{ "info": { "author": "David Dotson", "author_email": "dotsdl@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Programming Language :: Python", "Topic :: Scientific/Engineering" ], "description": "alchemlyb: the simple alchemistry library\n=========================================\n\n|doi| |docs| |build| |cov|\n\n**Warning**: This library is young. It is **not** API stable. It is a\nnucleation point. By all means use and help improve it, but note that it will\nchange with time.\n\n**alchemlyb** is an attempt to make alchemical free energy calculations easier\nto do by leveraging the full power and flexibility of the PyData stack. It\nincludes: \n\n1. Parsers for extracting raw data from output files of common molecular\n dynamics engines such as GROMACS [Abraham2015]_. \n\n2. Subsamplers for obtaining uncorrelated samples from timeseries data.\n\n3. Estimators for obtaining free energies directly from this data, using\n best-practices approaches for multistate Bennett acceptance ratio (MBAR)\n [Shirts2008]_ and thermodynamic integration (TI).\n\nIn particular, it uses internally the excellent `pymbar\n`_ library for performing MBAR and extracting\nindependent, equilibrated samples [Chodera2016]_.\n\n.. [Abraham2015] Abraham, M.J., Murtola, T., Schulz, R., P\u00e1ll, S., Smith, J.C.,\n Hess, B., and Lindahl, E. (2015). GROMACS: High performance molecular\n simulations through multi-level parallelism from laptops to supercomputers.\n SoftwareX 1\u20132, 19\u201325.\n\n.. [Shirts2008] Shirts, M.R., and Chodera, J.D. (2008). Statistically optimal\n analysis of samples from multiple equilibrium states. The Journal of Chemical\n Physics 129, 124105.\n\n.. [Chodera2016] Chodera, J.D. (2016). A Simple Method for Automated\n Equilibration Detection in Molecular Simulations. Journal of Chemical Theory\n and Computation 12, 1799\u20131805.\n\n.. |doi| image:: https://zenodo.org/badge/68669096.svg\n :alt: Zenodo DOI\n :scale: 100%\n :target: https://zenodo.org/badge/latestdoi/68669096\n\n.. |docs| image:: https://readthedocs.org/projects/alchemlyb/badge/?version=latest\n :alt: Documentation\n :scale: 100%\n :target: http://alchemlyb.readthedocs.io/en/latest/\n\n.. |build| image:: https://travis-ci.org/alchemistry/alchemlyb.svg?branch=master\n :alt: Build Status\n :scale: 100%\n :target: https://travis-ci.org/alchemistry/alchemlyb\n\n.. |cov| image:: https://codecov.io/gh/alchemistry/alchemlyb/branch/master/graph/badge.svg\n :alt: Code coverage\n :scale: 100%\n :target: https://codecov.io/gh/alchemistry/alchemlyb\n\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "", "keywords": "", "license": "BSD", "maintainer": "", "maintainer_email": "", "name": "alchemlyb", "package_url": "https://pypi.org/project/alchemlyb/", "platform": "", "project_url": "https://pypi.org/project/alchemlyb/", "project_urls": null, "release_url": "https://pypi.org/project/alchemlyb/0.3.0/", "requires_dist": [ "numpy", "pandas (>=0.23.0)", "pymbar", "scipy", "scikit-learn" ], "requires_python": "", "summary": "the simple alchemistry library", "version": "0.3.0" }, "last_serial": 5637489, "releases": { "0.1.0": [ { "comment_text": "", "digests": { "md5": "661020613f06249c8dd53fc3e1cde5bb", "sha256": "c608432dd8e9dafdeaf1e2bee2714b715110a57af7e05432cbca3325d7e2ee20" }, "downloads": -1, "filename": "alchemlyb-0.1.0-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "661020613f06249c8dd53fc3e1cde5bb", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 15965, "upload_time": "2017-05-27T07:04:36", "url": "https://files.pythonhosted.org/packages/55/e5/d24be00aeb419a8afe13f43a334d21f81a7336eb7735c71ddda7039f4ad5/alchemlyb-0.1.0-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "36285800f44fe9a089c8619088ca0565", "sha256": "71396b7b461413e5d1ed5f7d09ae9b5854be12672f91f3be0210fc776cbb5fac" }, "downloads": -1, "filename": "alchemlyb-0.1.0.tar.gz", "has_sig": false, "md5_digest": "36285800f44fe9a089c8619088ca0565", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11848, "upload_time": "2017-05-27T07:04:38", "url": "https://files.pythonhosted.org/packages/2c/b4/c7f46dc579644fbf7081fe7daa78998712caac58f2a526c72aa701e3ad33/alchemlyb-0.1.0.tar.gz" } ], "0.1.0a0": [ { "comment_text": "", "digests": { "md5": "de4ee31708c2367bfb869cb5372c49b3", "sha256": "2db6a17662167881bad7cd9ef0f587e1ec2327627b727867910eb35ab54d1da6" }, "downloads": -1, "filename": "alchemlyb-0.1.0a0.tar.gz", "has_sig": false, "md5_digest": "de4ee31708c2367bfb869cb5372c49b3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6485, "upload_time": "2017-02-20T03:40:17", "url": "https://files.pythonhosted.org/packages/4f/7d/f6473227c0412b3a244ad47ee7838a2316ca627b4a23ac101b0c29bf5175/alchemlyb-0.1.0a0.tar.gz" } ], "0.3.0": [ { "comment_text": "", "digests": { "md5": "3b626b7ce7b398e454d54edc6dee5161", "sha256": "9770890f54df29999bab2c555fabd7e160d80d1e3994e6e415add4add940e8ce" }, "downloads": -1, "filename": "alchemlyb-0.3.0-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "3b626b7ce7b398e454d54edc6dee5161", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 34162, "upload_time": "2019-08-06T03:54:04", "url": "https://files.pythonhosted.org/packages/bf/a8/0311a5843ff73479cc8e27b8118e19212b600c622ffd7c55d3b488ce4a41/alchemlyb-0.3.0-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "2386f06c4302511c9ec91ff0d2d2a713", "sha256": "9dad60521dab1fde7efae8a9c6b861a23d69f40c4202592af0b910a86033269c" }, "downloads": -1, "filename": "alchemlyb-0.3.0.tar.gz", "has_sig": false, "md5_digest": "2386f06c4302511c9ec91ff0d2d2a713", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 39681, "upload_time": "2019-08-06T03:54:06", "url": "https://files.pythonhosted.org/packages/1b/1e/160b58c9decdda568c9c6128ff6d00093d7c659d7e47277dc7f3182a66fb/alchemlyb-0.3.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "3b626b7ce7b398e454d54edc6dee5161", "sha256": "9770890f54df29999bab2c555fabd7e160d80d1e3994e6e415add4add940e8ce" }, "downloads": -1, "filename": "alchemlyb-0.3.0-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "3b626b7ce7b398e454d54edc6dee5161", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 34162, "upload_time": "2019-08-06T03:54:04", "url": "https://files.pythonhosted.org/packages/bf/a8/0311a5843ff73479cc8e27b8118e19212b600c622ffd7c55d3b488ce4a41/alchemlyb-0.3.0-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "2386f06c4302511c9ec91ff0d2d2a713", "sha256": "9dad60521dab1fde7efae8a9c6b861a23d69f40c4202592af0b910a86033269c" }, "downloads": -1, "filename": "alchemlyb-0.3.0.tar.gz", "has_sig": false, "md5_digest": "2386f06c4302511c9ec91ff0d2d2a713", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 39681, "upload_time": "2019-08-06T03:54:06", "url": "https://files.pythonhosted.org/packages/1b/1e/160b58c9decdda568c9c6128ff6d00093d7c659d7e47277dc7f3182a66fb/alchemlyb-0.3.0.tar.gz" } ] }