def test_update_P_allind(self):
import mat_emosqp
# Update matrix P
Px = self.P_new.data
mat_emosqp.update_P(Px, None, 0)
x, y, _, _, _ = mat_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(x, np.array([0., 5.]), decimal=5)
nptest.assert_array_almost_equal(
y, np.array([0., 0., 3., 0., 0.]), decimal=5)
# Update matrix P to the original value
Px_idx = np.arange(self.P.nnz)
mat_emosqp.update_P(Px, Px_idx, len(Px))
def test_update_P(self):
import mat_emosqp
# Update matrix P
Pnew_triu = sparse.triu(self.P_new).tocsc()
Px = Pnew_triu.data
Px_idx = np.arange(Pnew_triu.nnz)
mat_emosqp.update_P(Px, Px_idx, len(Px))
# Solve problem
x, y, _, _, _ = mat_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(x, np.array([0., 5.]), decimal=5)
nptest.assert_array_almost_equal(y,
np.array([0., 0., 3., 0., 0.]),
decimal=5)
# Update matrix P to the original value
P_triu = sparse.triu(self.P).tocsc()
Px = P_triu.data
Px_idx = np.arange(P_triu.nnz)
mat_emosqp.update_P(Px, Px_idx, len(Px))