46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
|
from __future__ import division, print_function, absolute_import
|
||
|
|
||
|
import numpy as np
|
||
|
from numpy.testing import assert_, assert_allclose
|
||
|
import scipy.linalg
|
||
|
from scipy.optimize import minimize
|
||
|
|
||
|
|
||
|
def test_1():
|
||
|
def f(x):
|
||
|
return x**4, 4*x**3
|
||
|
|
||
|
for gtol in [1e-8, 1e-12, 1e-20]:
|
||
|
for maxcor in range(20, 35):
|
||
|
result = minimize(fun=f, jac=True, method='L-BFGS-B', x0=20,
|
||
|
options={'gtol': gtol, 'maxcor': maxcor})
|
||
|
|
||
|
H1 = result.hess_inv(np.array([1])).reshape(1,1)
|
||
|
H2 = result.hess_inv.todense()
|
||
|
|
||
|
assert_allclose(H1, H2)
|
||
|
|
||
|
|
||
|
def test_2():
|
||
|
H0 = [[3, 0], [1, 2]]
|
||
|
|
||
|
def f(x):
|
||
|
return np.dot(x, np.dot(scipy.linalg.inv(H0), x))
|
||
|
|
||
|
result1 = minimize(fun=f, method='L-BFGS-B', x0=[10, 20])
|
||
|
result2 = minimize(fun=f, method='BFGS', x0=[10, 20])
|
||
|
|
||
|
H1 = result1.hess_inv.todense()
|
||
|
|
||
|
H2 = np.vstack((
|
||
|
result1.hess_inv(np.array([1, 0])),
|
||
|
result1.hess_inv(np.array([0, 1]))))
|
||
|
|
||
|
assert_allclose(
|
||
|
result1.hess_inv(np.array([1, 0]).reshape(2,1)).reshape(-1),
|
||
|
result1.hess_inv(np.array([1, 0])))
|
||
|
assert_allclose(H1, H2)
|
||
|
assert_allclose(H1, result2.hess_inv, rtol=1e-2, atol=0.03)
|
||
|
|
||
|
|