clustering.py 文件源码

def _EM_VMM_expectation_step_hard(mu_list, kappa_list, instance_array):
    start_time = time.time()
    n_clusters = len(mu_list); 
    n_datapoints, n_dimensions = instance_array.shape
    probs = np.ones((instance_array.shape[0],n_clusters),dtype=float)
    for mu_tmp, kappa_tmp, cluster_ident in zip(mu_list,kappa_list,range(n_clusters)):
        #We are checking the probability of belonging to cluster_ident
        probs_1 = np.product(np.exp(kappa_tmp*np.cos(instance_array-mu_tmp))/(2.*np.pi*spec.iv(0,kappa_tmp)),axis=1)
        probs[:,cluster_ident] = probs_1
    assignments = np.argmax(probs,axis=1)
    #return assignments, L
    return assignments, 0