Fitting Tool for High Energy Physics
Project description
IPANEMA: Hyperthread Curve-Fitting Module for Python
Ipanema provides a high-level interface to non-linear for Python. It supports most of the optimization methods from scipy.optimize jointly with others like emcc, ampgo and the so-calle Minuit.
Main functionalities:
Despite the comon use of plain float as fitting variables, Ipanema relies on the Parameter class. A Parameter has a value that can be varied in the fit, fixed, have upper and/or lower bounds. It can even have a value that is constrained by an algebraic expression of other Parameter values.
Multiple fitting algorithms working out-of-the-box without any change in the cost function to minimize.
Hyperthreading is avaliable and models can be compilead against different backends. One can use python for fits as usual, but if the amount of data is large, then better rewrite your code in cuda or opencl, and Ipanema can take care of that cost function. That’s simple.
Estimation of confidence intervals usin ANOVA instead of calculating uncertainties and correlations from the covariance matrix.
Copyright (c) 2020 Ipanema Developers ; GNU AFFERO GENERAL PUBLIC LICENSE
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