Source code for smt_optim.benchmarks.misc.edge_cases
import numpy as np
from smt_optim.benchmarks.base import BenchmarkProblem
[docs]
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)
[docs]
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]
]
[docs]
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()
[docs]
def cstr2(self, x):
if x.ndim == 1:
x = x.reshape(1, -1)
return (x[:, 0] - 0.8 * x[:, 1]).ravel()
