def test_copy_missing_diagonal_submatrix():
nobs = 5
k_endog = 3
missing = np.zeros((k_endog, nobs))
missing[0, 0] = 1
missing[:2, 1] = 1
missing[0, 2] = 1
missing[2, 2] = 1
missing[1, 3] = 1
missing[2, 4] = 1
A = np.zeros((k_endog, k_endog, nobs))
for t in range(nobs):
n = int(k_endog - np.sum(missing[:, t]))
A[:n, :n, t] = np.eye(n)
B = np.zeros((k_endog, k_endog, nobs), order='F')
missing = np.asfortranarray(missing.astype(np.int32))
tools.copy_missing_matrix(A, B, missing, True, True, False, inplace=True)
assert_equal(B, A)
B = np.zeros((k_endog, k_endog, nobs), order='F')
tools.copy_missing_matrix(A, B, missing, True, True, True, inplace=True)
assert_equal(B, A)
def test_copy_missing_diagonal_submatrix():
nobs = 5
k_endog = 3
missing = np.zeros((k_endog, nobs))
missing[0, 0] = 1
missing[:2, 1] = 1
missing[0, 2] = 1
missing[2, 2] = 1
missing[1, 3] = 1
missing[2, 4] = 1
A = np.zeros((k_endog, k_endog, nobs))
for t in range(nobs):
n = int(k_endog - np.sum(missing[:, t]))
A[:n, :n, t] = np.eye(n)
B = np.zeros((k_endog, k_endog, nobs), order='F')
missing = np.asfortranarray(missing.astype(np.int32))
tools.copy_missing_matrix(A, B, missing, True, True, False, inplace=True)
assert_equal(B, A)
B = np.zeros((k_endog, k_endog, nobs), order='F')
tools.copy_missing_matrix(A, B, missing, True, True, True, inplace=True)
assert_equal(B, A)
