binprism


Namebinprism JSON
Version 1.1.1 PyPI version JSON
download
home_pagehttps://github.com/JoeJimFlood/BinPrism
SummaryPackage for fitting continuous profiles to binned data
upload_time2023-01-21 19:25:53
maintainer
docs_urlNone
authorJoseph J. Flood
requires_python>=3.7
licenseGNU GPLv3
keywords data_analysis simulation
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # BinPrism
Tools for fitting linear combinations of continuous basis functions to match binned data.

Often, data from continuous variables are placed into discrete bins.
BinPrism fits continuous profiles to match these bins, allowing for the ability to produce clean visualizations, re-aggregate data into differently-sized bins, and simulate random values folling a continuous distribution matching the original data. Like a prism separating light into different colors, BinPrism takes in binned data and separates it into simple waves, saving the contribution of each wave to memory. Presently, BinPrism only works for periodic data (such as daily or yearly patterns), but it is hoped that in the future more domains will be supported.

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/JoeJimFlood/BinPrism",
    "name": "binprism",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.7",
    "maintainer_email": "",
    "keywords": "data_analysis,simulation",
    "author": "Joseph J. Flood",
    "author_email": "\"Joseph J. Flood\" <joejimflood@gmail.com>",
    "download_url": "",
    "platform": null,
    "description": "# BinPrism\nTools for fitting linear combinations of continuous basis functions to match binned data.\n\nOften, data from continuous variables are placed into discrete bins.\nBinPrism fits continuous profiles to match these bins, allowing for the ability to produce clean visualizations, re-aggregate data into differently-sized bins, and simulate random values folling a continuous distribution matching the original data. Like a prism separating light into different colors, BinPrism takes in binned data and separates it into simple waves, saving the contribution of each wave to memory. Presently, BinPrism only works for periodic data (such as daily or yearly patterns), but it is hoped that in the future more domains will be supported.\n",
    "bugtrack_url": null,
    "license": "GNU GPLv3",
    "summary": "Package for fitting continuous profiles to binned data",
    "version": "1.1.1",
    "split_keywords": [
        "data_analysis",
        "simulation"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "60a720dddbf723f499167a4cbcbd2b738134c9a68fd9bb3380e87f03ac0e236b",
                "md5": "5a385eff377dae630694070841de518a",
                "sha256": "9c54f5c3e12f79bda5143508cad6b8aa3fd6c2ff2c672d7236db98c1462f89f7"
            },
            "downloads": -1,
            "filename": "binprism-1.1.1-py2.py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "5a385eff377dae630694070841de518a",
            "packagetype": "bdist_wheel",
            "python_version": "py2.py3",
            "requires_python": ">=3.7",
            "size": 28730,
            "upload_time": "2023-01-21T19:25:53",
            "upload_time_iso_8601": "2023-01-21T19:25:53.096125Z",
            "url": "https://files.pythonhosted.org/packages/60/a7/20dddbf723f499167a4cbcbd2b738134c9a68fd9bb3380e87f03ac0e236b/binprism-1.1.1-py2.py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-01-21 19:25:53",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "github_user": "JoeJimFlood",
    "github_project": "BinPrism",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "binprism"
}
        
Elapsed time: 0.09864s