jan/opencl_fdtd
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update to use gridlock >=1.0

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Jan Petykiewicz 2021-10-31 19:47:25 -07:00
parent 4c81f33d05
commit 26ae8578c9
1 changed files with 13 additions and 9 deletions
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fdtd.py
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@ -114,14 +114,17 @@ def main():
# edge_coords = [numpy.arange(-100.5, 101), numpy.arange(-100.5, 101), numpy.arange(-1, 1)]
# #### Create the grid, mask, and draw the device ####
grid = gridlock.Grid(edge_coords, initial=n_air**2, num_grids=3)
# grid.draw_slab(surface_normal=gridlock.Direction.z,
grid = gridlock.Grid(edge_coords)
epsilon = grid.allocate(n_air**2)
# grid.draw_slab(epsilon,
# surface_normal=2,
# center=[0, 0, 0],
# thickness=th,
# eps=n_slab**2)
# mask = perturbed_l3(a, r)
#
# grid.draw_polygons(surface_normal=gridlock.Direction.z,
# grid.draw_polygons(epsilon,
# surface_normal=2,
# center=[0, 0, 0],
# thickness=2 * th,
# eps=n_air**2,
@ -135,7 +138,7 @@ def main():
for a in 'xz' for p in 'np']
#bloch = [{'axis': a, 'real': 1, 'imag': 0} for a in 'x']
bloch = []
sim = Simulation(grid.grids, do_poynting=True, pmls=pmls, bloch_boundaries=bloch)
sim = Simulation(epsilon, do_poynting=True, pmls=pmls, bloch_boundaries=bloch)
# Source parameters and function
w = 2 * numpy.pi * dx / wl
@ -188,7 +191,7 @@ def main():
# e = sim.update_G([e])
e.wait()
S = sim.S.get().reshape(grid.grids.shape) * sim.dt * dx * dx *dx
S = sim.S.get().reshape(epsilon.shape) * sim.dt * dx * dx *dx
m = 30
planes[t] = (
S[0][+pml_thickness+2, :, pml_thickness+3:-pml_thickness-3].sum(),
@ -217,10 +220,10 @@ def main():
# )
Ectr[t] = sim.E[ind].get()
u[t] = pyopencl.array.sum(sim.E * sim.E * sim.eps + h_old * sim.H).get() * dx * dx * dx
ui[t] = (sim.E * sim.E * sim.eps + h_old * sim.H).reshape(grid.grids.shape).get()[:, pml_thickness+m:-pml_thickness-m, :,
pml_thickness+m:-pml_thickness-m].sum() * dx * dx * dx
# ui[t] = (sim.E * sim.E * sim.eps + h_old * sim.H).reshape(grid.grids.shape).get()[:, pml_thickness+m:-pml_thickness-m,
# pml_thickness+m:-pml_thickness-m, :].sum() * dx * dx * dx
ui[t] = (sim.E * sim.E * sim.eps + h_old * sim.H).reshape(epsilon.shape).get()[:, pml_thickness+m:-pml_thickness-m, :,
pml_thickness+m:-pml_thickness-m].sum() * dx * dx * dx
# ui[t] = (sim.E * sim.E * sim.eps + h_old * sim.H).reshape(epsilon.shape).get()[:, pml_thickness+m:-pml_thickness-m,
# pml_thickness+m:-pml_thickness-m, :].sum() * dx * dx * dx
if t % 100 == 0:
logger.info('iteration {}: average {} iterations per sec'.format(t, (t+1)/(time.perf_counter()-start)))
@ -231,6 +234,7 @@ def main():
return meanas.fdmath.unvec(f, grid.shape)
d = {
'grid': grid,
'epsilon': epsilon,
'E': unvec(sim.E.get()),
'H': unvec(sim.H.get()),
'dt': sim.dt,