Bug in calculating local transfer entropy

[wirkuttis]

Hi there,

Thanks for the great library!
I discovered the following bug.

In the documentation Transfer Entropy considers X as Source input and Y as Target input. https://elife-asu.github.io/PyInform/timeseries.html#notation

In the source code, transfer entropy is calculated as transfer_entropy(source, target, k, condition=None, local=False) but in the preprocessing the source is assigned to ys = np.ascontiguousarray(source, np.int32) (which should be assigned to xs) and the target to xs = np.ascontiguousarray(target, np.int32) (which should be ys).

As a result _local_transfer_entropy(ys, xs) seems to provide the reversed result of information flow from source to target distribution rather than a target to the source distribution.

[RamiATASSI]

Hi,

I was suspicious about my results and got to the same conclusion after investigating.

Good to see that I am not alone. Still, I am very surprised about this "bug" and wonder if there is a logic behind it ?