def bragg_structure(seed: tp.Optional[int] = None) -> tp.Iterator[Experiment]:
seedg = create_seed_generator(seed)
recombinable: tp.List[tp.Union[str, ConfiguredOptimizer]] = [
ng.families.EvolutionStrategy(recombination_ratio=0.1, popsize=40).set_name("Pairwise-ES"),
ng.families.DifferentialEvolution(crossover="parametrization").set_name("Param-DE")
]
algos: tp.List[tp.Union[str, ConfiguredOptimizer]] = ["TwoPointsDE", "DE", "CMA", "NaiveTBPSA", "DiagonalCMA"]
algos += [ng.optimizers.ConfiguredPSO().set_name("PSO"), ng.optimizers.ParametrizedOnePlusOne().set_name("1+1")]
func = Photonics("bragg", 80, bounding_method="clipping")
func.parametrization.set_name("layer")
#
func_nostruct = Photonics("bragg", 80, bounding_method="clipping")
func_nostruct.parametrization.set_name("2pt").set_recombination(ng.p.mutation.RavelCrossover()) # type: ignore
#
func_mix = Photonics("bragg", 80, bounding_method="clipping")
param = func_mix.parametrization
param.set_name("mix")
param.set_recombination(ng.p.Choice([ng.p.mutation.Crossover(axis=1), ng.p.mutation.RavelCrossover()])) # type: ignore
muts = ["gaussian", "cauchy", ng.p.mutation.Jumping(axis=1, size=5), ng.p.mutation.Translation(axis=1)]
muts += [ng.p.mutation.LocalGaussian(axes=1, size=10)]
param.set_mutation(custom=ng.p.Choice(muts)) # type: ignore
for budget in [1e3, 1e4, 1e5, 1e6]:
xpseed = next(seedg)
for algo in algos:
yield Experiment(func, algo, int(budget), num_workers=1, seed=xpseed)
for f in [func, func_nostruct, func_mix]:
for algo in recombinable:
yield Experiment(f, algo, int(budget), num_workers=1, seed=xpseed)
def photonics(seed: tp.Optional[int] = None) -> tp.Iterator[Experiment]:
seedg = create_seed_generator(seed)
popsizes = [20, 40, 80]
es = [
ng.families.EvolutionStrategy(recombination_ratio=recomb,
only_offsprings=only,
popsize=pop,
offsprings=pop * 5)
for only in [True, False] for recomb in [0.1, .5] for pop in popsizes
]
algos = [
"TwoPointsDE", "DE", "RealSpacePSO", "PSO", "OnePlusOne",
"ParametrizationDE", "NaiveTBPSA", "SplitOptimizer5", "Shiva", "NGO",
"MultiCMA", "CMandAS2", "SplitOptimizer13"
] + es # type: ignore
for method in ["clipping", "tanh"]: # , "arctan"]:
for name in ["bragg", "chirped", "morpho"]:
func = Photonics(name,
60 if name == "morpho" else 80,
bounding_method=method)
for budget in [1e3, 1e4, 1e5, 1e6]:
for algo in algos:
xp = Experiment(func,
algo,
int(budget),
num_workers=1,
seed=next(seedg))
if not xp.is_incoherent:
yield xp
def photonics(seed: tp.Optional[int] = None) -> Iterator[Experiment]:
seedg = create_seed_generator(seed)
popsizes = [10, 40, 100]
es = [ng.families.EvolutionStrategy(recombination_ratio=recomb, only_offsprings=False, popsize=pop)
for recomb in [0.1, 1] for pop in popsizes]
es += [ng.families.EvolutionStrategy(recombination_ratio=recomb, only_offsprings=only, popsize=pop,
offsprings={10: 20, 40: 60, 100: 150}[pop])
for only in [True, False] for recomb in [0.1, 1] for pop in popsizes]
algos = ["TwoPointsDE", "DE", "PSO", "OnePlusOne", "ParametrizationDE", "NaiveTBPSA"] + es # type: ignore
for method in ["clipping", "tanh", "arctan"]:
# , "chirped"]]: # , "morpho"]]:
for func in [Photonics(x, 60 if x == "morpho" else 80, bounding_method=method) for x in ["bragg"]]:
for budget in [1e2, 1e3, 1e4, 1e5, 1e6]:
for algo in algos:
xp = Experiment(func, algo, int(budget), num_workers=1, seed=next(seedg))
if not xp.is_incoherent:
yield xp