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        "author": "Baruch Tabanpour",
        "author_email": "baruch@tabanpour.info",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Information Analysis"
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        "description": "sinkhorn_knopp\n--------\n\n[![Build Status](https://travis-ci.org/btaba/sinkhorn_knopp.svg?branch=master)](https://travis-ci.org/btaba/sinkhorn_knopp)\n\n\nTo convert non-negative square matrices with total support into doubly stochastic matrices. \n\n```python\n    >> import numpy as np\n    >> from sinkhorn_knopp import sinkhorn_knopp as skp\n    >> sk = skp.SinkhornKnopp()\n    >> P = [[.011, .15], [1.71, .1]]\n    >> P_ds = sk.fit(P)\n    >> print P_ds\n        [[ 0.06102561  0.93897439]\n        [ 0.93809928  0.06190072]]\n    >> print np.sum(P_ds, axis=0)\n        [ 0.99912489  1.00087511]\n    >> print np.sum(P_ds, axis=1)\n        [ 1.,  1.]\n```\n\nSee http://msp.org/pjm/1967/21-2/pjm-v21-n2-p14-s.pdf for reference.\n\n## Install\n\nEither:\n\n```sh\npip install sinkhorn_knopp\n```\n\nor\n\n```sh\ngit clone https://github.com/btaba/sinkhorn_knopp\ncd sinkhorn_knopp\npython setup.py install\n```\n\n## Uninstall\n\nDepending on the above, either:\n\n```sh\npip uninstall sinkhorn_knopp\n```\n\nor \n\n```sh\ncd sinkhorn_knopp\npython setup.py install --record files.txt\ncat files.txt | xargs rm -rf\n```\n\n",
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        "keywords": "sinkhorn-knopp,doubly stochastic matrix",
        "license": "MIT",
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        "name": "sinkhorn_knopp",
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