misc example updates
This commit is contained in:
parent
be647658d3
commit
7e8ff23356
2 changed files with 103 additions and 72 deletions
|
|
@ -1,4 +1,5 @@
|
|||
import importlib
|
||||
import logging
|
||||
import numpy
|
||||
from numpy.linalg import norm
|
||||
from matplotlib import pyplot, colors
|
||||
|
|
@ -6,12 +7,14 @@ import logging
|
|||
|
||||
import meanas
|
||||
from meanas import fdtd
|
||||
from meanas.fdmath import vec, unvec
|
||||
from meanas.fdmath import vec, unvec, fdfield_t
|
||||
from meanas.fdfd import waveguide_3d, functional, scpml, operators
|
||||
from meanas.fdfd.solvers import generic as generic_solver
|
||||
|
||||
import gridlock
|
||||
|
||||
from matplotlib import pyplot
|
||||
|
||||
|
||||
logging.basicConfig(level=logging.DEBUG)
|
||||
logging.getLogger('matplotlib').setLevel(logging.WARNING)
|
||||
|
|
|
|||
140
examples/fdtd.py
140
examples/fdtd.py
|
|
@ -1,18 +1,25 @@
|
|||
"""
|
||||
Example code for running an OpenCL FDTD simulation
|
||||
Example code for running an FDTD simulation
|
||||
|
||||
See main() for simulation setup.
|
||||
"""
|
||||
|
||||
import sys
|
||||
import time
|
||||
import copy
|
||||
|
||||
import numpy
|
||||
import h5py
|
||||
from numpy.linalg import norm
|
||||
|
||||
from meanas import fdtd
|
||||
from meanas.fdtd import cpml_params, updates_with_cpml
|
||||
from masque import Pattern, shapes
|
||||
from meanas.fdtd.misc import gaussian_packet
|
||||
|
||||
from meanas.fdfd.operators import e_full
|
||||
from meanas.fdfd.scpml import stretch_with_scpml
|
||||
from meanas.fdmath import vec
|
||||
from masque import Pattern, Circle, Polygon
|
||||
import gridlock
|
||||
import pcgen
|
||||
|
||||
|
|
@ -41,8 +48,7 @@ def perturbed_l3(a: float, radius: float, **kwargs) -> Pattern:
|
|||
`masque.Pattern` object containing the L3 design
|
||||
"""
|
||||
|
||||
default_args = {'hole_dose': 1,
|
||||
'trench_dose': 1,
|
||||
default_args = {
|
||||
'hole_layer': 0,
|
||||
'trench_layer': 1,
|
||||
'shifts_a': (0.15, 0, 0.075),
|
||||
|
|
@ -53,38 +59,40 @@ def perturbed_l3(a: float, radius: float, **kwargs) -> Pattern:
|
|||
}
|
||||
kwargs = {**default_args, **kwargs}
|
||||
|
||||
xyr = pcgen.l3_shift_perturbed_defect(mirror_dims=kwargs['xy_size'],
|
||||
xyr = pcgen.l3_shift_perturbed_defect(
|
||||
mirror_dims=kwargs['xy_size'],
|
||||
perturbed_radius=kwargs['perturbed_radius'],
|
||||
shifts_a=kwargs['shifts_a'],
|
||||
shifts_r=kwargs['shifts_r'])
|
||||
shifts_r=kwargs['shifts_r'],
|
||||
)
|
||||
xyr *= a
|
||||
xyr[:, 2] *= radius
|
||||
|
||||
pat = Pattern()
|
||||
pat.name = f'L3p-a{a:g}r{radius:g}rp{kwargs["perturbed_radius"]:g}'
|
||||
pat.shapes += [shapes.Circle(radius=r, offset=(x, y),
|
||||
dose=kwargs['hole_dose'],
|
||||
layer=kwargs['hole_layer'])
|
||||
#pat.name = f'L3p-a{a:g}r{radius:g}rp{kwargs["perturbed_radius"]:g}'
|
||||
pat.shapes[(kwargs['hole_layer'], 0)] += [
|
||||
Circle(radius=r, offset=(x, y))
|
||||
for x, y, r in xyr]
|
||||
|
||||
maxes = numpy.max(numpy.fabs(xyr), axis=0)
|
||||
pat.shapes += [shapes.Polygon.rectangle(
|
||||
pat.shapes[(kwargs['trench_layer'], 0)] += [
|
||||
Polygon.rectangle(
|
||||
lx=(2 * maxes[0]), ly=kwargs['trench_width'],
|
||||
offset=(0, s * (maxes[1] + a + kwargs['trench_width'] / 2)),
|
||||
dose=kwargs['trench_dose'], layer=kwargs['trench_layer'])
|
||||
offset=(0, s * (maxes[1] + a + kwargs['trench_width'] / 2))
|
||||
)
|
||||
for s in (-1, 1)]
|
||||
return pat
|
||||
|
||||
|
||||
def main():
|
||||
dtype = numpy.float32
|
||||
max_t = 8000 # number of timesteps
|
||||
max_t = 3600 # number of timesteps
|
||||
|
||||
dx = 40 # discretization (nm/cell)
|
||||
pml_thickness = 8 # (number of cells)
|
||||
|
||||
wl = 1550 # Excitation wavelength and fwhm
|
||||
dwl = 200
|
||||
dwl = 100
|
||||
|
||||
# Device design parameters
|
||||
xy_size = numpy.array([10, 10])
|
||||
|
|
@ -107,69 +115,89 @@ def main():
|
|||
|
||||
# #### Create the grid, mask, and draw the device ####
|
||||
grid = gridlock.Grid(edge_coords)
|
||||
epsilon = grid.allocate(n_air**2, dtype=dtype)
|
||||
grid.draw_slab(epsilon,
|
||||
surface_normal=2,
|
||||
center=[0, 0, 0],
|
||||
thickness=th,
|
||||
eps=n_slab**2)
|
||||
epsilon = grid.allocate(n_air ** 2, dtype=dtype)
|
||||
grid.draw_slab(
|
||||
epsilon,
|
||||
slab = dict(axis='z', center=0, span=th),
|
||||
foreground = n_slab ** 2,
|
||||
)
|
||||
|
||||
mask = perturbed_l3(a, r)
|
||||
grid.draw_polygons(
|
||||
epsilon,
|
||||
slab = dict(axis='z', center=0, span=2 * th),
|
||||
foreground = n_air ** 2,
|
||||
offset2d = (0, 0),
|
||||
polygons = mask.as_polygons(library=None),
|
||||
)
|
||||
|
||||
grid.draw_polygons(epsilon,
|
||||
surface_normal=2,
|
||||
center=[0, 0, 0],
|
||||
thickness=2 * th,
|
||||
eps=n_air**2,
|
||||
polygons=mask.as_polygons())
|
||||
print(f'{grid.shape=}')
|
||||
|
||||
print(grid.shape)
|
||||
|
||||
dt = .99/numpy.sqrt(3)
|
||||
e = [numpy.zeros_like(epsilon[0], dtype=dtype) for _ in range(3)]
|
||||
h = [numpy.zeros_like(epsilon[0], dtype=dtype) for _ in range(3)]
|
||||
dt = dx * 0.99 / numpy.sqrt(3)
|
||||
ee = numpy.zeros_like(epsilon, dtype=dtype)
|
||||
hh = numpy.zeros_like(epsilon, dtype=dtype)
|
||||
|
||||
dxes = [grid.dxyz, grid.autoshifted_dxyz()]
|
||||
|
||||
# PMLs in every direction
|
||||
pml_params = [[cpml_params(axis=dd, polarity=pp, dt=dt,
|
||||
thickness=pml_thickness, epsilon_eff=1.0**2)
|
||||
pml_params = [
|
||||
[cpml_params(axis=dd, polarity=pp, dt=dt, thickness=pml_thickness, epsilon_eff=n_air ** 2)
|
||||
for pp in (-1, +1)]
|
||||
for dd in range(3)]
|
||||
update_E, update_H = updates_with_cpml(cpml_params=pml_params, dt=dt,
|
||||
dxes=dxes, epsilon=epsilon)
|
||||
update_E, update_H = updates_with_cpml(cpml_params=pml_params, dt=dt, dxes=dxes, epsilon=epsilon)
|
||||
|
||||
# sample_interval = numpy.floor(1 / (2 * 1 / wl * dt)).astype(int)
|
||||
# print(f'Save time interval would be {sample_interval} * dt = {sample_interval * dt:3g}')
|
||||
|
||||
|
||||
# Source parameters and function
|
||||
w = 2 * numpy.pi * dx / wl
|
||||
fwhm = dwl * w * w / (2 * numpy.pi * dx)
|
||||
alpha = (fwhm ** 2) / 8 * numpy.log(2)
|
||||
delay = 7/numpy.sqrt(2 * alpha)
|
||||
source_phasor, _delay = gaussian_packet(wl=wl, dwl=100, dt=dt, turn_on=1e-5)
|
||||
aa, cc, ss = source_phasor(numpy.arange(max_t))
|
||||
srca_real = aa * cc
|
||||
src_maxt = numpy.argwhere(numpy.diff(aa < 1e-5))[-1]
|
||||
assert aa[src_maxt - 1] >= 1e-5
|
||||
phasor_norm = dt / (aa * cc * cc).sum()
|
||||
|
||||
def field_source(i):
|
||||
t0 = i * dt - delay
|
||||
return numpy.sin(w * t0) * numpy.exp(-alpha * t0**2)
|
||||
Jph = numpy.zeros_like(epsilon, dtype=complex)
|
||||
Jph[1, *(grid.shape // 2)] = epsilon[1, *(grid.shape // 2)]
|
||||
Eph = numpy.zeros_like(Jph)
|
||||
|
||||
# #### Run a bunch of iterations ####
|
||||
output_file = h5py.File('simulation_output.h5', 'w')
|
||||
start = time.perf_counter()
|
||||
for t in range(max_t):
|
||||
update_E(e, h, epsilon)
|
||||
for tt in range(max_t):
|
||||
update_E(ee, hh, epsilon)
|
||||
|
||||
e[1][tuple(grid.shape//2)] += field_source(t)
|
||||
update_H(e, h)
|
||||
if tt < src_maxt:
|
||||
ee[1, *(grid.shape // 2)] -= srca_real[tt]
|
||||
update_H(ee, hh)
|
||||
|
||||
avg_rate = (t + 1)/(time.perf_counter() - start))
|
||||
print(f'iteration {t}: average {avg_rate} iterations per sec')
|
||||
avg_rate = (tt + 1) / (time.perf_counter() - start)
|
||||
sys.stdout.flush()
|
||||
|
||||
if t % 20 == 0:
|
||||
r = sum([(f * f * e).sum() for f, e in zip(e, epsilon)])
|
||||
print('E sum', r)
|
||||
if tt % 200 == 0:
|
||||
print(f'iteration {tt}: average {avg_rate} iterations per sec')
|
||||
E_energy_sum = (ee * ee * epsilon).sum()
|
||||
print(f'{E_energy_sum=}')
|
||||
|
||||
# Save field slices
|
||||
if (t % 20 == 0 and (max_t - t <= 1000 or t <= 2000)) or t == max_t-1:
|
||||
print('saving E-field')
|
||||
for j, f in enumerate(e):
|
||||
output_file['/E{}_t{}'.format('xyz'[j], t)] = f[:, :, round(f.shape[2]/2)]
|
||||
if (tt % 20 == 0 and (max_t - tt <= 1000 or tt <= 2000)) or tt == max_t - 1:
|
||||
print(f'saving E-field at iteration {tt}')
|
||||
output_file[f'/E_t{tt}'] = ee[:, :, :, ee.shape[3] // 2]
|
||||
|
||||
Eph += (cc[tt] - 1j * ss[tt]) * phasor_norm * ee
|
||||
|
||||
omega = 2 * numpy.pi / wl
|
||||
Eph *= numpy.exp(-1j * dt / 2 * omega)
|
||||
b = -1j * omega * Jph
|
||||
dxes_fdfd = copy.deepcopy(dxes)
|
||||
for pp in (-1, +1):
|
||||
for dd in range(3):
|
||||
stretch_with_scpml(dxes_fdfd, axis=dd, polarity=pp, omega=omega, epsilon_effective=n_air ** 2, thickness=pml_thickness)
|
||||
A = e_full(omega=omega, dxes=dxes, epsilon=epsilon)
|
||||
residual = norm(A @ vec(ee) - vec(b)) / norm(vec(b))
|
||||
print(f'FDFD residual is {residual}')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue