(P[0] * P[3] + P[1] * P[2])
xInVec = xIn.reshape((L * M * N, 1), order='F')
idx_all = np.ones((L, M, N), dtype=bool)
# def mvp(x):
# 'Matrix-vector product operator'
# return mvp_volume_potential(x, circ_op, idx, Mr)
# Voxel permittivities for volume potential (all ones)
Mr_vol_pot = np.ones((L, M, N), dtype=np.complex128)
# Perform matrix-vector product
start = time.time()
# P_inc[i_harm] = mvp(xInVec).reshape(L, M, N, order='F')
P_inc[i_harm] = mvp_volume_potential(xInVec, circ_op, idx_all, Mr_vol_pot)\
.reshape(L, M, N, order='F')
# New Mr and Mr_box at new frequency
Mr_box[idx_scat_box] = refInd2**2 - 1
Mr[idx_scat] = refInd2**2 - 1
# Solve scattering problem
sol, J, u_sca = vie_solver(Mr_box, r_box, idx_scat_box,
P_inc[i_harm][idx_scat], k2)
# Evaluate scattered field in total domain
# Toeplitz operator
T = k2**2 * volume_potential(k2, r)
# Circulant embedding of Toeplitz operator
circ = circulant_embed_fftw(T, L, M, N)
def mvp(x):
'Matrix-vector product operator'
return mvp_volume_potential(x, circ_op, idx, Mr)