def test_lagrangian_size(self): self.assertEqual( al.AugmentedLagrangianNonsmooth( prog=self.prog, include_x_bounds=True).lagrangian_size(), 1) self.assertEqual( al.AugmentedLagrangianNonsmooth( prog=self.prog, include_x_bounds=False).lagrangian_size(), 1)
def test_is_equality(self): self.assertEqual( al.AugmentedLagrangianNonsmooth( prog=self.prog, include_x_bounds=True).is_equality(), [False]) self.assertEqual( al.AugmentedLagrangianSmooth(prog=self.prog, include_x_bounds=True).is_equality(), [False])
def test_eval_ad_nonsmooth(self): dut = al.AugmentedLagrangianNonsmooth(prog=self.prog, include_x_bounds=True) x_val = InitializeAutoDiff(np.array([1., 3])) al_val, constraint_residue, cost = dut.Eval(x=x_val, lambda_val=np.array([0.5]), mu=0.1) self.assertIsInstance(al_val, AutoDiffXd) self.assertIsInstance(constraint_residue, np.ndarray) self.assertIsInstance(cost, AutoDiffXd)
def test_eval_double_nonsmooth(self): dut = al.AugmentedLagrangianNonsmooth(prog=self.prog, include_x_bounds=True) x_val = np.array([1., 3]) lambda_val = np.array([0.5]) al_val, constraint_residue, cost = dut.Eval(x=x_val, lambda_val=lambda_val, mu=0.1) self.assertIsInstance(al_val, float) self.assertIsInstance(constraint_residue, np.ndarray) self.assertIsInstance(cost, float)