pymloc.model.optimization.objectives.nonlinear_leastsquares

Classes

AutomaticLocalNonLinearLeastSquares(…)
NonLinearLeastSquares(lower_level_variables, …)	Objective function of nonlinear least squares problems

class pymloc.model.optimization.objectives.nonlinear_leastsquares.AutomaticLocalNonLinearLeastSquares(global_objective)

Bases: pymloc.model.optimization.objectives.objective.AutomaticLocalObjective

Parameters

global_objective (pymloc.model.optimization.objectives.nonlinear_leastsquares.NonLinearLeastSquares) –

class pymloc.model.optimization.objectives.nonlinear_leastsquares.NonLinearLeastSquares(lower_level_variables, higher_level_variables, local_level_variables, rhs)

Bases: pymloc.model.optimization.objectives.objective.Objective

Objective function of nonlinear least squares problems

Parameters

rhs (Callable[[pymloc.model.variables.container.VariablesContainer, pymloc.model.variables.container.VariablesContainer, pymloc.model.variables.container.VariablesContainer], numpy.ndarray]) –

get_jac(ll_vars, hl_vars, loc_vars)

Helper method, that computes the jacobian of the residual function.

Possibly by using sensitivity information from lower level optimizations.

Return type

numpy.ndarray

residual(ll_vars, hl_vars, loc_vars)