def test001(self):
p = 1
R, X = self._create_case(p, T=1000)
B_hat, eps = solve_lasso(X, p=p, lmbda=0.0, eps=-np.inf,
maxiter=1000)
A_hat = B_to_A(B_hat)
YW = yule_walker(A_hat, R)
np.testing.assert_almost_equal(YW[1], np.zeros_like(YW[1]))
self.assertAlmostEqual(eps, 0.0)
return
def test002(self):
p = 5
R, X = self._create_case(p)
B_hat, eps = solve_lasso(X, p=p, lmbda=0.0,
eps=-np.inf, maxiter=1000)
A_hat = B_to_A(B_hat)
YW = yule_walker(A_hat, R)
for tau in range(1, p + 1):
np.testing.assert_almost_equal(YW[tau],
np.zeros_like(YW[tau]))
self.assertAlmostEqual(eps, 0.0)
return
def test003(self):
p = 5
lmbda = 0.05
for _ in range(10):
R, X = self._create_case(p, T=1000)
B_hat, eps = solve_lasso(X, p=p, lmbda=lmbda,
maxiter=250, eps=-np.inf)
self.assertTrue(eps > 0)
J_star = exact_cost_function(B_hat, X, lmbda=lmbda)
for _ in range(10):
J = exact_cost_function(
B_hat + 0.025 * np.random.normal(size=B_hat.shape),
X, lmbda=lmbda)
self.assertTrue(J_star < J)
return
def test004(self):
p = 5
n = 2
lmbda = 0.01
for _ in range(10):
R, X = self._create_case(p, T=1000)
W = np.abs(np.random.normal(size=(p, n, n)))
B_hat, eps = solve_lasso(X, p=p, lmbda=lmbda, W=W,
maxiter=250, eps=-np.inf,
line_srch=1.1, method="fista")
self.assertTrue(eps > 0)
J_star = cost_function(B_hat, R, lmbda=lmbda, W=W)
for _ in range(10):
J = cost_function(
B_hat + 0.025 * np.random.normal(size=B_hat.shape),
R, lmbda=lmbda, W=W)
self.assertTrue(J_star < J)
return