wip/py-cma 1.1.01 NetBSD

CMA-ES, Covariance Matrix Adaptation Evolution Strategy for non-linear numerical optimization in Python

a stochastic numerical optimization algorithm for difficult (non-convex, ill-conditioned, multimodal) optimization problems in continuous search spaces, implemented in Python.

Typical domain of application are objective functions with:

search space dimension between 5 and 100, at least about 100 times dimension function evaluations needed to get satisfactory solutions, non-separable, ill-conditioned, or rugged/multi-modal landscapes