def init_X(data_matrix): X_init = data_matrix.sample_latent_values( np.zeros((data_matrix.m, data_matrix.n)), 1.) svd_K = min(20, data_matrix.m // 4, data_matrix.n // 4) svd_K = max(svd_K, 2) # 0 and 1 cause it to crash _, _, _, _, _, X_init = low_rank.fit_model(data_matrix, svd_K, 10) return X_init
def init_X(data): svd_K = min(20, data.shape[0] // 4, data.shape[1] // 4) svd_K = max(svd_K, 2) # 1 and 0 cause it to crash dummy = observations.DataMatrix(data) _, _, _, _, _, X = low_rank.fit_model(dummy, svd_K, 10) return X
def init_X(data_matrix): X_init = data_matrix.sample_latent_values(np.zeros((data_matrix.m, data_matrix.n)), 1.) svd_K = min(20, data_matrix.m // 4, data_matrix.n // 4) svd_K = max(svd_K, 2) # 0 and 1 cause it to crash _, _, _, _, _, X_init = low_rank.fit_model(data_matrix, svd_K, 10) return X_init