pymead.optimization.sampling.PymooLHS# class PymooLHS(n_samples, norm_param_list)[source]# Bases: Sampling __init__(n_samples, norm_param_list)[source]# Latin-Hypercube sampling method from the pymoo package. Parameters: n_samples (int) – Number of samples norm_param_list (list) – List of normalized parameter values (usually from extract_parameters in MEA). Methods sample() Randomly samples the design space. sample()[source]# Randomly samples the design space. Returns: norm_param_list – 1-D array of normalized parameter values (usually from extract_parameters in MEA). Return type: np.ndarray
