@ -1313,9 +1324,13 @@ has to be calculated (default False).</li>
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<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>
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<span class="sd">"""Performs a linear fit to y = n + m * x and returns two Obs n, m.</span>
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<span class="sd"> y has to be a list of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
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<span class="sd"> x can either be a list of floats in which case no xerror is assumed, or</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> x : list</span>
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<span class="sd"> Can either be a list of floats in which case no xerror is assumed, or</span>
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<span class="sd"> a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</span>
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<span class="sd"> y : list</span>
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<span class="sd"> List of Obs, the dvalues of the Obs are used as yerror for the fit.</span>
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<span class="sd"> """</span>
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<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>
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@ -1336,9 +1351,15 @@ has to be calculated (default False).</li>
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<div class="docstring"><p>Performs a linear fit to y = n + m * x and returns two Obs n, m.</p>
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<p>y has to be a list of Obs, the dvalues of the Obs are used as yerror for the fit.
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x can either be a list of floats in which case no xerror is assumed, or
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a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</p>
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<h6 id="parameters">Parameters</h6>
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<ul>
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<li><strong>x</strong> (list):
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Can either be a list of floats in which case no xerror is assumed, or
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a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</li>
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<li><strong>y</strong> (list):
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List of Obs, the dvalues of the Obs are used as yerror for the fit.</li>
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</ul>
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</div>
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@ -1354,7 +1375,7 @@ a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</p>
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<details>
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<summary>View Source</summary>
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<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>
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<span class="sd">""" Generates a quantile-quantile plot of the fit result which can be used to</span>
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<span class="sd">"""Generates a quantile-quantile plot of the fit result which can be used to</span>
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<span class="sd"> check if the residuals of the fit are gaussian distributed.</span>
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<span class="sd"> """</span>
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@ -1611,6 +1611,8 @@
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<span class="sd"> obs_b : Obs</span>
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<span class="sd"> Second observable</span>
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<span class="sd"> Notes</span>
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<span class="sd"> -----</span>
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<span class="sd"> Keep in mind to only correlate primary observables which have not been reweighted</span>
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<span class="sd"> yet. The reweighting has to be applied after correlating the observables.</span>
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<span class="sd"> Currently only works if ensembles are identical (this is not strictly necessary).</span>
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@ -1807,6 +1809,8 @@
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<span class="sd"> list_of_obs : list</span>
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<span class="sd"> list of the Obs object to be combined</span>
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<span class="sd"> Notes</span>
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<span class="sd"> -----</span>
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<span class="sd"> It is not possible to combine obs which are based on the same replicum</span>
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<span class="sd"> """</span>
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<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>
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@ -4778,6 +4782,8 @@ on the configurations in obs[i].idl.</li>
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<span class="sd"> obs_b : Obs</span>
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<span class="sd"> Second observable</span>
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<span class="sd"> Notes</span>
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<span class="sd"> -----</span>
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<span class="sd"> Keep in mind to only correlate primary observables which have not been reweighted</span>
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<span class="sd"> yet. The reweighting has to be applied after correlating the observables.</span>
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<span class="sd"> Currently only works if ensembles are identical (this is not strictly necessary).</span>
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@ -4821,10 +4827,13 @@ on the configurations in obs[i].idl.</li>
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First observable</li>
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<li><strong>obs_b</strong> (Obs):
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Second observable</li>
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<li><strong>Keep in mind to only correlate primary observables which have not been reweighted</strong></li>
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<li><strong>yet. The reweighting has to be applied after correlating the observables.</strong></li>
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<li><strong>Currently only works if ensembles are identical (this is not strictly necessary).</strong></li>
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</ul>
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<h6 id="notes">Notes</h6>
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<p>Keep in mind to only correlate primary observables which have not been reweighted
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yet. The reweighting has to be applied after correlating the observables.
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Currently only works if ensembles are identical (this is not strictly necessary).</p>
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</div>
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@ -4987,6 +4996,8 @@ name of the ensemble the samples are defined on.</li>
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<span class="sd"> list_of_obs : list</span>
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<span class="sd"> list of the Obs object to be combined</span>
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<span class="sd"> Notes</span>
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<span class="sd"> -----</span>
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<span class="sd"> It is not possible to combine obs which are based on the same replicum</span>
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<span class="sd"> """</span>
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<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>
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@ -5017,8 +5028,11 @@ name of the ensemble the samples are defined on.</li>
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<ul>
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<li><strong>list_of_obs</strong> (list):
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list of the Obs object to be combined</li>
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<li><strong>It is not possible to combine obs which are based on the same replicum</strong></li>
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</ul>
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<h6 id="notes">Notes</h6>
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<p>It is not possible to combine obs which are based on the same replicum</p>
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</div>
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