Source code for smt_optim.benchmarks.misc.edge_cases
import numpy as np
from smt_optim.benchmarks.base import BenchmarkProblem
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class Rosenbrock2(BenchmarkProblem):
def __init__(self):
super().__init__()
self.num_dim = 2
self.num_cstr = 2
self.num_fidelity = 1
self.bounds = np.array([[-2, 2], [-2, 2]])
self.costs = [1]
self.objective = [self.hf_objective]
self.constraints = [[self.hf_constraint], [self.hf_constraint2]]
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def hf_objective(self, x):
res = (1 - x[0]) ** 2 + 100 * (x[1] - x[0] ** 2) ** 2
return res
# def lf_objective(self, x):
# res = self.hf_objective(x) + 0.1*np.sin(10*x[0] + 5*x[1])
# return res
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def hf_constraint(self, x):
res = -(x[0] ** 2) - (x[1] - 1) ** 1 / 2
return -res
# def lf_constraint(self, x):
# res = self.hf_constraint(x) - 0.1*np.sin(10*x[0] + 5*x[1])
# return res
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def hf_constraint2(self, x):
# return -1 - 2*x[0] + (x[1]+15/9)**2
# return -x[1] + 0.2 + x[0]
return -0.5 * np.sin(5 * (x[0] - 0.5) ** 2 - x[1] - np.pi / 8)
# def lf_constraint2(self, x):
# x[0] = x[0] + 0.1
# x[1] = x[1] - 1
# return 0.9 * self.hf_constraint2(x)
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class TwoConstraints(BenchmarkProblem):
def __init__(self):
super().__init__()
self.num_dim = 2
self.num_cstr = 2
self.num_fidelity = 1
self.bounds = np.array([[1, 4], [1, 4]])
self.costs = [1]
self.objective = [self.func]
self.constraints = [[self.cstr1], [self.cstr2]]
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def func(self, x):
if x.ndim == 1:
x = x.reshape(1, -1)
return (x[:, 0] ** 2 + x[:, 1] ** 2).ravel()
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def cstr1(self, x):
if x.ndim == 1:
x = x.reshape(1, -1)
return (0.15 * (x[:, 0] - 4) ** 2 + 0.1 * (x[:, 1] - 4) ** 2 - 1).ravel()
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def cstr2(self, x):
if x.ndim == 1:
x = x.reshape(1, -1)
return (x[:, 0] - 0.8 * x[:, 1]).ravel()
