uadapy.dr.uapca_revisited module

uadapy.dr.uapca_revisited.uapca_revisited(distributions: list, n_dims: int = 2, n_samples: int = 10000, seed: int = None) → list

Applies UAPCA Revisited algorithm to the distributions and returns the projected samples for each distribution. It assumes normal distributions. If you apply other distributions that provide mean and covariance, these values would be used to approximate a normal distribution.

Parameters:

• distributions (list) – List of input distributions

• n_dims (int) – Target dimension. Default is 2.

• n_samples (int) – Number of Monte Carlo samples. Default is 10000.

• seed (int, optional) – Random seed for reproducibility. Default is None.

Returns:

List of arrays containing projected samples for each distribution. Each array has shape (n_samples, n_dims).

Return type:

list