TEnt of discrete variable timeseries. Added example.

[evanfeinberg]

In this PR, we add the ability to directly compute transfer entropy with timeseries containing discrete random variables or, equivalently, continuous data that has been pre-binned. This has been accomplished by adding a n_bins=None to entropy(). If n_bins=None, entropy() will compute counts with numpy.bincount(), which will directly count the frequency of each discrete label for each variable. This functionality is added at a higher level to ncmutinf(), which gives the option of passing int timeseries and n_bins=None, which will then compute Transfer Entropy in the way described above.

In addition, an example has been added in an examples folder demonstrating a usage of the above and generally how to flexibly use the MDEntropy API.