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./wip/py-lmfit, Least-Squares Minimization with Bounds and Constraints

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Branch: CURRENT, Version: 0.9.3, Package name: py27-lmfit-0.9.3, Maintainer: jihbed.research

A library for least-squares minimization and data fitting in Python. Built
on top of scipy.optimize, lmfit provides a Parameter object which can be set
as fixed or free, can have upper and/or lower bounds, or can be written in
terms of algebraic constraints of other Parameters. The user writes a function
to be minimized as a function of these Parameters, and the scipy.optimize
methods are used to find the optimal values for the Parameters.
The Levenberg-Marquardt (leastsq) is the default minimization algorithm, and
provides estimated standard errors and correlations between varied Parameters.
Other minimization methods, including Nelder-Mead's downhill simplex, Powell's
method, BFGS, Sequential Least Squares, and others are also supported. Bounds
and contraints can be placed on Parameters for all of these methods.


Required to run:
[devel/py-setuptools] [math/py-scipy] [math/py-numpy] [lang/python27]

Required to build:
[pkgtools/cwrappers]

Master sites:

SHA1: b83a6e6babb363d9bdb7ca1b3b91c53083ea8347
RMD160: c218b487bb2bdd5be3daf8dfd3905100dac0a6da
Filesize: 1093.582 KB

Version history: (Expand)