This package facilitates the creation and manipulation of arbitrarily complicated (correlated) multi-dimensional Gaussian random variables. The random variables are represented by a new data type (gvar.GVar
) that can be used in arithmetic expressions and pure Python functions. Such expressions/functions create new Gaussian random variables while automatically tracking statistical correlations between the new and old variables. This data type is useful for simple error propagation, but also is heavily used by the Bayesian least-squares fitting module lsqfit.py
to define priors and specify fit results, while accounting for correlations between all variables. Documentation can is in the doc/
subdirectory: see doc/html/index.html
or look online at <https://gvar.readthedocs.io>.
These packages use numpy
for efficient array arithmetic, and cython
to compile efficient code. gvar
uses automatic differentiation to track covariances through arbitrary arithmetic.
Information on how to install the components is in the INSTALLATION
file.
To test the libraries try make tests
. Some examples are give in the examples/
subdirectory.
gvar
version numbers have the form major.minor.patch
where: incompatible changes are signaled by incrementing the major
version number, the minor
number signals new features, and the patch
number signals bug fixes.
Copyright (c) 2008-2020 G. Peter Lepage