Distribution Fitting/Regression Library
Project description
probfit is a set of functions that helps you construct a complex fit. It’s intended to be used with iminuit. The tool includes Binned/Unbinned Likelihood estimator, \(\chi^2\) regression, Binned \(\chi^2\) estimator and Simultaneous fit estimator. Various functors for manipulating PDF such as Normalization and Convolution(with caching) and various builtin functions normally used in B physics is also provided.
import numpy as np from iminuit import Minuit from probfit import UnbinnedLH, gaussian data = np.random.randn(10000) unbinned_likelihood = UnbinnedLH(gaussian, data) minuit = Minuit(unbinned_likelihood, mean=0.1, sigma=1.1) minuit.migrad() unbinned_likelihood.draw(minuit)
MIT license (open source)
The tutorial is an IPython notebook that you can view online here. To run it locally: cd tutorial; ipython notebook –pylab=inline tutorial.ipynb.
- Dependencies:
matplotlib (optional, for plotting)
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