SUSE Package Hub 15 SP1 one-click install
Install python-lmfit
NOTE: This one-click installation requires that the SUSE Package Hub extension to already be enabled.
See http://packagehub.suse.com/how-to-use/ for information on enabling the Package Hub extension
If the extension is not enabled, this installation will fail while trying to enable an invalid repo.
This package might depend on packages from SUSE Linux Enterprise modules. If those modules are not enabled, a package dependency error will be encountered.
SUSE-PackageHub-15-SP1-Backports-Pool
Package Hub 15 SP1
Dummy repo - this will fail
-
python-lmfit
Least-Squares Minimization with Bounds and Constraints
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 constraints 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.
SUSE Package Hub 15 SP1 one-click install
Install python-lmfit
NOTE: This one-click installation requires that the SUSE Package Hub extension to already be enabled.
See http://packagehub.suse.com/how-to-use/ for information on enabling the Package Hub extension
If the extension is not enabled, this installation will fail while trying to enable an invalid repo.
This package might depend on packages from SUSE Linux Enterprise modules. If those modules are not enabled, a package dependency error will be encountered.
SUSE-PackageHub-15-SP1-Backports-Pool
Package Hub 15 SP1
Dummy repo - this will fail
-
python-lmfit
Least-Squares Minimization with Bounds and Constraints
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 constraints 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.