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such that the boundaries are not passed as options anymore and the BoundTransform boundary handling can be used easily with any other algorithm. Also, fmin2 could use the function wrapper instead of passing bounds to the GenoPheno transformation.
where the docstring of BoundTransform should be improved.
The text was updated successfully, but these errors were encountered:
nikohansen
changed the title
Implement a shorter function wrapper based on transformations.BoxConstraintsLinQuadTransformation
Implement a shorter function boundary wrapper based on transformations.BoxConstraintsLinQuadTransformationSep 18, 2024
importcmaclassWrapBoundaryTransform(cma.fitness_transformations.ComposedFunction):
def__init__(self, objective_function, boundaries):
# could in principle be done with BoundPenalty tooself.boundary_handler=cma.boundary_handler.BoundTransform(boundaries)
self.transform=self.boundary_handler.transformsuper(WrapBoundaryTransform, self).__init__(
[objective_function, self.transform])
The output of fmin2 is the untransformed solution, hence the optimal x-values are negative, which is a little confusing and somewhat mitigated by the bounds option.
such that the boundaries are not passed as options anymore and the
BoundTransform
boundary handling can be used easily with any other algorithm. Also,fmin2
could use the function wrapper instead of passing bounds to theGenoPheno
transformation.This wrapper is just a shortcut for
where the docstring of
BoundTransform
should be improved.The text was updated successfully, but these errors were encountered: