{ "info": { "author": "F. B. Lalibert\u00e9", "author_email": "frederic.laliberte@utoronto.ca", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Natural Language :: English", "Programming Language :: Python :: 2.7", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "pyccm\n=====\n\nThis package computes the Convergent Cross Mapping described by\nSugihara et al., 2012: \"Detecting Causality in Complex Ecosystems\". Science 338: 496\u2013500\n\nThis code was adapted from https://github.com/cjbayesian/rccm by Corey Chivers.\n\nFrederic Laliberte, Univerity of Toronto, 2014\n\nThe Natural Sciences and Engineering Research Council of Canada (NSERC/CRSNG) funded \nFBL during this project.\n\nVersion History\n---------------\n\n0.4: The correlations are computed on the vector at lag 0. Note: this returns to the Sugihara et al. approach.\n Bug fixes with E>2\n\n0.3: The correlations are computed on the lagged vectors. Note: this departs from Sugihara et al.\n\n0.2: Added the capability of analyzing time series limited to a few months per year\n\n0.1: First version", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "UNKNOWN", "keywords": "time series", "license": "BSD", "maintainer": null, "maintainer_email": null, "name": "pyccm", "package_url": "https://pypi.org/project/pyccm/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/pyccm/", "project_urls": { "Download": "UNKNOWN", "Homepage": "UNKNOWN" }, "release_url": "https://pypi.org/project/pyccm/0.4/", "requires_dist": null, "requires_python": null, "summary": "Implementation of the Convergent Cross Mapping", "version": "0.4" }, "last_serial": 1471575, "releases": { "0.2": [ { "comment_text": "", "digests": { "md5": "f440257fe5d0720a9f2d9ceac0ce4319", "sha256": "7924719c304d54ba8da1c9bd4653cca9f44f498a3c94b97bf239cd74ad5e33df" }, "downloads": -1, "filename": "pyccm-0.2.tar.gz", "has_sig": false, "md5_digest": "f440257fe5d0720a9f2d9ceac0ce4319", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 3695, "upload_time": "2014-08-28T22:23:21", "url": "https://files.pythonhosted.org/packages/fb/9c/b14140f992e7af414cf6862cc01fcd1f8c95a0d0e7085ffb606e7c063bb7/pyccm-0.2.tar.gz" } ], "0.3": [ { "comment_text": "", "digests": { "md5": "03163ac48a417f4ebece87a17a3cccd0", "sha256": "7cfc47f81264a6a78b812dc7377e7e189ad82605b0c4d6f9ccaa583b8d3f1ffd" }, "downloads": -1, "filename": "pyccm-0.3.tar.gz", "has_sig": false, "md5_digest": "03163ac48a417f4ebece87a17a3cccd0", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4061, "upload_time": "2014-12-04T22:18:17", "url": "https://files.pythonhosted.org/packages/ae/d2/914e0ed85d7ae8b23295ddedab23948a8dc236d554674620874522c8d00e/pyccm-0.3.tar.gz" } ], "0.4": [ { "comment_text": "", "digests": { "md5": "981830fb3d3687aab27b96bcc623b976", "sha256": "ec1a08a62a6f8745bc87f1546e50892bc613f44e0ebae33ef63c4ad5de4fdc18" }, "downloads": -1, "filename": "pyccm-0.4.tar.gz", "has_sig": false, "md5_digest": "981830fb3d3687aab27b96bcc623b976", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5406, "upload_time": "2015-03-21T21:26:25", "url": "https://files.pythonhosted.org/packages/9e/59/8ac925de720f7cee84add14e41ef76ed483d058f2a4f034420f7a078146c/pyccm-0.4.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "981830fb3d3687aab27b96bcc623b976", "sha256": "ec1a08a62a6f8745bc87f1546e50892bc613f44e0ebae33ef63c4ad5de4fdc18" }, "downloads": -1, "filename": "pyccm-0.4.tar.gz", "has_sig": false, "md5_digest": "981830fb3d3687aab27b96bcc623b976", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5406, "upload_time": "2015-03-21T21:26:25", "url": "https://files.pythonhosted.org/packages/9e/59/8ac925de720f7cee84add14e41ef76ed483d058f2a4f034420f7a078146c/pyccm-0.4.tar.gz" } ] }