MINUIT2 from Python - Fitting like a boss
Project description
iminuit is a Python interface to the MINUIT2 C++ package.
It can be used as a general robust function minimization method, but is most commonly used for likelihood fits of models to data, and to get model parameter error estimates from likelihood profile analysis.
Documentation: http://iminuit.readthedocs.org/
Gitter: https://gitter.im/HSF/PyHEP
Mailing list: https://groups.google.com/forum/#!forum/scikit-hep-forum
License: MINUIT2 is LGPL and iminuit is MIT
Citation: https://github.com/iminuit/iminuit/blob/master/CITATION
In a nutshell
from iminuit import Minuit
def f(x, y, z):
return (x - 2) ** 2 + (y - 3) ** 2 + (z - 4) ** 2
m = Minuit(f)
m.migrad() # run optimiser
print(m.values) # {'x': 2,'y': 3,'z': 4}
m.hesse() # run covariance estimator
print(m.errors) # {'x': 1,'y': 1,'z': 1}Release history Release notifications | RSS feed
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