def trust_region_constr_nonlinear_constraint():
constraint_function = lambda x: (x[0] + x[1])**2
constraints = [
NonlinearInequalityConstraint(constraint_function, np.array([2.]),
np.array([np.inf]))
]
return OptTrustRegionConstrained([(-1, 1), (-1, 1)], constraints, 1000)
def test_invalid_constraint_object():
constraint_function = lambda x: (x[0] + x[1])**2
with pytest.raises(ValueError):
return OptTrustRegionConstrained([(-1, 1), (-1, 1)],
[constraint_function], 1000)
def trust_region_constr_linear_constraint():
constraints = [
LinearInequalityConstraint(np.array([[0, 1]]), np.array([0.5]),
np.array([np.inf]))
]
return OptTrustRegionConstrained([(-1, 1), (-1, 1)], constraints, 1000)
def _get_optimizer(self, context_manager):
if len(self.space.constraints) == 0:
return OptLbfgs(context_manager.contextfree_space.get_bounds())
else:
return OptTrustRegionConstrained(context_manager.contextfree_space.get_bounds(), self.space.constraints)