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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"> a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</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>
@ -701,8 +707,8 @@
<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"> check if the residuals of the fit are gaussian distributed.</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>
<span class="n">residuals</span> <span class="o">=</span> <span class="p">[]</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"> a list of Obs, where the dvalues of the Obs are used as xerror for the fit.</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>
@ -1354,8 +1375,8 @@ 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"> check if the residuals of the fit are gaussian distributed.</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>
<span class="n">residuals</span> <span class="o">=</span> <span class="p">[]</span>