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import numpy as np
from cmaes import CatCMAwM
def SphereIntCOM(x, z, c):
return sum(x * x) + sum(z * z) + len(c) - sum(c[:, 0])
def SphereInt(x, z):
return sum(x * x) + sum(z * z)
def SphereCOM(x, c):
return sum(x * x) + len(c) - sum(c[:, 0])
def f_cont_int_cat():
# [lower_bound, upper_bound] for each continuous variable
X = [[-5, 5], [-5, 5]]
# possible values for each integer variable
Z = [[-1, 0, 1], [-2, -1, 0, 1, 2]]
# number of categories for each categorical variable
C = [3, 3]
optimizer = CatCMAwM(x_space=X, z_space=Z, c_space=C)
for generation in range(50):
solutions = []
for _ in range(optimizer.population_size):
sol = optimizer.ask()
value = SphereIntCOM(sol.x, sol.z, sol.c)
solutions.append((sol, value))
print(f"#{generation} {sol} evaluation: {value}")
optimizer.tell(solutions)
def f_cont_int():
# [lower_bound, upper_bound] for each continuous variable
X = [[-np.inf, np.inf], [-np.inf, np.inf]]
# possible values for each integer variable
Z = [[-2, -1, 0, 1, 2], [-2, -1, 0, 1, 2]]
# initial distribution parameters (Optional)
# If you know a promising solution for X and Z, set init_mean to that value.
init_mean = np.ones(len(X) + len(Z))
init_cov = np.diag(np.ones(len(X) + len(Z)))
init_sigma = 1.0
optimizer = CatCMAwM(
x_space=X, z_space=Z, mean=init_mean, cov=init_cov, sigma=init_sigma
)
for generation in range(50):
solutions = []
for _ in range(optimizer.population_size):
sol = optimizer.ask()
value = SphereInt(sol.x, sol.z)
solutions.append((sol, value))
print(f"#{generation} {sol} evaluation: {value}")
optimizer.tell(solutions)
def f_cont_cat():
# [lower_bound, upper_bound] for each continuous variable
X = [[-5, 5], [-5, 5]]
# number of categories for each categorical variable
C = [3, 5]
# initial distribution parameters (Optional)
init_cat_param = np.array(
[
[0.5, 0.3, 0.2, 0.0, 0.0], # zero-padded at the end
[0.2, 0.2, 0.2, 0.2, 0.2], # each row must sum to 1
]
)
optimizer = CatCMAwM(x_space=X, c_space=C, cat_param=init_cat_param)
for generation in range(50):
solutions = []
for _ in range(optimizer.population_size):
sol = optimizer.ask()
value = SphereCOM(sol.x, sol.c)
solutions.append((sol, value))
print(f"#{generation} {sol} evaluation: {value}")
optimizer.tell(solutions)
if __name__ == "__main__":
f_cont_int_cat()
# f_cont_int()
# f_cont_cat()
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