Use Moran processes on interaction graph

The Moran process method on the Game class can take an interaction_graph_adjacency_matrix which defines the interaction graph as described in [Ohtsuki2007]:

>>> import nashpy as nash
>>> import numpy as np
>>> A = np.array([[3, 1], [1, 2]])
>>> game = nash.Game(A)

In this case, the moran_process method returns a generator of a given collection of generations where individuals interact if and only if they are adjacent on the interaction graph (in the example below, the individuals are placed on a cycle and only interact with the successive individuals except for the last individual who interacts with everyone including themself):

>>> np.random.seed(0)
>>> interaction_graph_adjacency_matrix = np.array(((0, 1, 0), (0, 0, 1), (1, 1, 1)))
>>> generations = game.moran_process(initial_population=(0, 0, 1), interaction_graph_adjacency_matrix=interaction_graph_adjacency_matrix)
>>> for population in generations:
...     print(population)
[0 1 1]
[0 1 1]
[0 1 1]
...
[0 1 1]
[1 1 1]