cma.fitness_transformations.LowEffectiveDimension

class documentation

class LowEffectiveDimension(ComposedFunction):

Constructor: LowEffectiveDimension(f, effective_dimensions)

Evaluate a function only in a lower dimensional subspace.

effective_dimensions = 0.1 can be an int (number of effective variables) or a ratio <= 1 (-> max(1, int(ratio * len(x)))) or an index array. In the former two cases, the first variables are effective.

See also NeutralVariables for the case when the dimension affects the underlying function definition.

Caveat: this has never been thoroughly tested.

>>> from cma import fitness_transformations as ft
>>> fun = ft.LowEffectiveDimension(cma.ff.sphere)
>>> 1**2 + 2**2 == fun(range(1, 21))
True

Method	`__init__`	`effective_dimensions` can be an `int` or a ratio or and index array.
Instance Variable	`_select_effective`	Undocumented

Inherited from ComposedFunction:

Method	`__call__`	Undocumented
Method	`inverse`	evaluate the composition of inverses on `x`.
Instance Variable	`list_of_inverses`	Undocumented

Inherited from Function (via ComposedFunction):

Method	`initialize`	initialization of `Function`
Instance Variable	`evaluations`	Undocumented
Instance Variable	`ftarget`	Undocumented
Instance Variable	`target_hit_at`	Undocumented
Property	`function_names_to_evaluate_first_found`	attributes which are searched for to be called if no function was given to `__init__`.
Class Variable	`_function_names_to_evaluate_first_found`	Undocumented
Instance Variable	`__callable`	Undocumented
Instance Variable	`__initialized`	Undocumented

def __init__(self, f, effective_dimensions=0.1): ¶

overrides cma.fitness_transformations.ComposedFunction.__init__

effective_dimensions can be an int or a ratio or and index array.

_select_effective = ¶

Undocumented