[examples/fdfd] split fdfd example into two files

examples/fdfd0.py

@@ -0,0 +1,103 @@
+import numpy
+from numpy.linalg import norm
+from matplotlib import pyplot, colors
+import logging
+
+import meanas
+from meanas import fdtd
+from meanas.fdmath import vec, unvec
+from meanas.fdfd import waveguide_3d, functional, scpml, operators
+from meanas.fdfd.solvers import generic as generic_solver
+
+import gridlock
+
+
+logging.basicConfig(level=logging.DEBUG)
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+
+__author__ = 'Jan Petykiewicz'
+
+
+def pcolor(ax, v) -> None:
+    mappable = ax.pcolor(v, cmap='seismic', norm=colors.CenteredNorm())
+    ax.axis('equal')
+    ax.get_figure().colorbar(mappable)
+
+
+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)
+    epsilon = grid.allocate(n_air**2, dtype=numpy.float32)
+    grid.draw_cylinder(
+        epsilon,
+        h = dict(axis='z', center=center[2], span=th),
+        radius = max(radii),
+        center2d = center[:2],
+        foreground = n_ring ** 2,
+        num_points = 24,
+        )
+    grid.draw_cylinder(
+        epsilon,
+        h = dict(axis='z', center=center[2], span=th * 1.1),
+        radius = min(radii),
+        center2d = center[:2],
+        foreground = 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.fdfd.scpml.stretch_with_scpml(dxes, axis=a, polarity=p, omega=omega,
+                                                        thickness=pml_thickness)
+
+    J = [numpy.zeros_like(epsilon[0], dtype=complex) for _ in range(3)]
+    J[1][15, grid.shape[1]//2, grid.shape[2]//2] = 1
+
+
+    #
+    # Solve!
+    #
+    sim_args = dict(
+        omega = omega,
+        dxes = dxes,
+        epsilon = vec(epsilon),
+        )
+    x = solver(J=vec(J), **sim_args)
+
+    A = operators.e_full(omega, dxes, vec(epsilon)).tocsr()
+    b = -1j * omega * vec(J)
+    print('Norm of the residual is ', norm(A @ x - b) / norm(b))
+
+    E = unvec(x, grid.shape)
+
+    #
+    # Plot results
+    #
+    grid.visualize_slice(E.real, plane=dict(z=0), which_shifts=1, pcolormesh_args=dict(norm=colors.CenteredNorm(), cmap='bwr'))
+
+
+if __name__ == '__main__':
+    test0()