65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import numpy as np
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from numpy.testing import assert_allclose
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import scipy.linalg
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from scipy.optimize import minimize
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def test_1():
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def f(x):
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return x**4, 4*x**3
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for gtol in [1e-8, 1e-12, 1e-20]:
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for maxcor in range(20, 35):
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result = minimize(fun=f, jac=True, method='L-BFGS-B', x0=20,
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options={'gtol': gtol, 'maxcor': maxcor})
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H1 = result.hess_inv(np.array([1])).reshape(1,1)
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H2 = result.hess_inv.todense()
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assert_allclose(H1, H2)
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def test_2():
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H0 = [[3, 0], [1, 2]]
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def f(x):
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return np.dot(x, np.dot(scipy.linalg.inv(H0), x))
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result1 = minimize(fun=f, method='L-BFGS-B', x0=[10, 20])
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result2 = minimize(fun=f, method='BFGS', x0=[10, 20])
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H1 = result1.hess_inv.todense()
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H2 = np.vstack((
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result1.hess_inv(np.array([1, 0])),
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result1.hess_inv(np.array([0, 1]))))
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assert_allclose(
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result1.hess_inv(np.array([1, 0]).reshape(2,1)).reshape(-1),
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result1.hess_inv(np.array([1, 0])))
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assert_allclose(H1, H2)
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assert_allclose(H1, result2.hess_inv, rtol=1e-2, atol=0.03)
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def test_3():
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def todense_old_impl(self):
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s, y, n_corrs, rho = self.sk, self.yk, self.n_corrs, self.rho
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I_arr = np.eye(*self.shape, dtype=self.dtype)
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Hk = I_arr
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for i in range(n_corrs):
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A1 = I_arr - s[i][:, np.newaxis] * y[i][np.newaxis, :] * rho[i]
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A2 = I_arr - y[i][:, np.newaxis] * s[i][np.newaxis, :] * rho[i]
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Hk = np.dot(A1, np.dot(Hk, A2)) + (rho[i] * s[i][:, np.newaxis] *
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s[i][np.newaxis, :])
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return Hk
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H0 = [[3, 0], [1, 2]]
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def f(x):
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return np.dot(x, np.dot(scipy.linalg.inv(H0), x))
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result1 = minimize(fun=f, method='L-BFGS-B', x0=[10, 20])
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assert_allclose(result1.hess_inv.todense(), todense_old_impl(result1.hess_inv))
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