def predict(self, x): group = [] eta = qs.QsUpdater.calculate_eta(x.reshape(1, -1), ql_updater.W, ql_updater.nu, qm_updater.m, qm_updater.beta, qp_updater.alpha)[0] for _ in range(TRIAL_NUM): ys = [] for k in range(K): Lambda = self.wishs[k].sample().astype(np.float32) g_mu = gauss.Gauss(qm_updater.m[k], qm_updater.beta[k] * Lambda) mu = g_mu.sample() g_x = gauss.Gauss(mu, torch.tensor(Lambda)) y = eta[k] * g_x.probs(x) ys.append(y) ys /= np.sum(ys) group.append(ys) return np.array(group)
def page_rank1(m_transi): taille_p = len(m_transi) m_n = m_transi - np.identity(taille_p) m_n = np.transpose(m_n) ligne_a_ajouter = np.ones((1, taille_p)) y = np.zeros((taille_p, 1)) m_n = np.concatenate((m_n, ligne_a_ajouter)) y = np.concatenate((y, np.array([[1]]))) m_n, y = gauss.Gauss(m_n, y) res = gauss.solveTriSup(m_n, y) return res
import input_output as io import gauss import aditional_functions as af import LU A = io.Input_matrix_from_keyboard() b = io.Input_matrix_from_keyboard() af.checking_SLAR(A, b) x = gauss.Gauss(A, b) if type(x) == int: print("The system is degenerate, we figure out it on the " + str(-x) + " iteration") else: io.print_matrix(x, "Answer via Gauss: ") io.print_matrix(af.subtraction(af.multiplying(A, x), b), "r = A*x - b = ") (L, U) = LU.Factorization(A) if L == False: print("This matrix can't be factorized") quit(-1) io.print_matrix(L, "Matrix L:") io.print_matrix(U, "Matrix U:") io.print_matrix(af.multiplying(L, U), "L*U = ") B = LU.Inversed_matrix(L, U) io.print_matrix(B, "A^(-1) = ") x = LU.solution(L, U, b) io.print_matrix(x, "Answer via LU factorization: ") print("Number of conditionality = " + str(round(LU.matrix_norm(A) * LU.matrix_norm(B)))) io.print_matrix(af.subtraction(af.multiplying(A, x), b), "r = A*x - b = ")