{ "info": { "author": "Adrian Buerger", "author_email": "adrian.buerger@hs-karlsruhe.de", "bugtrack_url": null, "classifiers": [], "description": "PECas 0.5.1\n===========\n\nParameter estimation using CasADi\n---------------------------------\n\n|travis| |coverall| |rtd|\n\n.. |travis| image:: https://travis-ci.org/adbuerger/PECas.svg?branch=master\n :target: https://travis-ci.org/adbuerger/PECas\n :alt: Travis CI build status master branch\n\n.. |coverall| image:: https://coveralls.io/repos/adbuerger/PECas/badge.svg?branch=master&service=github\n :target: https://coveralls.io/github/adbuerger/PECas?branch=master\n :alt: Coverage Status\n\n.. |rtd| image:: https://readthedocs.org/projects/pecas/badge/?version=latest\n :target: http://pecas.readthedocs.org/en/latest/?badge=latest\n :alt: Documentation Status\n\nPECas holds a user-friendly environment for solving parameter estimation problems and for interpretation of the results recieved. It does so by providing Python classes that can be initialized with the problem specifications, while the computations can then easily be performed by using the available class functions.\n\n**Please note:** as it's name suggests, PECas makes use of the optimization framework `CasADi `_ to solve parameter estimation problems. For PECas to work, you need CasADi version >= 2.4.0-rc2 to be installed on your system, otherwise the installation will abort.\n\nPECas is still in it's testing state, and does not yet contain all the features it will provide in future versions. Therefore, you should check for updates on a regular basis.\n\nFor an installation guide, a tutorial on how to use PECas and a detailed documentation, please visit `the manual pages `_ .", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://github.com/adbuerger/PECas/", "keywords": "", "license": "LGPL", "maintainer": "", "maintainer_email": "", "name": "pecas", "package_url": "https://pypi.org/project/pecas/", "platform": "Linux,Windows", "project_url": "https://pypi.org/project/pecas/", "project_urls": { "Homepage": "http://github.com/adbuerger/PECas/" }, "release_url": "https://pypi.org/project/pecas/0.5.1/", "requires_dist": null, "requires_python": "", "summary": "Parameter estimation using CasADi", "version": "0.5.1" }, "last_serial": 1811722, "releases": { "0.5": [ { "comment_text": "", "digests": { "md5": "6a1285acb23b520443119e20ac4f3efc", "sha256": "4317a7a83ba5c4c31b670c8ed194da03554af61a40d4dc58f33f8d38381b1beb" }, "downloads": -1, "filename": "pecas-0.5.tar.gz", "has_sig": false, "md5_digest": "6a1285acb23b520443119e20ac4f3efc", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 20019, "upload_time": "2015-11-10T17:05:29", "url": "https://files.pythonhosted.org/packages/f7/47/eea5c2c7247005031213de3d5ae48b4e35b343d7c3fd17b78c1763d0106c/pecas-0.5.tar.gz" } ], "0.5.1": [ { "comment_text": "", "digests": { "md5": "b3a6a14e61a8a552014411eb591c37e3", "sha256": "ff90a7a7398da5eaa887ff8c4909e22db6bc9bee2ec66570b0c8faf49a37a8ac" }, "downloads": -1, "filename": "pecas-0.5.1.tar.gz", "has_sig": false, "md5_digest": "b3a6a14e61a8a552014411eb591c37e3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 20847, "upload_time": "2015-11-11T15:59:41", "url": "https://files.pythonhosted.org/packages/ca/3d/9b00dca60da669e5aed340dc951b882585d1e86c4cfa29d64e7cc3c2b704/pecas-0.5.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "b3a6a14e61a8a552014411eb591c37e3", "sha256": "ff90a7a7398da5eaa887ff8c4909e22db6bc9bee2ec66570b0c8faf49a37a8ac" }, "downloads": -1, "filename": "pecas-0.5.1.tar.gz", "has_sig": false, "md5_digest": "b3a6a14e61a8a552014411eb591c37e3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 20847, "upload_time": "2015-11-11T15:59:41", "url": "https://files.pythonhosted.org/packages/ca/3d/9b00dca60da669e5aed340dc951b882585d1e86c4cfa29d64e7cc3c2b704/pecas-0.5.1.tar.gz" } ] }