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Check tournament_size <= n_parents in hl_api #268

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Jan 6, 2021
Merged

Check tournament_size <= n_parents in hl_api #268

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e2c36fe
Check tournament_size <= n_parents in _create_new_offspring_generation
HenrikMettler Jan 5, 2021
811df3e
Provide default value to tournament size
HenrikMettler Jan 6, 2021
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13 changes: 10 additions & 3 deletions cgp/ea/mu_plus_lambda.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,8 +20,8 @@ class MuPlusLambda:
def __init__(
self,
n_offsprings: int,
tournament_size: int,
*,
tournament_size: Union[None, int] = None,
n_processes: int = 1,
local_search: Callable[[IndividualBase], None] = lambda combined: None,
k_local_search: Union[int, None] = None,
Expand All @@ -34,8 +34,8 @@ def __init__(
----------
n_offsprings : int
Number of offspring in each iteration.
tournament_size : int
Tournament size in each iteration.
tournament_size : int, optional
Tournament size in each iteration. Defaults to the number of parents in the population
n_processes : int, optional
Number of parallel processes to be used. If greater than 1,
parallel evaluation of the objective is supported. Defaults to 1.
Expand Down Expand Up @@ -159,6 +159,13 @@ def step(
def _create_new_offspring_generation(self, pop: Population) -> List[IndividualBase]:
# use tournament selection to randomly select individuals from
# parent population

if self.tournament_size is None:
self.tournament_size = pop.n_parents

if self.tournament_size > pop.n_parents:
raise ValueError("tournament_size must be less or equal n_parents")

offsprings: List[IndividualBase] = []
while len(offsprings) < self.n_offsprings:
tournament_pool = pop.rng.permutation(pop.parents)[: self.tournament_size]
Expand Down
1 change: 0 additions & 1 deletion examples/example_hurdles.py
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Expand Up @@ -127,7 +127,6 @@ def objective_two(individual):
# the (n+1)th objective by a list of numbers between 0 and 1.
ea_params = {
"n_offsprings": 4,
"tournament_size": 2,
"n_processes": 1,
"hurdle_percentile": [0.5, 0.0],
}
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2 changes: 1 addition & 1 deletion examples/example_minimal.py
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Expand Up @@ -81,7 +81,7 @@ def objective(individual):
"primitives": (cgp.Add, cgp.Sub, cgp.Mul, cgp.ConstantFloat),
}

ea_params = {"n_offsprings": 4, "tournament_size": 2, "n_processes": 2}
ea_params = {"n_offsprings": 4, "n_processes": 2}

evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 0.0}

Expand Down
2 changes: 1 addition & 1 deletion examples/example_multi_genome.py
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Expand Up @@ -82,7 +82,7 @@ def objective(individual):
}
genome_params = [single_genome_params, single_genome_params]

ea_params = {"n_offsprings": 4, "tournament_size": 2, "n_processes": 1}
ea_params = {"n_offsprings": 4, "n_processes": 1}

evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 0.0}

Expand Down
2 changes: 1 addition & 1 deletion examples/example_piecewise_target_function.py
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Expand Up @@ -89,7 +89,7 @@ def objective(individual, rng):
"primitives": (cgp.IfElse, cgp.Mul, cgp.Add, cgp.Sub, cgp.ConstantFloat,),
}

ea_params = {"n_offsprings": 4, "tournament_size": 2, "n_processes": 2}
ea_params = {"n_offsprings": 4, "n_processes": 2}

evolve_params = {"max_generations": int(args["--max-generations"]), "min_fitness": 0.0}

Expand Down
3 changes: 1 addition & 2 deletions examples/example_reorder.py
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Expand Up @@ -85,10 +85,9 @@ def objective(individual):
"primitives": (cgp.Add, cgp.Sub, cgp.Mul, cgp.ConstantFloat),
}

ea_params = {"n_offsprings": 4, "tournament_size": 2, "n_processes": 2}
ea_params = {"n_offsprings": 4, "n_processes": 2}
ea_params_with_reorder = {
"n_offsprings": 4,
"tournament_size": 2,
"n_processes": 2,
"reorder_genome": True,
}
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2 changes: 1 addition & 1 deletion test/test_ea_mu_plus_lambda.py
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Expand Up @@ -71,9 +71,9 @@ def objective(ind):
return ind

population_params["n_parents"] = 1

pop = cgp.Population(**population_params, genome_params=genome_params)

ea_params["tournament_size"] = 1
ea = cgp.ea.MuPlusLambda(**ea_params)
ea.initialize_fitness_parents(pop, objective)

Expand Down