def testSubmatrix(self): n = self.n Psym = poisson.poisson1d_sym(n) P = poisson.poisson1d(n) for i in range(n): P[i, i] = 4.0 Psym[i, i] = 4.0 # read and test diagonal blocks for i in range(n): self.failUnless( llmat_isEqual(self.A[n * i:n * (i + 1), n * i:n * (i + 1)], P)) #self.failUnless(llmat_isEqual(self.S[n*i:n*(i+1),n*i:n*(i+1)], P)) self.failUnless( llmat_isEqual(self.A[n * i:n * (i + 1), n * i:n * (i + 1)], Psym)) #self.failUnless(llmat_isEqual(self.S[n*i:n*(i+1),n*i:n*(i+1)], Psym)) # store and get diagonal blocks R = spmatrix_util.ll_mat_rand(n * n, n * n, 0.01) # random matrix for i in range(n): R[n * i:n * (i + 1), n * i:n * (i + 1)] = P self.failUnless( llmat_isEqual(R[n * i:n * (i + 1), n * i:n * (i + 1)], P)) R[n * i:n * (i + 1), n * i:n * (i + 1)] = Psym self.failUnless( llmat_isEqual(R[n * i:n * (i + 1), n * i:n * (i + 1)], Psym)) # store and get off-diagonal blocks for i in range(n - 1): R[n * i:n * (i + 1), n * (i + 1):n * (i + 2)] = P self.failUnless( llmat_isEqual(R[n * i:n * (i + 1), n * (i + 1):n * (i + 2)], P)) R[n * i:n * (i + 1), n * (i + 1):n * (i + 2)] = Psym self.failUnless( llmat_isEqual(R[n * i:n * (i + 1), n * (i + 1):n * (i + 2)], Psym)) # store and get diagonal blocks in symmetric matrix R = spmatrix.ll_mat_sym(n * n) for i in range(n): R[n * i:n * (i + 1), n * i:n * (i + 1)] = Psym self.failUnless( llmat_isEqual(R[n * i:n * (i + 1), n * i:n * (i + 1)], Psym)) # store and get off-diagonal blocks in symmetric matrix for i in range(n - 1): R[n * (i + 1):n * (i + 2), n * i:n * (i + 1)] = P self.failUnless( llmat_isEqual(R[n * (i + 1):n * (i + 2), n * i:n * (i + 1)], P)) R[n * (i + 1):n * (i + 2), n * i:n * (i + 1)] = Psym self.failUnless( llmat_isEqual(R[n * (i + 1):n * (i + 2), n * i:n * (i + 1)], Psym))
def setUp(self): self.n = 50000 self.A = PysparseMatrix(matrix=poisson.poisson1d_sym(self.n)) self.x_exact = numpy.ones(self.n)/math.sqrt(self.n) self.normx = 1.0/math.sqrt(self.n) self.b = self.A * self.x_exact lmbd_min = 4.0 * math.sin(math.pi/2.0/self.n) ** 2 lmbd_max = 4.0 * math.sin((self.n - 1)*math.pi/2.0/self.n) ** 2 cond = lmbd_max/lmbd_min self.tol = cond * macheps() self.LU = None self.relerr = 0.0 self.descr = '' self.fmt = '\t%10s %8.2e %8.2e %8d %8d %6.2f %6.2f\n'
def testSubmatrix(self): n = self.n Psym = poisson.poisson1d_sym(n) P = poisson.poisson1d(n) for i in range(n): P[i, i] = 4.0 Psym[i, i] = 4.0 # read and test diagonal blocks for i in range(n): self.failUnless(llmat_isEqual(self.A[n * i : n * (i + 1), n * i : n * (i + 1)], P)) # self.failUnless(llmat_isEqual(self.S[n*i:n*(i+1),n*i:n*(i+1)], P)) self.failUnless(llmat_isEqual(self.A[n * i : n * (i + 1), n * i : n * (i + 1)], Psym)) # self.failUnless(llmat_isEqual(self.S[n*i:n*(i+1),n*i:n*(i+1)], Psym)) # store and get diagonal blocks R = spmatrix_util.ll_mat_rand(n * n, n * n, 0.01) # random matrix for i in range(n): R[n * i : n * (i + 1), n * i : n * (i + 1)] = P self.failUnless(llmat_isEqual(R[n * i : n * (i + 1), n * i : n * (i + 1)], P)) R[n * i : n * (i + 1), n * i : n * (i + 1)] = Psym self.failUnless(llmat_isEqual(R[n * i : n * (i + 1), n * i : n * (i + 1)], Psym)) # store and get off-diagonal blocks for i in range(n - 1): R[n * i : n * (i + 1), n * (i + 1) : n * (i + 2)] = P self.failUnless(llmat_isEqual(R[n * i : n * (i + 1), n * (i + 1) : n * (i + 2)], P)) R[n * i : n * (i + 1), n * (i + 1) : n * (i + 2)] = Psym self.failUnless(llmat_isEqual(R[n * i : n * (i + 1), n * (i + 1) : n * (i + 2)], Psym)) # store and get diagonal blocks in symmetric matrix R = spmatrix.ll_mat_sym(n * n) for i in range(n): R[n * i : n * (i + 1), n * i : n * (i + 1)] = Psym self.failUnless(llmat_isEqual(R[n * i : n * (i + 1), n * i : n * (i + 1)], Psym)) # store and get off-diagonal blocks in symmetric matrix for i in range(n - 1): R[n * (i + 1) : n * (i + 2), n * i : n * (i + 1)] = P self.failUnless(llmat_isEqual(R[n * (i + 1) : n * (i + 2), n * i : n * (i + 1)], P)) R[n * (i + 1) : n * (i + 2), n * i : n * (i + 1)] = Psym self.failUnless(llmat_isEqual(R[n * (i + 1) : n * (i + 2), n * i : n * (i + 1)], Psym))