print('')
xx, niter, res, tt = my_gmres("\nGmres restart={0} maxiter={1}",
M, b, tol, restart, maxiter)
ecald = checker('Calderon ', A, J, xx)
etrans = checker('Transmission ', J, X, xx, b)
Ecald.append(ecald)
Etrans.append(etrans)
print('')
print('STF classic', '[{}]'.format(int(M.shape[0] / 2)))
print('')
stf = STF(xtf)
M_stf = stf.get()
b_stf = stf.rhs()
print(M_stf.shape)
zz_stf, niter_stf, res_stf, tt_stf = my_gmres("\nGmres restart={0} maxiter={1}",
M_stf, b_stf, tol, restart, maxiter)
n, = zz_stf.shape
n = int(n/2)
sold_stf, soln_stf = zz_stf[:n], zz_stf[n:]
gui = bem.GridFunction(stf.space, fun=uinc)
uicoeffs = gui.coefficients
print('')
xx, niter, res, tt = my_gmres("\nGmres restart={0} maxiter={1}", M, b, tol,
restart, maxiter)
ecald = checker('Calderon ', A, J, xx)
etrans = checker('Transmission ', J, X, xx, b)
Ecald.append(ecald)
Etrans.append(etrans)
print('')
print('STF classic', '[{}]'.format(int(M.shape[0] / 2)))
print('')
stf = STF(xtf)
M_stf = stf.get()
b_stf = stf.rhs()
print(M_stf.shape)
zz_stf, niter_stf, res_stf, tt_stf = my_gmres(
"\nGmres restart={0} maxiter={1}", M_stf, b_stf, tol, restart, maxiter)
n, = zz_stf.shape
n = int(n / 2)
sold_stf, soln_stf = zz_stf[:n], zz_stf[n:]
gui = bem.GridFunction(stf.space, fun=uinc)
uicoeffs = gui.coefficients
result[0] = -np.exp(1j * kRef * x[1])
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(
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,
