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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)
  • Documentation
  • 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:
Release History

Release History

This version
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1.0.5

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1.0.4

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1.0.3

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1.0.2

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1.0.1

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1.0.0

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
probfit-1.0.5.tar.gz (960.7 kB) Copy SHA256 Checksum SHA256 Source Sep 14, 2013

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