def test_lincomb_op_with_zero_coefficients():
p1 = MonomOperator(1)
p2 = MonomOperator(2)
p10 = p1 + 0 * p2
p0 = 0 * p1 + 0 * p1
x = np.linspace(-1., 1., num=3)
vx = p1.source.make_array((x[:, np.newaxis]))
pc1 = NumpyMatrixOperator(np.eye(p1.source.dim))
pc2 = NumpyMatrixOperator(2 * np.eye(p1.source.dim))
pc10 = pc1 + 0 * pc2
pc0 = 0 * pc1 + 0 * pc2
assert np.allclose(p0.apply(vx).to_numpy(), [0.])
assert len(p0.apply(vx)) == len(vx)
assert almost_equal(p10.apply(vx), p1.apply(vx)).all()
assert np.allclose(p0.apply2(vx, vx), [0.])
assert len(p0.apply2(vx, vx)) == len(vx)
assert np.allclose(p10.apply2(vx, vx), p1.apply2(vx, vx))
assert np.allclose(p0.pairwise_apply2(vx, vx), [0.])
assert len(p0.pairwise_apply2(vx, vx)) == len(vx)
assert np.allclose(p10.pairwise_apply2(vx, vx), p1.pairwise_apply2(vx, vx))
assert np.allclose(pc0.apply_adjoint(vx).to_numpy(), [0.])
assert len(pc0.apply_adjoint(vx)) == len(vx)
assert almost_equal(pc10.apply_adjoint(vx), pc1.apply_adjoint(vx)).all()
def apply_adjoint(self, V, mu=None):
return NumpyMatrixOperator.apply_adjoint(self, V, mu=mu)