{ "info": { "author": "", "author_email": "", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Operating System :: MacOS", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering", "Topic :: Software Development" ], "description": "scikit-tensor\n=============\n.. image:: https://travis-ci.org/evertrol/scikit-tensor-py3.svg?branch=master\n :target: https://travis-ci.org/evertrol/scikit-tensor-py3\n\nscikit-tensor is a Python module for multilinear algebra and tensor\nfactorizations. Currently, scikit-tensor supports basic tensor operations\nsuch as folding/unfolding, tensor-matrix and tensor-vector products as\nwell as the following tensor factorizations:\n\n* Canonical / Parafac Decomposition\n* Tucker Decomposition\n* RESCAL\n* DEDICOM\n* INDSCAL\n\nMoreover, all operations support dense and tensors.\n\nNote\n----\n\nThis is a Python 3 only compatible maintenance release. It appears the\ndevelopment for scikit-tensor has stalled, and the project has been\nabandoned. This fork only supports Python 3.5 and later, and is\navailable on PyPI as `scikit-tensor-py3`, for easier installation.\n\nIssues and pull requests are welcomed, but issues relating algorithms\nand requests for additional algorithms may be postponed or ignored\naltogether. Technical (code) issues are welcomed.\n\nDependencies\n------------\n\nThe required dependencies to build the software are `Numpy` and `SciPy`.\n\nUsage\n-----\n\nExample script to decompose sensory bread data (available from\nhttp://www.models.life.ku.dk/datasets) using CP-ALS::\n\n\n import logging\n from scipy.io.matlab import loadmat\n from sktensor import dtensor, cp_als\n\n # Set logging to DEBUG to see CP-ALS information\n logging.basicConfig(level=logging.DEBUG)\n\n # Load Matlab data and convert it to dense tensor format\n mat = loadmat('../data/sensory-bread/brod.mat')\n T = dtensor(mat['X'])\n\n # Decompose tensor using CP-ALS\n P, fit, itr, exectimes = cp_als(T, 3, init='random')\n\n\nInstallation\n------------\n\nThis package uses distutils, which is the default way of installing\npython modules. The use of virtual environments is recommended::\n\n pip install scikit-tensor-py3\n\nTo install in development mode::\n\n git clone https://github.com/evertrol/scikit-tensor-py3.git\n pip install -e scikit-tensor\n\nContributing & Development\n--------------------------\n\nscikit-tensor is still an extremely young project, and I'm happy for\nany contributions (patches, code, bugfixes, documentation, whatever)\nto get it to a stable and useful point. Feel free to get in touch with\nme via email (mnick at AT mit DOT edu) or directly via github. See\nalso the note above.\n\nDevelopment is synchronized via git. Feel free to fork this project\nand make pull requests from that fork.\n\nAuthors\n-------\n\n* Maximilian Nickel: `Web `_,\n `Email `,\n `Twitter `_\n* Evert Rol (maintenance for Python 3 version): `Email `_\n\nLicense\n-------\n\nscikit-tensor-py3 is licensed under the `GPLv3 `_\n\nRelated Projects\n----------------\n\n* `Matlab Tensor Toolbox `_:\n A Matlab toolbox for tensor factorizations and tensor operations\n freely available for research and evaluation.\n\n* `Matlab Tensorlab `_ A Matlab toolbox for\n tensor factorizations, complex optimization, and tensor optimization\n freely available for non-commercial academic research.\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "http://github.com/evertrol/scikit-tensor-py3", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://github.com/evertrol/scikit-tensor-py3", "keywords": "", "license": "GPLv3", "maintainer": "Evert Rol", "maintainer_email": "evert.rol@gmail.com", 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