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.