{ "info": { "author": "Daniel Foreman-Mackey and Jonathan Goodman", "author_email": "danfm@nyu.edu", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python" ], "description": "ACOR\n====\n\nThis is a direct port of a C++ routine by\n`Jonathan Goodman `_ (NYU)\ncalled `ACOR `_ that\nestimates the autocorrelation time of time series data very quickly.\n\n`Dan Foreman-Mackey `_ (NYU) made a few surface changes to\nthe interface in order to write a Python wrapper (with the permission of the\noriginal author).\n\nInstallation\n------------\n\nJust run ::\n\n pip install acor\n\nwith ``sudo`` if you really need it.\n\nOtherwise, download the source code\n`as a tarball `_\nor clone the git repository from `GitHub `_: ::\n\n git clone https://github.com/dfm/acor.git\n\nThen run ::\n\n cd acor\n python setup.py install\n\nto compile and install the module ``acor`` in your Python path. The only\ndependency is `NumPy `_ (including the\n``python-dev`` and ``python-numpy-dev`` packages which you might have to\ninstall separately on some systems).\n\nUsage\n-----\n\nGiven some time series ``x``, you can estimate the autocorrelation time\n(``tau``) using: ::\n\n import acor\n tau, mean, sigma = acor.acor(x)\n\nReferences\n----------\n\n* http://www.math.nyu.edu/faculty/goodman/software/acor/index.html\n* http://www.stat.unc.edu/faculty/cji/Sokal.pdf", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://github.com/dfm/acor", "keywords": null, "license": "MIT", "maintainer": null, "maintainer_email": null, "name": "acor", "package_url": "https://pypi.org/project/acor/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/acor/", "project_urls": { "Download": "UNKNOWN", "Homepage": "http://github.com/dfm/acor" }, "release_url": "https://pypi.org/project/acor/1.1.1/", "requires_dist": null, "requires_python": null, "summary": "Estimate the autocorrelation time of a time series quickly.", "version": "1.1.1" }, "last_serial": 1180942, "releases": { "1.0.0": [ { "comment_text": "", "digests": { "md5": "4e12022df7315c754809eaab45a28c83", "sha256": "7aebe81db3d0be139eef95f9ff854f986c4f156a8792e34f9b21167e5bebf167" }, "downloads": -1, "filename": "acor-1.0.0.tar.gz", "has_sig": false, "md5_digest": "4e12022df7315c754809eaab45a28c83", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 3892, "upload_time": "2012-02-02T04:21:31", "url": "https://files.pythonhosted.org/packages/d9/20/7741417fbef10d5c3fb9086628b072e6a65edaaff27dd54f962e819cad43/acor-1.0.0.tar.gz" } ], "1.0.1": [ { "comment_text": "", "digests": { "md5": "1df35fb4ad1d28e5a320b94f83a88bc1", "sha256": "ccaa5d68a98e1dbf377aafbcb6d3e7a542086f68fc9f5968b11ea81c84c21ce5" }, "downloads": -1, "filename": "acor-1.0.1.tar.gz", "has_sig": false, "md5_digest": "1df35fb4ad1d28e5a320b94f83a88bc1", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4541, "upload_time": "2012-06-08T00:32:11", "url": "https://files.pythonhosted.org/packages/f5/ba/c2ba4abea13fa7a364a028c0077c2b20bb5cd8d4197b0e6ae111f6bcf658/acor-1.0.1.tar.gz" } ], "1.0.2": [ { "comment_text": "", "digests": { "md5": "a63e6673f60fcc1dc817800367a6b887", "sha256": "8cf00629df6fc0f8004b07192f48bc187c2adabb4382c6ad1c01a37f5366e8ff" }, "downloads": -1, "filename": "acor-1.0.2.tar.gz", "has_sig": false, "md5_digest": "a63e6673f60fcc1dc817800367a6b887", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5445, "upload_time": "2012-06-08T17:37:15", "url": "https://files.pythonhosted.org/packages/95/6f/50b9ef78b9de8c45c66bf1980d097326d86f5b7cf79e21b226c21d7dde32/acor-1.0.2.tar.gz" } ], "1.1.0": [ { "comment_text": "", "digests": { "md5": "3f44b8d440d039de1bbfe8ba76b878de", "sha256": "f02201767b78439fb15cb582bfcd3bb6ada43ff7346f4949f0ba143b1bffa5d8" }, "downloads": -1, "filename": "acor-1.1.0.tar.gz", "has_sig": false, "md5_digest": "3f44b8d440d039de1bbfe8ba76b878de", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6235, "upload_time": "2014-01-03T18:28:08", "url": "https://files.pythonhosted.org/packages/f9/6d/6e702337d89e7adcb6a52ad77fa2b44b621853f60b241f6fe93c76a605c5/acor-1.1.0.tar.gz" } ], "1.1.1": [ { "comment_text": "", "digests": { "md5": "8681b949f50e0f9a02bfbd15f7a3d56c", "sha256": "4c647d30326004cfcfbcf630e97586ce574954e36bebf75b657d33d5d79e94e3" }, "downloads": -1, "filename": "acor-1.1.1.tar.gz", "has_sig": false, "md5_digest": "8681b949f50e0f9a02bfbd15f7a3d56c", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6122, "upload_time": "2014-08-05T18:19:47", "url": "https://files.pythonhosted.org/packages/d7/63/2f696a862e1687bd14a30b7319ec3fbe02ba78f80af43c32e999d0e7435a/acor-1.1.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "8681b949f50e0f9a02bfbd15f7a3d56c", "sha256": "4c647d30326004cfcfbcf630e97586ce574954e36bebf75b657d33d5d79e94e3" }, "downloads": -1, "filename": "acor-1.1.1.tar.gz", "has_sig": false, "md5_digest": "8681b949f50e0f9a02bfbd15f7a3d56c", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6122, "upload_time": "2014-08-05T18:19:47", "url": "https://files.pythonhosted.org/packages/d7/63/2f696a862e1687bd14a30b7319ec3fbe02ba78f80af43c32e999d0e7435a/acor-1.1.1.tar.gz" } ] }