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.