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Refactoring the code to check for duplicate pokemon into the outer crossover loop #60

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merged 3 commits into from
Jun 28, 2023
Merged

Refactoring the code to check for duplicate pokemon into the outer crossover loop #60

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cec4553
make a couple of refactors
phinate Jun 28, 2023
60498d1
make a couple of refactors
phinate Jun 28, 2023
ef2c6de
fix
phinate Jun 28, 2023
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102 changes: 36 additions & 66 deletions src/p2lab/genetic/operations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -104,6 +104,24 @@ def crossover_fn(
allow_all=allow_all,
**kwargs,
)
team1_names = [p.formatted.split("|")[0] for p in team1_pokemon]
team2_names = [p.formatted.split("|")[0] for p in team2_pokemon]

while (len(set(team1_names)) != len(team1_names)) or (
len(set(team2_names)) != len(team2_names)
):
print(
"Found duplicate pokemon in new team from crossover, resampling..."
)
team1_pokemon, team2_pokemon = crossover_method(
team1=team1_pokemon,
team2=team2_pokemon,
num_pokemon=num_pokemon,
allow_all=allow_all,
**kwargs,
)
team1_names = [p.formatted.split("|")[0] for p in team1_pokemon]
team2_names = [p.formatted.split("|")[0] for p in team2_pokemon]

# Build new teams
team1_new = Team(pokemon=team1_pokemon)
Expand Down Expand Up @@ -260,30 +278,10 @@ def sample_swap(
)

team1_pokemon = population[team1_indices]
team1_names = [p.formatted.split("|")[0] for p in team1_pokemon]

# Get indices for team 2, which are just the indices not in team 1
team2_indices = list(set(indices) - set(team1_indices))
team2_pokemon = population[team2_indices]
team2_names = [p.formatted.split("|")[0] for p in team2_pokemon]

# ensure we don't sample the same pokemon twice on either team
while len(set(team1_names)) != len(team1_names) or len(set(team2_names)) != len(
team2_names
):
print("Found duplicate pokemon, resampling...")
team1_indices = np.random.choice(
indices,
size=num_pokemon,
replace=False,
)

team1_pokemon = population[team1_indices]
team1_names = [p.formatted.split("|")[0] for p in team1_pokemon]

team2_indices = list(set(indices) - set(team1_indices))
team2_pokemon = population[team2_indices]
team2_names = [p.formatted.split("|")[0] for p in team2_pokemon]

# Return teams
return list(team1_pokemon), list(team2_pokemon)
Expand All @@ -293,7 +291,7 @@ def sample_swap(
def mutate(
teams: list[Team],
num_pokemon: int,
mutate_prob: float,
mutate_prob: float | np.ndarray,
pokemon_population: list[str],
allow_all: bool,
k: int = None,
Expand All @@ -313,9 +311,14 @@ def mutate(
be random.
"""
new_teams = []
for team in teams:
if isinstance(mutate_prob, float):
mutate_prob_iter = [mutate_prob] * len(teams)
else:
mutate_prob_iter = mutate_prob

for team, prob in zip(teams, mutate_prob_iter):
# Each team faces a random chance of mutation
if np.random.choice([True, False], size=None, p=[mutate_prob, 1 - mutate_prob]):
if np.random.choice([True, False], size=None, p=[prob, 1 - prob]):
# If k has not been chosen, choose randomly how many team members to mutate
if k is None:
# If allow_all is true, the teams may just completely swap members
Expand Down Expand Up @@ -363,7 +366,8 @@ def fitness_mutate(
):
"""
A mutation operation. Does the same as regular mutation, except that
mutate probabilites are now inverse to fitness scores.
mutate probabilites are now one minus the fitness of the team. This means
that teams with a higher fitness are less likely to mutate.

Should either be used prior to crossover, or without using any kind of
crossover.
Expand All @@ -378,45 +382,11 @@ def fitness_mutate(
k: Number of team members to mutate. If set to None, this number will
be random.
"""
new_teams = []

for index, team in enumerate(teams):
# Each team faces a random chance of mutation
if np.random.choice(
[True, False], size=None, p=[1 - fitness[index], fitness[index]]
):
# If k has not been chosen, choose randomly how many team members to mutate
if k is None:
# If allow_all is true, the teams may just completely swap members
# or not swap at all. This changes the higher level crossover probs!
n = 0 if allow_all else 1
k = random.sample(range(n, num_pokemon - n), k=1)[0]

# Randomly swap k members of the team out with pokemon from the general pop
# IMPORTANT: ensure that no team has the same pokemon in it
mutate_indices = np.random.choice(range(num_pokemon), size=k, replace=False)
new_pokemon = np.random.choice(
pokemon_population,
size=k,
replace=False, # replace would create duplicates
) # open to parameterising the replace
# check that these new pokemon are not already in the team
names = [p.formatted.split("|")[0] for p in new_pokemon]
while any(name in team.names for name in names):
print("Found duplicate pokemon, resampling...")
new_pokemon = np.random.choice(
pokemon_population,
size=k,
replace=False, # replace would create duplicates
)
names = [p.formatted.split("|")[0] for p in new_pokemon]
# Create new team with the mutated pokemon and the rest of the team
old_pokemon = np.array(team.pokemon)[
[i for i in range(num_pokemon) if i not in mutate_indices]
]
new_team = [*new_pokemon, *old_pokemon]
new_teams.append(Team(new_team))
else:
new_teams.append(team)

return new_teams
return mutate(
teams,
num_pokemon,
mutate_prob=1 - fitness,
pokemon_population=pokemon_population,
allow_all=allow_all,
k=k,
)