Ensemble averages
Project description
enstat
Documentation: enstat.readthedocs.io
Overview
enstat is a library to facilitate the computation of ensemble averages (and their standard deviation and variance). The key feature is that a class stored the sum of the first and second statistical moments and the number of samples, such that adding a sample can be done trivially, while giving access to the mean etc. at all times.
Disclaimer
This library is free to use under the MIT license. Any additions are very much appreciated, in terms of suggested functionality, code, documentation, testimonials, word-of-mouth advertisement, etc. Bug reports or feature requests can be filed on GitHub. As always, the code comes with no guarantee. None of the developers can be held responsible for possible mistakes.
Download: .zip file | .tar.gz file.
(c - MIT) T.W.J. de Geus (Tom) | tom@geus.me | www.geus.me | github.com/tdegeus/enstat
Installation
Using conda
conda install -c conda-forge enstat
Using PyPi
pip install enstat
Change-log
v0.5.0
- [BREAKING CHANGE] Changing
shape
,size
,dtype
,first
,second
,norm
to properties rather than functions (now call without()
) - Adding
add_point
to array classes - [tests] Using unittest discover
- [docs] Using furo theme. Minor updates.
v0.4.1
- Enforcing shape to be a tuple (like in NumPy) (#14)
v0.4.0
- Simplifying namespace. Using opportunity to simplify class names
- Avoiding zero division warning
- Adding test with defaultdict
v0.3.1
- Return NaN when there is no data (before zero was returned)
- (style) Fixing pre-commit
- (style) Renaming "test" -> "tests"
- (style) Applying pre-commit
v0.3.0
- Adding mask option to
enstat.static.StaticNd
.
v0.2.0
- Adding size and shape methods.
- Various generalisations.
Project details
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