def discrete(seed: Optional[int] = None) -> Iterator[Experiment]:
"""Discrete test bed, including useless variables, 5 values or 2 values per character.
Poorly designed, should be reimplemented from scratch using a decent instrumentation."""
seedg = create_seed_generator(seed)
names = [
n for n in ArtificialFunction.list_sorted_function_names()
if "one" in n or "jump" in n
]
optims = ["NGO", "Shiva", "DiagonalCMA", "CMA"] + sorted(
x for x, y in ng.optimizers.registry.items()
if "andomSearch" in x or ("iscrete" in x and "epea" not in x
and "DE" not in x and "SSNEA" not in x))
# Block dimension = dimension of a block on which the function "name" is applied. There are several blocks,
# and possibly useless variables; so the total dimension is num_blocks * block_dimension * (1+ uv_factor).
functions = [
ArtificialFunction(name,
block_dimension=bd,
num_blocks=n_blocks,
useless_variables=bd * uv_factor * n_blocks)
for name in names for bd in [5, 30, 180] for uv_factor in [0, 5, 10]
for n_blocks in [1]
]
for func in functions:
for optim in optims:
for budget in [
100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100,
1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 2100,
2200, 2300, 2400, 2500, 2600, 2700, 2800, 2900, 3000
]: # , 10000]:
yield Experiment(func,
optim,
budget=budget,
num_workers=1,
seed=next(seedg))
def discrete2(seed: Optional[int] = None) -> Iterator[Experiment]:
"""Discrete test bed, including useless variables, binary only.
Poorly designed, should be reimplemented from scratch using a decent instrumentation."""
seedg = create_seed_generator(seed)
names = [
n for n in ArtificialFunction.list_sorted_function_names()
if ("one" in n or "jump" in n) and ("5" not in n) and ("hard" in n)
]
optims = ["NGO", "Shiva", "DiagonalCMA", "CMA"
] + sorted(x for x, y in ng.optimizers.registry.items()
if "andomSearch" in x or "PBIL" in x or "cGA" in x or
("iscrete" in x and "epea" not in x and "DE" not in x
and "SSNEA" not in x))
functions = [
ArtificialFunction(name,
block_dimension=bd,
num_blocks=n_blocks,
useless_variables=bd * uv_factor * n_blocks)
for name in names for bd in [5, 30, 180] for uv_factor in [0, 5, 10]
for n_blocks in [1]
]
for func in functions:
for optim in optims:
for nw in [1, 10]:
for budget in [
100, 200, 300, 400, 500, 600, 700, 800, 900, 1000,
1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900,
2000, 2100, 2200, 2300, 2400, 2500, 2600, 2700, 2800,
2900, 3000
]: # , 10000]:
yield Experiment(func,
optim,
budget=budget,
num_workers=nw,
seed=next(seedg))
