Currently MIMO transfer num den data is kept in list of lists. This is good for quick access with different lengths of entries. For example, if some element has only 1 and the other element has s^3 + 5s^2 - 4s -7
and they can be kept as [[1], [1, 5, -4, -7]. But for some operations walking over list of lists is too slow and inconvenient. For example adding a 3D zero padded numpy array is much easier to multiply with a scalar etc.
A MIMO transfer object can hold both the list of lists and also the 3D array version. Hence add NumPy arrays.
Currently MIMO transfer num den data is kept in list of lists. This is good for quick access with different lengths of entries. For example, if some element has only
1and the other element hass^3 + 5s^2 - 4s -7and they can be kept as
[[1], [1, 5, -4, -7]. But for some operations walking over list of lists is too slow and inconvenient. For example adding a 3D zero padded numpy array is much easier to multiply with a scalar etc.A MIMO transfer object can hold both the list of lists and also the 3D array version. Hence add NumPy arrays.