def test_dendritic_input():
torch.manual_seed(SEED)
r_in = torch.Tensor(1, 5).normal_(std=0.1) + 5.0
model = AbstractConvexCell([3, 2], 1)
u_in = model.f_inv(r_in)
assert model.dendritic_input(u_in, 0)[0].tolist() == pytest.approx(
r_in[0, :3].tolist())
assert model.dendritic_input(u_in, 1)[0].tolist() == pytest.approx(
r_in[0, 3:3 + 2].tolist())
def test_input_scale():
torch.manual_seed(SEED)
scale_0 = 0.15
scale_1 = 1.05
r_in = torch.Tensor(1, 5).normal_(std=0.1) + 5.0
model = AbstractConvexCell([3, 2], 1)
model.set_input_scale(0, scale_0)
model.set_input_scale(1, scale_1)
u_in = model.f_inv(r_in)
assert model.dendritic_input(u_in, 0)[0].tolist() == pytest.approx(
(scale_0 * r_in[0, :3]).tolist())
assert model.dendritic_input(u_in, 1)[0].tolist() == pytest.approx(
(scale_1 * r_in[0, 3:3 + 2]).tolist())