Metadata-Version: 1.2
Name: alchemlyb
Version: 0.4.1
Summary: the simple alchemistry library
Home-page: UNKNOWN
Author: David Dotson
Author-email: dotsdl@gmail.com
Maintainer: Oliver Beckstein
Maintainer-email: orbeckst@gmail.com
License: BSD
Description: alchemlyb: the simple alchemistry library
        =========================================
        
        |doi| |docs| |build| |cov|
        
        **alchemlyb** makes alchemical free energy calculations easier to do
        by leveraging the full power and flexibility of the PyData stack. It
        includes:
        
        1. Parsers for extracting raw data from output files of common
           molecular dynamics engines such as `GROMACS`_, `AMBER`_, `NAMD`_
           and `other simulation codes`_.
        
        2. Subsamplers for obtaining uncorrelated samples from timeseries data.
        
        3. Estimators for obtaining free energies directly from this data, using
           best-practices approaches for multistate Bennett acceptance ratio (MBAR)
           [Shirts2008]_ and thermodynamic integration (TI).
        
        In particular, it uses internally the excellent `pymbar
        <http://pymbar.readthedocs.io/>`_ library for performing MBAR and extracting
        independent, equilibrated samples [Chodera2016]_.
        
        .. [Shirts2008] Shirts, M.R., and Chodera, J.D. (2008). Statistically optimal
            analysis of samples from multiple equilibrium states. The Journal of Chemical
            Physics 129, 124105.
        
        .. [Chodera2016] Chodera, J.D. (2016). A Simple Method for Automated
            Equilibration Detection in Molecular Simulations. Journal of Chemical Theory
            and Computation 12, 1799–1805.
        
        .. _GROMACS: http://www.gromacs.org/
        
        .. _AMBER: http://ambermd.org/
        
        .. _NAMD: http://www.ks.uiuc.edu/Research/namd/
        
        .. _`other simulation codes`: https://alchemlyb.readthedocs.io/en/latest/parsing.html
            
        .. |doi| image:: https://zenodo.org/badge/68669096.svg
            :alt: Zenodo DOI
            :scale: 100%
            :target: https://zenodo.org/badge/latestdoi/68669096
        
        .. |docs| image:: https://readthedocs.org/projects/alchemlyb/badge/?version=latest
            :alt: Documentation
            :scale: 100%
            :target: http://alchemlyb.readthedocs.io/en/latest/
        
        .. |build| image:: https://travis-ci.org/alchemistry/alchemlyb.svg?branch=master
            :alt: Build Status
            :scale: 100%
            :target: https://travis-ci.org/alchemistry/alchemlyb
        
        .. |cov| image:: https://codecov.io/gh/alchemistry/alchemlyb/branch/master/graph/badge.svg
            :alt: Code coverage
            :scale: 100%
            :target: https://codecov.io/gh/alchemistry/alchemlyb
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows 
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: C
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Software Development :: Libraries :: Python Modules
