MarkovProcess object in distribution.py, towards #639 #902
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See #639
This puts a tested MarkovProcess class into distribution for handling sampling from Markov arrays.
The code demonstrates how to turn a general Python function into a numpy function that can broadcast over an array.
It uses the numpy random number generator to sample based on an array of weights instead of coding that up manually with
cumsumandsearchsorted.https://numpy.org/doc/stable/reference/random/generated/numpy.random.RandomState.choice.html?highlight=choice#numpy.random.RandomState.choice
One this is merged in, the next step will be to refactor the Markov model code to use this on the draws.