{ "info": { "author": "['Marion Neumann', 'Shan Huang', 'Daniel Marthaler', 'Kristian Kersting']", "author_email": "marion.neumann@uni-bonn.de.com,shan.huang@iais.fraunhofer.de,dan.marthaler@gmail.com,kristian.kersting@cs.tu-dortmund.de", "bugtrack_url": null, "classifiers": [], "description": "```\n Marion Neumann [m dot neumann at wustl dot edu]\n Daniel Marthaler [dan dot marthaler at gmail dot com]\n Shan Huang [schan dot huang at gmail dot com]\n Kristian Kersting [kristian dot kersting at cs dot tu-dortmund dot de]\n\n This file is part of pyGPs.\n The software package is released under the BSD 2-Clause (FreeBSD) License.\n\n Copyright (c) by\n Marion Neumann, Daniel Marthaler, Shan Huang & Kristian Kersting, 18/02/2014\n```\n\npyGPs is a Python library for Gaussian Process (GP) Regression and Classification.\nHere is an online [documentation](http://www-ai.cs.uni-dortmund.de/weblab/static/api_docs/pyGPs/), where you will find a comprehensive introduction to functionalities and demonstrations. You can also find the same doc locally in `/doc/build/html/index.html`. \n\nGenerally speaking, pyGPs is an object-oriented GPs implementation. The functionality follows roughly the gpml matlab implementation by Carl Edward Rasmussen and Hannes Nickisch (Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2013-01-21). Standard GP regression and classification as well as FITC (sparse GPs) inference is implemented.\n\nFurther, pyGPs includes implementations of\n- minimize.py implemented in python by Roland Memisevic 2008, following minimize.m which is copyright (C) 1999 - 2006, Carl Edward Rasmussen\n- scg.py (Copyright (c) Ian T Nabney (1996-2001))\n- brentmin.py (Copyright (c) by Hannes Nickisch 2010-01-10.)\n\nFinally, pyGPs is constantly maintained. If you feel you have some relevant skills and are interested in contributing then please do get in touch. We appreciate any feedback.\n\nInstalling pyGPs\n------------------\nYou can install via pip (**Recommended!**):\n \n pip install pyGPs \n\nAlternatively, download the archive and extract it to any local directory. \nInstall the package using setup.py:\n\n python setup.py install\n\nor add the local directory to your PYTHONPATH:\n\n export PYTHONPATH=$PYTHONPATH:/path/to/local/directory/../parent_folder_of_pyGPs\n\nRequirements\n--------------\n- python 2.6 or 2.7 or *NEW:* python 3\n- scipy (v0.13.0 or later), numpy, and matplotlib: open-source packages for scientific computing using the Python programming language. \n\n\nAcknowledgements\n--------------\nThe following persons helped to improve this software: Roman Garnett, Maciej Kurek, Hannes Nickisch, Zhao Xu, and Alejandro Molina.\n\nThis work is partly supported by the Fraunhofer ATTRACT fellowship STREAM.\n\nCitation\n-------------\nTo cite pyGps, please use the following BibTex:\n```\n@article{JMLR:v16:neumann15a,\n author = {Marion Neumann and Shan Huang and Daniel E. Marthaler and Kristian Kersting},\n title = {pyGPs -- A Python Library for Gaussian Process Regression and Classification},\n journal = {Journal of Machine Learning Research},\n year = {2015},\n volume = {16},\n pages = {2611-2616},\n url = {http://jmlr.org/papers/v16/neumann15a.html}\n}\n```", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/marionmari/pyGPs", "keywords": null, "license": "COPYRIGHT.txt", "maintainer": null, "maintainer_email": null, "name": "pyGPs", "package_url": "https://pypi.org/project/pyGPs/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/pyGPs/", "project_urls": { "Download": "UNKNOWN", "Homepage": "https://github.com/marionmari/pyGPs" }, "release_url": "https://pypi.org/project/pyGPs/1.3.5/", "requires_dist": null, "requires_python": null, "summary": "Gaussian Processes for Regression and Classification", "version": "1.3.5" }, "last_serial": 2888692, "releases": { "1.2": [], "1.3.1": [ { "comment_text": "", "digests": { "md5": "db9081b35285cc50341392faeb468ac7", "sha256": "a29ab0e0f858482b0d971416c2adc9ddc3aec480a841466180697a8420449873" }, "downloads": -1, "filename": "pyGPs-1.3.1.tar.gz", "has_sig": false, "md5_digest": "db9081b35285cc50341392faeb468ac7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10286438, "upload_time": "2014-12-05T00:59:13", "url": "https://files.pythonhosted.org/packages/62/03/d2cc08324867b9a5c51cae085ebd04020863f0661a4a713be7d092b45057/pyGPs-1.3.1.tar.gz" } ], "1.3.2": [ { "comment_text": "", "digests": { "md5": "0e73d512f4d8edda389c76d4cb4aa727", "sha256": "4dc6a97464cbd88dc45893b63eda8390877d4aea00f41c76c9130033eacc09af" }, "downloads": -1, "filename": "pyGPs-1.3.2.tar.gz", "has_sig": false, "md5_digest": "0e73d512f4d8edda389c76d4cb4aa727", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10286629, "upload_time": "2015-01-17T22:09:26", "url": "https://files.pythonhosted.org/packages/11/17/4363c19c14534daeb5e124367d32d4c7ac9763bf8dfbf3acbae01ea97d2b/pyGPs-1.3.2.tar.gz" } ], "1.3.3": [ { "comment_text": "", "digests": { "md5": "b203dbd2223db1c2862023a8c3c8a2ce", "sha256": "f3b8042c54f211b8b77b7a322ddf384993fb42520d5c5a18a8a62980f696ba50" }, "downloads": -1, "filename": "pyGPs-1.3.3.tar.gz", "has_sig": false, "md5_digest": "b203dbd2223db1c2862023a8c3c8a2ce", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10291558, "upload_time": "2016-09-12T17:35:12", "url": "https://files.pythonhosted.org/packages/12/68/04ad4cbf5df7a1de8407719abc1eb1a1ae92b23572c9ead1642d90f77d66/pyGPs-1.3.3.tar.gz" } ], "1.3.4": [ { "comment_text": "", "digests": { "md5": "f79dfb6122fc03db210347a658fdbf3b", "sha256": "953daec618ff3aa4b877f505d459705728c4afa5982b85eb28f7ddd39e7ba4a4" }, "downloads": -1, "filename": "pyGPs-1.3.4.tar.gz", "has_sig": false, "md5_digest": "f79dfb6122fc03db210347a658fdbf3b", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10293934, "upload_time": "2017-03-08T15:07:00", "url": "https://files.pythonhosted.org/packages/31/03/85992200472cc13f007b2febe9b25f2a66a739f474f47dc544eff26c114b/pyGPs-1.3.4.tar.gz" } ], "1.3.5": [ { "comment_text": "", "digests": { "md5": "7bdc6fc01ae29812d24f4ced69cf7a18", "sha256": "5af668415a7bf1666c7c6da3bb09d29e48c395862c6feb23964b476972a015d4" }, "downloads": -1, "filename": "pyGPs-1.3.5.tar.gz", "has_sig": false, "md5_digest": "7bdc6fc01ae29812d24f4ced69cf7a18", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10294336, "upload_time": "2017-05-21T11:29:51", "url": "https://files.pythonhosted.org/packages/05/68/90138cccbdd5aa95b69761d4b3ef7d90594094c574c0696a09af64a6e3c1/pyGPs-1.3.5.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "7bdc6fc01ae29812d24f4ced69cf7a18", "sha256": "5af668415a7bf1666c7c6da3bb09d29e48c395862c6feb23964b476972a015d4" }, "downloads": -1, "filename": "pyGPs-1.3.5.tar.gz", "has_sig": false, "md5_digest": "7bdc6fc01ae29812d24f4ced69cf7a18", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10294336, "upload_time": "2017-05-21T11:29:51", "url": "https://files.pythonhosted.org/packages/05/68/90138cccbdd5aa95b69761d4b3ef7d90594094c574c0696a09af64a6e3c1/pyGPs-1.3.5.tar.gz" } ] }