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 = ")