def test_GN_quadratic(self): GN = Optimization.GaussNewton() xopt = GN.minimize(getQuadratic(self.A, self.b), np.array([0, 0])) x_true = np.array([5., 5.]) print('xopt: ', xopt) print('x_true: ', x_true) self.assertTrue(np.linalg.norm(xopt - x_true, 2) < TOL, True)
def test_GN_Rosenbrock(self): GN = Optimization.GaussNewton() xopt = GN.minimize(Rosenbrock, np.array([0, 0])) x_true = np.array([1., 1.]) print('xopt: ', xopt) print('x_true: ', x_true) self.assertTrue(np.linalg.norm(xopt - x_true, 2) < TOL, True)