Metadata-Version: 1.1
Name: gvar
Version: 8.3.2
Summary: Utilities for manipulating correlated Gaussian random variables.
Home-page: https://github.com/gplepage/gvar.git
Author: G. Peter Lepage
Author-email: g.p.lepage@cornell.edu
License: GPLv3+
Description:     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 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).
        
            This package uses numpy for efficient array arithmetic, and cython to
            compile efficient core routines and interface code.
            
Platform: Any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Cython
Classifier: Topic :: Scientific/Engineering
Requires: cython (>=0.17)
Requires: numpy (>=1.7)
