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Distribution Fitting/Regression Library

Project description

probfit
--------

*probfit* is a set of functions that helps you construct a complex fit. It's
intended to be used with `iminuit <http://iminuit.github.com/iminuit/>`_. The
tool includes Binned/Unbinned Likelihood estimator, :math:`\chi^2` regression,
Binned :math:`\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.

::

from probfit import UnbinnedLH, gaussian
from iminuit import Minuit
data = np.randn(10000)
ulh = UnbinnedLH(data)
m = Minuit(ulh, mean=0.1, sigma=1.1)
m.migrad()
ulh.draw(m)


Requirement
-----------

- iminuit https://iminuit.github.com/iminuit/
- numpy http://www.numpy.org/
- matplotlib http://matplotlib.org/

Tutorial
--------

open tutorial.ipynb in ipython notebook. You can `view it online <http://nbviewer.ipython.org/urls/raw.github.com/iminuit/probfit/master/tutorial/tutorial.ipynb>`_ too.


Documentation
-------------

See `here <http://iminuit.github.com/probfit/>`_

Project details


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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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Filename, size & hash SHA256 hash help File type Python version Upload date
probfit-1.0.2.tar.gz (754.8 kB) Copy SHA256 hash SHA256 Source None Jan 6, 2013

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