pymatcher

Name	pymatcher JSON
Version	0.0.0 JSON
	download
home_page	https://github.com/jw156605/matcher
Summary	Manifold Alignment to Characterize Experimental Relationships
upload_time	2017-06-16 18:50:58
maintainer
docs_url	None
author	Joshua D. Welch
requires_python
license	MIT
keywords	manifold learning single cell genomics
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage

            MATCHER
=======================

MATCHER is intended to be run with the Anaconda distribution of Python (https://www.continuum.io/downloads). 

Installation: pip install <path-to-matcher>

Full HTML documentation is available in docs/build/html/index.html

MATCHER_demo.ipynb is a Jupyter notebook demonstrating how to run MATCHER on synthetic data provided with the package.
            

Raw data

            {
    "_id": null,
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "cheesecake_code_kwalitee_id": null,
    "keywords": "manifold learning single cell genomics",
    "upload_time": "2017-06-16 18:50:58",
    "author": "Joshua D. Welch",
    "home_page": "https://github.com/jw156605/matcher",
    "github_user": "jw156605",
    "download_url": "https://pypi.python.org/packages/2e/ba/4594178c61fdb7f353f6fc7c633c4c5b7ba687a08ff0f22f2a6a58f67e43/pymatcher-0.0.0.tar.gz",
    "platform": "",
    "version": "0.0.0",
    "cheesecake_documentation_id": null,
    "description": "MATCHER\r\n=======================\r\n\r\nMATCHER is intended to be run with the Anaconda distribution of Python (https://www.continuum.io/downloads). \r\n\r\nInstallation: pip install <path-to-matcher>\r\n\r\nFull HTML documentation is available in docs/build/html/index.html\r\n\r\nMATCHER_demo.ipynb is a Jupyter notebook demonstrating how to run MATCHER on synthetic data provided with the package.",
    "lcname": "pymatcher",
    "name": "pymatcher",
    "github": true,
    "bugtrack_url": null,
    "license": "MIT",
    "travis_ci": false,
    "github_project": "matcher",
    "summary": "Manifold Alignment to Characterize Experimental Relationships",
    "split_keywords": [
        "manifold",
        "learning",
        "single",
        "cell",
        "genomics"
    ],
    "author_email": "jwelch@cs.unc.edu",
    "urls": [
        {
            "has_sig": false,
            "upload_time": "2017-06-16T18:50:58",
            "comment_text": "",
            "python_version": "source",
            "url": "https://pypi.python.org/packages/2e/ba/4594178c61fdb7f353f6fc7c633c4c5b7ba687a08ff0f22f2a6a58f67e43/pymatcher-0.0.0.tar.gz",
            "md5_digest": "4ad15e82f994adc83a751bc75e90210f",
            "downloads": 0,
            "filename": "pymatcher-0.0.0.tar.gz",
            "packagetype": "sdist",
            "path": "2e/ba/4594178c61fdb7f353f6fc7c633c4c5b7ba687a08ff0f22f2a6a58f67e43/pymatcher-0.0.0.tar.gz",
            "size": 1557507
        }
    ],
    "cheesecake_installability_id": null,
    "coveralls": true
}