class foxes_opt.problems.layout.geom_layouts.objectives.Objective(iwopy.core.function.OptFunction)[source]

Abstract base class for objective functions.

Public members

abstract maximize()[source]

Returns flag for maximization of each component.

classmethod new(objective_type, *args, **kwargs)[source]

Run-time objective function factory.

Objective(problem, name, n_vars_int=None, n_vars_float=None, ...)

Constructor

abstract n_components()

Returns the number of components of the function.

initialize(verbosity=0)

Initialize the object.

property component_names

The names of the components

property var_names_int

The names of the integer variables

property n_vars_int

The number of int variables

property var_names_float

The names of the float variables

property n_vars_float

The number of float variables

vardeps_int()

Gets the dependencies of all components on the function int variables

vardeps_float()

Gets the dependencies of all components on the function float variables

rename_vars_int(varmap)

Rename integer variables.

rename_vars_float(varmap)

Rename float variables.

calc_individual(vars_int, vars_float, problem_results, ...)

Calculate values for a single individual of the underlying problem.

calc_population(vars_int, vars_float, problem_results, ...)

Calculate values for all individuals of a population.

finalize_individual(vars_int, vars_float, problem_results, ...)

Finalization, given the champion data.

finalize_population(vars_int, vars_float, problem_results, ...)

Finalization, given the final population data.

ana_deriv(vars_int, vars_float, var, components=None)

Calculates the analytic derivative, if possible.

__str__()

Get info string

property initialized

Flag for finished initialization

finalize(verbosity=0)

Finalize the object.