Metadata-Version: 2.1
Name: binprism
Version: 1.1.1
Summary: Package for fitting continuous profiles to binned data
Home-page: https://github.com/JoeJimFlood/BinPrism
Author: Joseph J. Flood
Author-email: "Joseph J. Flood" <joejimflood@gmail.com>
License: GNU GPLv3
Keywords: data_analysis,simulation
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
License-File: license.txt.txt
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: matplotlib

# 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.
