shape = mtf.shape
size, _ = shape
Size.append(size)
A = 2.0 * At
A2 = A * iJ * A
Ce = 0.5 * J - At
Ci = 0.5 * J + At
Ce2 = Ce * iJ * Ce
Ci2 = Ci * iJ * Ci
x = np.random.rand(shape[0]) + 1j * np.random.rand(shape[0])
b = mtf.rhs(dir_data, neu_data)
M = A - X
print('')
print(nlambda, mtf.shape, flush=True)
print('')
checker('A2 = J', A2, J, x)
checker('exterior Proj.', Ce2, Ce, x)
checker('interior Proj.', Ci2, Ci, x)
checker('error-Calderon with random [no-sense]', A, J, x)
print('')
print('MTF classic', M.shape)
print('')
shape = mtf.shape
size, _ = shape
Size.append(size)
A = 2.0 * At
A2 = A * iJ * A
Ce = 0.5 * J - At
Ci = 0.5 * J + At
Ce2 = Ce * iJ * Ce
Ci2 = Ci * iJ * Ci
x = np.random.rand(shape[0]) + 1j * np.random.rand(shape[0])
b = mtf.rhs(dir_data, neu_data)
M = A - X
print('')
print(nlambda, mtf.shape, flush=True)
print('')
checker('A2 = J', A2, J, x)
checker('exterior Proj.', Ce2, Ce, x)
checker('interior Proj.', Ci2, Ci, x)
checker('error-Calderon with random [no-sense]', A, J, x)
print('')
print('MTF classic', M.shape)
print('')
def neu_data(x, normal, dom_ind, result):
result[0] = -1j * normal[1] * kRef * np.exp(1j * kRef * x[1])
xtf = xTF(kRef, n)
xtf.setRHS(dir_data, neu_data)
space = xtf.space
shape = xtf.shape
fd, fn = xtf.getDir(), xtf.getNeu()
fdir, fneu = xtf.getGFdir(), xtf.getGFneu()
STF, MTF = STF(xtf), MTF(xtf)
stf, rhs_stf = STF.get(), STF.rhs()
mtf, rhs_mtf = MTF.get(), MTF.rhs()
x_stf = solve(stf, rhs_stf)
xd_stf, xn_stf = x_stf[0:shape], x_stf[shape:]
x_mtf = solve(mtf, rhs_mtf)
xd_mtf, xn_mtf = x_mtf[0:shape], x_mtf[shape:2 * shape]
yd_mtf, yn_mtf = x_mtf[2 * shape:3 * shape], x_mtf[3 * shape:4 * shape]
print('')
print('l2 norm (relative)')
print(la.norm(xd_mtf - xd_stf), la.norm(xn_mtf - xn_stf))
print(
la.norm(xd_mtf - yd_mtf - fd) / la.norm(xd_mtf),
la.norm(-xn_mtf - yn_mtf - fn) / la.norm(xn_mtf))
def neu_data(x, normal, dom_ind, result):
result[0] = -1j * normal[1] * kRef * np.exp( 1j * kRef * x[1])
xtf = xTF(kRef, n)
xtf.setRHS(dir_data, neu_data)
space = xtf.space
shape = xtf.shape
fd, fn = xtf.getDir(), xtf.getNeu()
fdir, fneu = xtf.getGFdir(), xtf.getGFneu()
STF, MTF = STF(xtf), MTF(xtf)
stf, rhs_stf = STF.get(), STF.rhs()
mtf, rhs_mtf = MTF.get(), MTF.rhs()
rescaleRes = lambda res, P, rhs: res / la.norm(P(rhs))
print('\nSTF restart={0} maxiter={1}'.format(restart, maxiter), flush=True)
Mat, b = stf, rhs_stf
print('size: ', stf.shape, 2*shape)
del res
res = []
tt = time()
x_stf, info = gmres(Mat, b,
orthog='mgs',
tol=tol,
residuals=res,
