py36-lmfit-0.9.13.tgz


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Description

py36-lmfit - Least-squares minimization with bounds and constraints

Property Value
Distribution NetBSD 7.0
Repository NetBSD amd64
Package filename py36-lmfit-0.9.13.tgz
Package name py36-lmfit
Package version 0.9.13
Package release -
Package architecture amd64
Package type tgz
Category math python
Homepage http://lmfit.github.io/lmfit-py/
License modified-bsd
Maintainer -
Download size 124.13 KB
Installed size 921.08 KB
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.
In addition, methods for explicitly calculating confidence intervals
are provided for exploring minmization problems where the approximation
of estimating Parameter uncertainties from the covariance matrix
is questionable.

Alternatives

Package Version Architecture Repository
py36-lmfit-0.9.13.tgz 0.9.13 i386 NetBSD
py36-lmfit - - -

Requires

Name Value
py36-asteval >= 0.9.12
py36-numpy >= 1.10
py36-scipy >= 0.19
py36-setuptools >= 0.8
py36-six >= 1.11.0
py36-uncertainties >= 3.0
python36 >= 3.6.0

Download

Type URL
Mirror ftp.netbsd.org
Binary Package py36-lmfit-0.9.13.tgz
Source Package py36-lmfit

Install Howto

Install py36-lmfit tgz package:

# pkg_add py36-lmfit

See Also

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