Metadata-Version: 2.1
Name: brute-curvefit
Version: 0.0.3
Summary: Curve fitting using both brute force and scipy.optimize
Home-page: https://github.com/analkumar2/brute_force
Author: Anal Kumar
Author-email: analkumar2@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

This is a simple script which tries to find the global minima using scipy.optimize.curve_fit as well as a parameter search over the parameter space.
It first generates ntol random models, then selects ntol*returnnfactor best models and does scipy.optimize.curve_fit on all of them. It then returns the best model of them all.
This script improves scipy.optimize.curve_fit in two ways - No need to give initial values and thus getting global minima instead of local minima. And second, it automatically normalize and standardizes the data.

FUTURE:
1. Parallelize
2. Use Genetic algorithm instead of brute-force


