{ "info": { "author": "Labex Archimede AMU", "author_email": "dominique.benielli@univ-amu.fr", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Natural Language :: English", "Operating System :: MacOS :: MacOS X", "Operating System :: POSIX :: Linux", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "This package, as well as the **IntertwiningWavelet**, ``iw`` toolbox, is Free software, released under BSD License.\n\nDocumentation is available on the public site at `intertwiningwavelet doc `_.\n\nThe latest version of **IntertwiningWavelet**, is available on the `gitlab repository `_ , which provides the git repository managing the source code and where issues can be reported.\n\nThe **IntertwiningWavelet** package is a Python Package for wavelet analysis on graphs.\nThis toolbox is dedicated to a method called IntertwiningWavelet (IW) which provides a multiresolution analysis on non oriented graphs. It provides a wavelet basis on a graph and can analyse a banch of signals defined on this graph. \n\nThe method is fully described and analysed in `Intertwining wavelets or Multiresolution analysis on graphs through random forests. `_, `Approximate and exact solutions of intertwining equations through random spanning forests. `_ and a quicker description can be found in `Random forests and Network analysis. `_. The approach relies on probabilistic tools: a random spanning forest to downsample the set of vertices, and approximate solutions of Markov intertwining relation to provide a subgraph structure and a filterbank which is a basis of the set of functions. As a by-product, the method provides a graph coarse-graining procedure.\n\nThe original ``iw`` Toolbox is developed in Python/Cython at `LabEx Archim\u00e8de `_ , as a `I2M `_ project.\n\n\nHistory\n=======\n\n0.0.0 (2018-02-15)\n------------------\nFirst version\n\n0.0.1 (2019-03-21)\n------------------\n-Fix bug inversion matrice lead to negatives values in the case of very small laplacian.\nComputation of Laplacian and Schur complement performs with interative method.\n\n-Fix Bug for decimation /nR\n\n-Fix bug for alpha == 0\n\n-multi signals extented\n\n0.0.6 (2019-09-13)\n------------------\n\nFix pypi deposit\n\n\n\nPeople\n------\n\n\n * Clothilde Melot\n\n * Alexandre Gaudilliere\n\n * Fabienne Castell \n\n * Dominique Benielli", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "", "keywords": "", "license": "new BSD", "maintainer": "", "maintainer_email": "", "name": "IntertwiningWavelet", "package_url": "https://pypi.org/project/IntertwiningWavelet/", "platform": "", "project_url": "https://pypi.org/project/IntertwiningWavelet/", "project_urls": null, "release_url": "https://pypi.org/project/IntertwiningWavelet/0.0.10/", "requires_dist": null, "requires_python": "", "summary": "IntertwiningWavelet : Pyramidal algorithms for wavelet decomposition on Graphs", "version": "0.0.10" }, "last_serial": 5929083, "releases": { "0.0.10": [ { "comment_text": "", "digests": { "md5": "826787bb34c4b6bd609a048f386bf748", "sha256": "7e4ce81c57afdfe352499e7e4ae894e2bf2cfd48ae45563a2f159d05a190e3b4" }, "downloads": -1, "filename": "IntertwiningWavelet-0.0.10.tar.gz", "has_sig": false, "md5_digest": "826787bb34c4b6bd609a048f386bf748", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11089681, "upload_time": "2019-10-04T15:53:41", "url": "https://files.pythonhosted.org/packages/dc/d7/9549877f8e5dac0b0ed9d59e1f7a161121dba7893cfc98c19d25c281eb65/IntertwiningWavelet-0.0.10.tar.gz" } ], "0.0.6": [ { "comment_text": "", "digests": { "md5": "d472ee86868111e806d9f0f470c00292", "sha256": "33eb4d09dabb475df7b7857a6022d788e2a3c1799bc079efbc27770c047061e4" }, "downloads": -1, "filename": "IntertwiningWavelet-0.0.6.tar.gz", "has_sig": false, "md5_digest": "d472ee86868111e806d9f0f470c00292", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10943638, "upload_time": "2019-09-13T15:41:57", "url": "https://files.pythonhosted.org/packages/08/13/50bcd0639da0e321e060641337992fde8a66fca2b9017fef8be193866b11/IntertwiningWavelet-0.0.6.tar.gz" } ], "0.0.7": [ { "comment_text": "", "digests": { "md5": "a76e9de4557226794ec9a5376fd05168", "sha256": "5139d355f88a857c36002e80cc70b4906e5d5337c33525d0414ff596136e6e76" }, "downloads": -1, "filename": "IntertwiningWavelet-0.0.7.tar.gz", "has_sig": false, "md5_digest": "a76e9de4557226794ec9a5376fd05168", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10943593, "upload_time": "2019-09-19T17:21:50", "url": "https://files.pythonhosted.org/packages/48/34/94d18d37b6a8f0b4890530d24bb028a8726068f8f3aa69d5eb27d0083a1e/IntertwiningWavelet-0.0.7.tar.gz" } ], "0.0.8": [ { "comment_text": "", "digests": { "md5": "4eab6768a941d2e2244c4366d87c30db", "sha256": "c5cba06bc4dc4c2298da374def954d89fa4abbaecead185090fef830363aa344" }, "downloads": -1, "filename": "IntertwiningWavelet-0.0.8.tar.gz", "has_sig": false, "md5_digest": "4eab6768a941d2e2244c4366d87c30db", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10943689, "upload_time": "2019-09-20T17:14:37", "url": "https://files.pythonhosted.org/packages/9e/57/d653b06f3124dc0f176188d9c64a63358af7014c871d7ce7163170f3a03d/IntertwiningWavelet-0.0.8.tar.gz" } ], "0.0.9": [ { "comment_text": "", "digests": { "md5": "f5516172c2faf0d49bff02ff1f63ab9c", "sha256": "b0fd22d2c6f8d4f8e91cab866987fc01b1186634c4fe6bcca3345673d52612fe" }, "downloads": -1, "filename": "IntertwiningWavelet-0.0.9.tar.gz", "has_sig": false, "md5_digest": "f5516172c2faf0d49bff02ff1f63ab9c", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11017878, "upload_time": "2019-09-27T12:51:28", "url": "https://files.pythonhosted.org/packages/66/4f/84dee92aca303b36450748bc83fa89dd0cd0981d426fd4667937a0e69321/IntertwiningWavelet-0.0.9.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "826787bb34c4b6bd609a048f386bf748", "sha256": "7e4ce81c57afdfe352499e7e4ae894e2bf2cfd48ae45563a2f159d05a190e3b4" }, "downloads": -1, "filename": "IntertwiningWavelet-0.0.10.tar.gz", "has_sig": false, "md5_digest": "826787bb34c4b6bd609a048f386bf748", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11089681, "upload_time": "2019-10-04T15:53:41", "url": "https://files.pythonhosted.org/packages/dc/d7/9549877f8e5dac0b0ed9d59e1f7a161121dba7893cfc98c19d25c281eb65/IntertwiningWavelet-0.0.10.tar.gz" } ] }