import importlib import numpy from numpy.linalg import norm import meanas from meanas import vec, unvec from meanas.fdfd import waveguide_mode, functional, scpml from meanas.fdfd.solvers import generic as generic_solver import gridlock from matplotlib import pyplot __author__ = 'Jan Petykiewicz' def test0(solver=generic_solver): dx = 50 # discretization (nm/cell) pml_thickness = 10 # (number of cells) wl = 1550 # Excitation wavelength omega = 2 * numpy.pi / wl # Device design parameters radii = (1, 0.6) th = 220 center = [0, 0, 0] # refractive indices n_ring = numpy.sqrt(12.6) # ~Si n_air = 4.0 # air # Half-dimensions of the simulation grid xyz_max = numpy.array([1.2, 1.2, 0.3]) * 1000 + pml_thickness * dx # Coordinates of the edges of the cells. half_edge_coords = [numpy.arange(dx/2, m + dx, step=dx) for m in xyz_max] edge_coords = [numpy.hstack((-h[::-1], h)) for h in half_edge_coords] # #### Create the grid, mask, and draw the device #### grid = gridlock.Grid(edge_coords, initial=n_air**2, num_grids=3) grid.draw_cylinder(surface_normal=gridlock.Direction.z, center=center, radius=max(radii), thickness=th, eps=n_ring**2, num_points=24) grid.draw_cylinder(surface_normal=gridlock.Direction.z, center=center, radius=min(radii), thickness=th*1.1, eps=n_air ** 2, num_points=24) dxes = [grid.dxyz, grid.autoshifted_dxyz()] for a in (0, 1, 2): for p in (-1, 1): dxes = meanas.scpml.stretch_with_scpml(dxes, axis=a, polarity=p, omega=omega, thickness=pml_thickness) J = [numpy.zeros_like(grid.grids[0], dtype=complex) for _ in range(3)] J[1][15, grid.shape[1]//2, grid.shape[2]//2] = 1e5 ''' Solve! ''' x = solver(J=vec(J), **sim_args) A = functional.e_full(omega, dxes, vec(grid.grids)).tocsr() b = -1j * omega * vec(J) print('Norm of the residual is ', norm(A @ x - b)) E = unvec(x, grid.shape) ''' Plot results ''' pyplot.figure() pyplot.pcolor(numpy.real(E[1][:, :, grid.shape[2]//2]), cmap='seismic') pyplot.axis('equal') pyplot.show() def test1(solver=generic_solver): dx = 40 # discretization (nm/cell) pml_thickness = 10 # (number of cells) wl = 1550 # Excitation wavelength omega = 2 * numpy.pi / wl # Device design parameters w = 600 th = 220 center = [0, 0, 0] # refractive indices n_wg = numpy.sqrt(12.6) # ~Si n_air = 1.0 # air # Half-dimensions of the simulation grid xyz_max = numpy.array([0.8, 0.9, 0.6]) * 1000 + (pml_thickness + 2) * dx # Coordinates of the edges of the cells. half_edge_coords = [numpy.arange(dx/2, m + dx/2, step=dx) for m in xyz_max] edge_coords = [numpy.hstack((-h[::-1], h)) for h in half_edge_coords] # #### Create the grid and draw the device #### grid = gridlock.Grid(edge_coords, initial=n_air**2, num_grids=3) grid.draw_cuboid(center=center, dimensions=[8e3, w, th], eps=n_wg**2) dxes = [grid.dxyz, grid.autoshifted_dxyz()] for a in (0, 1, 2): for p in (-1, 1): dxes = scpml.stretch_with_scpml(dxes,omega=omega, axis=a, polarity=p, thickness=pml_thickness) half_dims = numpy.array([10, 20, 15]) * dx dims = [-half_dims, half_dims] dims[1][0] = dims[0][0] ind_dims = (grid.pos2ind(dims[0], which_shifts=None).astype(int), grid.pos2ind(dims[1], which_shifts=None).astype(int)) wg_args = { 'omega': omega, 'slices': [slice(i, f+1) for i, f in zip(*ind_dims)], 'dxes': dxes, 'axis': 0, 'polarity': +1, } wg_results = waveguide_mode.solve_waveguide_mode(mode_number=0, **wg_args, epsilon=grid.grids) J = waveguide_mode.compute_source(**wg_args, **wg_results) H_overlap = waveguide_mode.compute_overlap_e(**wg_args, **wg_results) pecg = gridlock.Grid(edge_coords, initial=0.0, num_grids=3) # pecg.draw_cuboid(center=[700, 0, 0], dimensions=[80, 1e8, 1e8], eps=1) # pecg.visualize_isosurface() pmcg = gridlock.Grid(edge_coords, initial=0.0, num_grids=3) # pmcg.draw_cuboid(center=[700, 0, 0], dimensions=[80, 1e8, 1e8], eps=1) # pmcg.visualize_isosurface() ''' Solve! ''' sim_args = { 'omega': omega, 'dxes': dxes, 'epsilon': vec(grid.grids), 'pec': vec(pecg.grids), 'pmc': vec(pmcg.grids), } x = solver(J=vec(J), **sim_args) b = -1j * omega * vec(J) A = operators.e_full(**sim_args).tocsr() print('Norm of the residual is ', norm(A @ x - b)) E = unvec(x, grid.shape) ''' Plot results ''' def pcolor(v): vmax = numpy.max(numpy.abs(v)) pyplot.pcolor(v, cmap='seismic', vmin=-vmax, vmax=vmax) pyplot.axis('equal') pyplot.colorbar() center = grid.pos2ind([0, 0, 0], None).astype(int) pyplot.figure() pyplot.subplot(2, 2, 1) pcolor(numpy.real(E[1][center[0], :, :])) pyplot.subplot(2, 2, 2) pyplot.plot(numpy.log10(numpy.abs(E[1][:, center[1], center[2]]) + 1e-10)) pyplot.subplot(2, 2, 3) pcolor(numpy.real(E[1][:, :, center[2]])) pyplot.subplot(2, 2, 4) def poyntings(E): e = vec(E) h = operators.e2h(omega, dxes) @ e cross1 = operators.poynting_e_cross(e, dxes) @ h.conj() cross2 = operators.poynting_h_cross(h.conj(), dxes) @ e s1 = unvec(0.5 * numpy.real(cross1), grid.shape) s2 = unvec(0.5 * numpy.real(-cross2), grid.shape) return s1, s2 s1x, s2x = poyntings(E) pyplot.plot(s1x[0].sum(axis=2).sum(axis=1)) pyplot.plot(s2x[0].sum(axis=2).sum(axis=1)) pyplot.show() q = [] for i in range(-5, 30): H_rolled = [numpy.roll(h, i, axis=0) for h in H_overlap] q += [numpy.abs(vec(E) @ vec(H_rolled))] pyplot.figure() pyplot.plot(q) pyplot.title('Overlap with mode') pyplot.show() print('Average overlap with mode:', sum(q)/len(q)) def module_available(name): return importlib.util.find_spec(name) is not None if __name__ == '__main__': # test0() if module_available('opencl_fdfd'): from opencl_fdfd import cg_solver as opencl_solver test1(opencl_solver) # from opencl_fdfd.csr import fdfd_cg_solver as opencl_csr_solver # test1(opencl_csr_solver) # elif module_available('magma_fdfd'): # from magma_fdfd import solver as magma_solver # test1(magma_solver) else: test1()