{
    "info": {
        "author": "Yiyin Zhou",
        "author_email": "yz2227@columbia.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Environment :: Other Environment",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering"
        ],
        "description": "",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "https://github.com/bionet/vtem/archive/0.1.1.tar.gz",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "http://bionet.github.io/vtem",
        "keywords": "Time Enoding, Time Decoding, Population encoding",
        "license": "",
        "maintainer": "Nikul Ukani",
        "maintainer_email": "nikul@ee.columbia.edu",
        "name": "vtem",
        "package_url": "https://pypi.org/project/vtem/",
        "platform": "",
        "project_url": "https://pypi.org/project/vtem/",
        "project_urls": {
            "Download": "https://github.com/bionet/vtem/archive/0.1.1.tar.gz",
            "Homepage": "http://bionet.github.io/vtem"
        },
        "release_url": "https://pypi.org/project/vtem/0.1.1/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "This package provides code to encode and decode videos with  time encoding machines consisting of  gabor or centre surround receptive fields followed by Integrate-and-fire neurons .It supports both the pseudoinverse algorithm and recurrent neural networks method for decoding.",
        "version": "0.1.1"
    },
    "last_serial": 771049,
    "releases": {
        "0": [],
        "0.1.1": []
    },
    "urls": []
}