Prob.SmbMixture

SmbMixture.py

Copyright (c) 2020, SAXS Team, KEK-PF

class SmbMixture(K, max_iter=100)

Bases: object

calculate_mean_covariance(X, prediction)

Calculate means and covariance of different

clusters from k-means prediction

Parameters:

prediction: cluster labels from k-means X: N*d numpy array data points

Returns:

intial_means: for E-step of EM algorithm intial_cov: for E-step of EM algorithm

fit(X, bins=None)

guess_initial_params()

initilize()

moderate_sigmas(sigmas)

solve_params(k, m1, m2)

smb_pdf(x, mu, sigma, scale=1)