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    "info": {
        "author": "vittore.scolari@pasteur.fr",
        "author_email": "",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Artistic License",
            "Operating System :: MacOS",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
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            "Programming Language :: Python :: 3",
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            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
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            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Bio-Informatics",
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        "description": "![Serpentine logo](demos/serpentine.gif)\n\n# Serpentine binning\n\n[![PyPI version](https://badge.fury.io/py/serpentine.svg)](https://badge.fury.io/py/serpentine)\n![PyPI - Python Version](https://img.shields.io/pypi/pyversions/serpentine.svg)\n[![Build Status](https://travis-ci.org/koszullab/serpentine.svg?branch=master)](https://travis-ci.org/koszullab/serpentine)\n[![Appveyor Status](https://ci.appveyor.com/api/projects/status/github/koszullab/serpentine?svg=true)](https://ci.appveyor.com/project/baudrly/serpentine)\n[![codecov](https://codecov.io/gh/koszullab/serpentine/branch/master/graph/badge.svg)](https://codecov.io/gh/koszullab/serpentine)\n[![Read the docs](https://readthedocs.org/projects/serpentine/badge)](https://serpentine.readthedocs.io)\n[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/koszullab/serpentine/master?filepath=doc%2Fnotebooks%2Fdemo_yeast.ipynb)\n[![License: Artistic-2.0](https://img.shields.io/badge/License-Artistic%202.0-0298c3.svg)](https://opensource.org/licenses/Artistic-2.0)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)\n\nLocally smearing noisy regions in Hi-C contact maps as a prelude to differential analyses\n\n## Table of contents\n\n   - [Synopsis](#synopsis)\n   - [Installation](#installation)\n   - [Documentation](#documentation)\n   - [Authors](#authors)\n   - [Copyright and license](#copyright-and-license)\n\n## Synopsis\n\nUse it as a Python 3 library:\n\n```python\n   import numpy as np\n   import serpentine as sp\n\n   A = np.loadtxt('./demos/A.csv')\n   B = np.loadtxt('./demos/B.csv')\n   trend, threshold = sp.MDbefore(A, B, show=False)\n\n   sA, sB, sK = sp.serpentin_binning(A, B, threshold, threshold / 5)\n```\n\nOr as a standalone UNIX tool:\n\n```\n$ serpentine --help\n   Serpentine binning\n\n   An implementation of the so-called 'serpentine binning' procedure described\n   in Scolari et al.\n\n   Command line::\n\n    Usage:\n        serpentine.py [<matrixA>] [<matrixB>] [--threshold=auto] [--verbose]\n                      [--min-threshold=auto] [--trend=high] [--triangular]\n                      [--limit=3] [--demo] [--demo-size=500]\n\n    Arguments:\n        matrixA                         The first input matrix, in plain text\n                                        CSV format. Optional in demo mode.\n        matrixB                         The second input matrix, in plain text\n                                        CSV format. Optional in demo mode or\n                                        single binning mode.\n\n    Options:\n        -h, --help                      Display this help message.\n        --version                       Display the program's current version.\n        -t auto, --threshold auto       Threshold value to trigger binning.\n                                        [default: auto]\n        -m auto, --min-threshold auto   Minimum value to force trigger binning\n                                        in either matrix. [default: auto]\n        --trend high                    Trend to subtract to the differential\n                                        matrix, possible values are \"mean\":\n                                        equal amount of positive and negative\n                                        differences, and \"high\": normalize\n                                        at the regions with higher coverage.\n                                        [default: high]\n        --triangular                    Treat the matrix as triangular,\n                                        useful when plotting matrices adjacent\n                                        to the diagonal. [default: False]\n        --limit 3                       Set the z-axis limit on the\n                                        plot of the differential matrix.\n                                        [default: 3]\n        --demo                          Run a demo on randomly generated\n                                        matrices. [default: False]\n        --demo-size 500                 Size of the test matrix for the demo.\n                                        [default: 500]\n        -v, --verbose                   Show verbose output. [default: False]\n```\n\n## Installation\n\n```sh\n   sudo pip3 install -e git+https://github.com/koszullab/serpentine.git@master#egg=serpentine\n```\n\n## Documentation\n\nExecuting the command `serpentine  --help` will give you a brief help of the command line tool. For a detailed reference to the python library functions, please \nread the [documentation](https://serpentine.readthedocs.io/en/latest/).\n\n## Authors\n\nCluster Buster ([scovit](https://github.com/scovit), a.k.a. Vittore F. Scolari),\nLyamovich ([baudrly](https://github.com/baudrly), a.k.a. Lyam Baudry)\n\n## Copyright and license\n\nCopyright \u00a9 2017 Institut Pasteur, this software has been developed in\nthe Regulation Spatiale des Chromosomes team of Pasteur Institut,\nParis, France.\n\nThis library is free software; you can redistribute it and/or modify\nit under the Artistic License.\n\n\n",
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