def test_unvec_symm(self):
np.random.seed(0)
n = 5
x = np.random.randn(n, n)
x = x + x.T
np.testing.assert_allclose(
cone_lib.unvec_symm(cone_lib.vec_symm(x), n), x)
def test_proj_psd(self):
import cvxpy as cp
np.random.seed(0)
n = 10
for _ in range(15):
x = np.random.randn(n, n)
x = x + x.T
x_vec = cone_lib.vec_symm(x)
z = cp.Variable((n, n), PSD=True)
objective = cp.Minimize(cp.sum_squares(z - x))
prob = cp.Problem(objective)
prob.solve(solver="SCS", eps=1e-10)
p = cone_lib.unvec_symm(
cone_lib._proj(x_vec, cone_lib.PSD, dual=False), n)
np.testing.assert_allclose(p, z.value, atol=1e-5, rtol=1e-5)
np.testing.assert_allclose(p, cone_lib.unvec_symm(
cone_lib._proj(x_vec, cone_lib.PSD, dual=True), n))
def test_vec_symm(self):
np.random.seed(0)
n = 5
x = np.random.randn(cone_lib.vec_psd_dim(n))
np.testing.assert_allclose(
cone_lib.vec_symm(cone_lib.unvec_symm(x, n)), x)