class foxes.opt.problems.layout.geom_layouts.constraints.Constraint(iwopy.core.function.OptFunction)[source]

Abstract base class for optimization constraints.

Attributes

tol: float

The tolerance for constraint violations

Public members

Constraint(*args, tol=1e-05, **kwargs)[source]

Constructor

get_bounds()[source]

Returns the bounds for all components.

check_individual(constraint_values, verbosity=0)[source]

Check if the constraints are fullfilled for the given individual.

check_population(constraint_values, verbosity=0)[source]

Check if the constraints are fullfilled for the given population.

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.