A simple objective that assumes the same variables as defined by the problem.

Public members¶

SimpleObjective(problem, name='f', n_components=1, ...)[source]

Constructor

abstract f(*x)[source]

The function.

g(var, *x, components)[source]

The analytical derivative of the function f, df/dvar, if available.

property has_ana_derivs

Returns analyical derivatives flag

maximize()[source]

Returns flag for maximization of each component.

n_components()[source]

Returns the number of components of the function.

calc_individual(vars_int, vars_float, problem_results, ...)[source]

Calculate values for a single individual of the underlying problem.

calc_population(vars_int, vars_float, problem_results, ...)[source]

Calculate values for all individuals of a population.

ana_deriv(vars_int, vars_float, var, components=None)[source]

Calculates the analytic derivative, if possible.

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

Run-time objective function factory.

initialize(verbosity=0)[source]

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()[source]

Gets the dependencies of all components on the function int variables

vardeps_float()[source]

Gets the dependencies of all components on the function float variables

rename_vars_int(varmap)[source]

Rename integer variables.

rename_vars_float(varmap)[source]

Rename float variables.

finalize_individual(vars_int, vars_float, problem_results, ...)[source]

Finalization, given the champion data.

finalize_population(vars_int, vars_float, problem_results, ...)[source]

Finalization, given the final population data.

__str__()[source]

Get info string

property initialized

Flag for finished initialization

finalize(verbosity=0)[source]

Finalize the object.