lattice/pyerrors
1
0
Fork 0
mirror of https://github.com/fjosw/pyerrors.git synced 2025-05-15 12:03:42 +02:00
Code Issues Projects Releases Packages Wiki Activity

Documentation updated

Browse source
This commit is contained in:
fjosw 2023-01-24 13:10:49 +00:00
parent 29ff03442b
commit cdd465c116
2 changed files with 3 additions and 3 deletions
Download patch file Download diff file Expand all files Collapse all files

4
docs/pyerrors.html
View file

@ -153,7 +153,7 @@ It is based on the gamma method <a href="https://arxiv.org/abs/hep-lat/0306017">
<p><code><a href="">pyerrors</a></code> introduces a new datatype, <code>Obs</code>, which simplifies error propagation and estimation for auto- and cross-correlated data. <p><code><a href="">pyerrors</a></code> introduces a new datatype, <code>Obs</code>, which simplifies error propagation and estimation for auto- and cross-correlated data.
An <code>Obs</code> object can be initialized with two arguments, the first is a list containing the samples for an observable from a Monte Carlo chain. An <code>Obs</code> object can be initialized with two arguments, the first is a list containing the samples for an observable from a Monte Carlo chain.
The samples can either be provided as python list or as numpy array. The samples can either be provided as python list or as numpy array.
The second argument is a list containing the names of the respective Monte Carlo chains as strings. These strings uniquely identify a Monte Carlo chain/ensemble. <strong>It is crucial for the correct error propagation that observations from the same Monte Carlo history are labeled with the same name. See <a href="#Multiple-ensemblesreplica">Multiple ensembles/replica</a> for details.</strong></p> The second argument is a list containing the names of the respective Monte Carlo chains as strings. These strings uniquely identify a Monte Carlo chain/ensemble. <strong>It is crucial for the correct error propagation that observations from the same Monte Carlo history are labeled with the same name. See <a href="#multiple-ensemblesreplica">Multiple ensembles/replica</a> for details.</strong></p>
<div class="pdoc-code codehilite"> <div class="pdoc-code codehilite">
<pre><span></span><code><span class="kn">import</span> <span class="nn">pyerrors</span> <span class="k">as</span> <span class="nn">pe</span> <pre><span></span><code><span class="kn">import</span> <span class="nn">pyerrors</span> <span class="k">as</span> <span class="nn">pe</span>
@ -680,7 +680,7 @@ The following entries are optional:</li>
</span><span id="L-41"><a href="#L-41"><span class="linenos"> 41</span></a><span class="sd">`pyerrors` introduces a new datatype, `Obs`, which simplifies error propagation and estimation for auto- and cross-correlated data.</span> </span><span id="L-41"><a href="#L-41"><span class="linenos"> 41</span></a><span class="sd">`pyerrors` introduces a new datatype, `Obs`, which simplifies error propagation and estimation for auto- and cross-correlated data.</span>
</span><span id="L-42"><a href="#L-42"><span class="linenos"> 42</span></a><span class="sd">An `Obs` object can be initialized with two arguments, the first is a list containing the samples for an observable from a Monte Carlo chain.</span> </span><span id="L-42"><a href="#L-42"><span class="linenos"> 42</span></a><span class="sd">An `Obs` object can be initialized with two arguments, the first is a list containing the samples for an observable from a Monte Carlo chain.</span>
</span><span id="L-43"><a href="#L-43"><span class="linenos"> 43</span></a><span class="sd">The samples can either be provided as python list or as numpy array.</span> </span><span id="L-43"><a href="#L-43"><span class="linenos"> 43</span></a><span class="sd">The samples can either be provided as python list or as numpy array.</span>
</span><span id="L-44"><a href="#L-44"><span class="linenos"> 44</span></a><span class="sd">The second argument is a list containing the names of the respective Monte Carlo chains as strings. These strings uniquely identify a Monte Carlo chain/ensemble. **It is crucial for the correct error propagation that observations from the same Monte Carlo history are labeled with the same name. See [Multiple ensembles/replica](#Multiple-ensemblesreplica) for details.**</span> </span><span id="L-44"><a href="#L-44"><span class="linenos"> 44</span></a><span class="sd">The second argument is a list containing the names of the respective Monte Carlo chains as strings. These strings uniquely identify a Monte Carlo chain/ensemble. **It is crucial for the correct error propagation that observations from the same Monte Carlo history are labeled with the same name. See [Multiple ensembles/replica](#multiple-ensemblesreplica) for details.**</span>
</span><span id="L-45"><a href="#L-45"><span class="linenos"> 45</span></a> </span><span id="L-45"><a href="#L-45"><span class="linenos"> 45</span></a>
</span><span id="L-46"><a href="#L-46"><span class="linenos"> 46</span></a><span class="sd">```python</span> </span><span id="L-46"><a href="#L-46"><span class="linenos"> 46</span></a><span class="sd">```python</span>
</span><span id="L-47"><a href="#L-47"><span class="linenos"> 47</span></a><span class="sd">import pyerrors as pe</span> </span><span id="L-47"><a href="#L-47"><span class="linenos"> 47</span></a><span class="sd">import pyerrors as pe</span>

2
docs/search.js
View file

File diff suppressed because one or more lines are too long