cma.boundary_handler.BoundNone

class documentation

class BoundNone(BoundaryHandlerBase):

Constructor: BoundNone(bounds)

no boundaries

Method	`__init__`	`bounds` can be `None` or `[lb, ub]`
Method	`is_in_bounds`	return `True` if `x` is in bounds.

Inherited from BoundaryHandlerBase:

Method	`__call__`	return penalty or list of penalties, by default zero(s).
Method	`amend_bounds_for_integer_variables`	set bounds away from `at=0.5` such that
Method	`get_bound`	return lower and upper bound of variable with index `index`
Method	`get_bounds`	`get_bounds('lower', 8)` returns the lower bounds in 8-D
Method	`has_bounds`	return `True` if any variable is bounded
Method	`idx_out_of_bounds`	return index list of out-of-bound values in `x`.
Method	`into_bounds`	set out-of-bound values on bounds and return `x`.
Method	`inverse`	inverse of repair if it exists, at least it should hold `repair == repair o inverse o repair`
Method	`repair`	projects infeasible values on the domain bound, might be overwritten by derived class
Method	`to_dim_times_two`	return boundaries in format `[[lb0, ub0], [lb1, ub1], ...]`, as used by `BoxConstraints...` class.
Method	`update`	end-iteration callback of boundary handler (abstract/empty)
Instance Variable	`bounds`	Undocumented
Instance Variable	`use_cached_values`	default behavior as to whether to use cached values
Method	`_get_bounds`	ib == 0/1 means lower/upper bound, return a vector of length `dimension`
Instance Variable	`_bounds_dict`	saved return values of get_bounds(i, dim). Changing `self.bounds` may only be effective when this is reset.

def __init__(self, bounds=None): ¶

overrides cma.boundary_handler.BoundaryHandlerBase.__init__

bounds can be None or [lb, ub]

where lb and ub are either None or a vector (which can have None entries).

On return, the bounds attribute of self are the bounds in a normalized form.

To compute bounds for any dimension, the last entry of bounds is then recycled for variables with indices >= len(bounds[i]) for i in (0,1).

def is_in_bounds(self, x): ¶

overrides cma.boundary_handler.BoundaryHandlerBase.is_in_bounds

return True if x is in bounds.

>>> import numpy as np
>>> import cma

>>> b = cma.boundary_handler.BoundaryHandlerBase(bounds=[[-0.5], 0.2])
>>> for n in [2, 4, 9]:
...     x = np.random.randn(n)
...     assert (all(-0.5 <= x) and all(0.2 >= x)) is b.is_in_bounds(x)