cma.fitness_transformations.IntegerMixedFunction

class documentation

class IntegerMixedFunction(ComposedFunction):

compose fitness function with some integer variables.

>>> import cma
>>> f = cma.s.ft.IntegerMixedFunction(cma.ff.elli, [0, 3, 6])
>>> assert f([0.2, 2]) == f([0.4, 2]) != f([1.2, 2])

It is advisable to set minstd of integer variables to 1 / (2 * len(integer_variable_indices) + 1), in which case in an independent model at least 33% (1 integer variable) -> 39% (many integer variables) of the solutions should have an integer mutation on average. Option integer_variables of cma.CMAOptions implements this simple measure.

Method	`__init__`	apply operator(x[i]) for i in integer_variable_indices before to call function(x)
Instance Variable	`copy_arg`	Undocumented
Instance Variable	`integer_variable_indices`	Undocumented
Instance Variable	`operator`	Undocumented
Method	`_flatten`	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, function, integer_variable_indices, operator=np.floor, copy_arg=True): ¶

overrides cma.fitness_transformations.ComposedFunction.__init__

apply operator(x[i]) for i in integer_variable_indices before to call function(x)

copy_arg = ¶

Undocumented

integer_variable_indices = ¶

Undocumented

operator = ¶

Undocumented

def _flatten(self, x): ¶

Undocumented