A Markov Random Walk takes an inital distribution p0
and calculates the stationary distribution of that.
The diffusion process is regulated by a restart probability r
which controls how often the MRW jumps back to the initial values.
1  random.walk(p0, graph, r = 0.5, ...)

p0 
an 
graph 
an ( 
r 
a scalar between (0, 1). restart probability if a Markov random walk with restart is desired 
... 
additional parameters 
returns the stationary distribution as numeric vector
Simon Dirmeier, simon.dirmeier@gmx.de
Tong, H., Faloutsos, C., & Pan, J. Y. (2006),
Fast random walk with restart and its applications.
Koehler, S., Bauer, S., Horn, D., & Robinson, P. N. (2008),
Walking the interactome for prioritization of candidate disease genes.
The American Journal of Human Genetics
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