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Animate2D for OptimizationProblem #2186

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merged 9 commits into from
Sep 1, 2022
+39,996 −1,491
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Animate2D for OptimizationProblem #2186

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e577213
return eps array if ax=None
thomasdorch Aug 2, 2022
4e12834
plot/update eps and/or fields in Animate2D
thomasdorch Aug 2, 2022
4184c0c
add step_funcs to OptimizationProblem
thomasdorch Aug 4, 2022
4d31ceb
make step_funcs default to empty list
thomasdorch Aug 4, 2022
716d35c
set Animate2D 'sim' argument default value to None
thomasdorch Aug 4, 2022
ce3b42f
fix visualization tests
thomasdorch Aug 11, 2022
ecd1710
enable Animate2D in Jupyter notebooks
thomasdorch Aug 13, 2022
b2b3eb0
use ion/ioff to prevent duplicate figures in notebooks
thomasdorch Aug 13, 2022
36cf445
update adjoint tutorial 3 with animated plot
thomasdorch Aug 14, 2022
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18 changes: 13 additions & 5 deletions python/adjoint/optimization_problem.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,8 +37,9 @@ def __init__(
minimum_run_time=0,
maximum_run_time=None,
finite_difference_step=utils.FD_DEFAULT,
step_funcs: list = None,
):

self.step_funcs = step_funcs if step_funcs is not None else []
self.sim = simulation

if isinstance(objective_functions, list):
Expand Down Expand Up @@ -184,15 +185,17 @@ def forward_run(self):
if any(isinstance(m, LDOS) for m in self.objective_arguments):
self.sim.run(
mp.dft_ldos(self.frequencies),
*self.step_funcs,
until_after_sources=mp.stop_when_dft_decayed(
self.decay_by, self.minimum_run_time, self.maximum_run_time
),
)
else:
self.sim.run(
*self.step_funcs,
until_after_sources=mp.stop_when_dft_decayed(
self.decay_by, self.minimum_run_time, self.maximum_run_time
)
),
)

# record objective quantities from user specified monitors
Expand Down Expand Up @@ -254,9 +257,10 @@ def adjoint_run(self):

# Adjoint run
self.sim.run(
*self.step_funcs,
until_after_sources=mp.stop_when_dft_decayed(
self.decay_by, self.minimum_run_time, self.maximum_run_time
)
),
)

# reset the m number
Expand Down Expand Up @@ -376,15 +380,17 @@ def calculate_fd_gradient(
if any(isinstance(m, LDOS) for m in self.objective_arguments):
self.sim.run(
mp.dft_ldos(self.frequencies),
*self.step_funcs,
until_after_sources=mp.stop_when_energy_decayed(
dt=1, decay_by=1e-11
),
)
else:
self.sim.run(
*self.step_funcs,
until_after_sources=mp.stop_when_dft_decayed(
self.decay_by, self.minimum_run_time, self.maximum_run_time
)
),
)

# record final objective function value
Expand All @@ -409,15 +415,17 @@ def calculate_fd_gradient(
if any(isinstance(m, LDOS) for m in self.objective_arguments):
self.sim.run(
mp.dft_ldos(self.frequencies),
*self.step_funcs,
until_after_sources=mp.stop_when_energy_decayed(
dt=1, decay_by=1e-11
),
)
else:
self.sim.run(
*self.step_funcs,
until_after_sources=mp.stop_when_dft_decayed(
self.decay_by, self.minimum_run_time, self.maximum_run_time
)
),
)

# record final objective function value
Expand Down
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