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)
