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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, :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.

.. code-block:: python

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)

* `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:
- `iminuit <>`_
- `numpy <>`_
- `matplotlib <>`_ (optional, for plotting)
* Developing probfit: see the `development page <>`_

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