def hapinitial(allele):
#Edge counts are used. Count of edge/Total count for all edges.
for i in G.out_edges(1, data=True):
if i[2]['allele'] == allele:
return sum(G.node[i[1]]['frequency'])/sum(G.node[1]['frequency'])
import math
import numpy as np
import itertools
from v3 import G, glevel
#ll is number of levels in the graph
ll = len(glevel) -1
print "ll"
print ll
#Set the genotype
GT = [('?','?'),(1,1),(1,2),(1,2)]
#Create n the list of the number of edges in each level
n = [G.out_degree(1)]
#m is the list of matrices of forward probabilities at each level
m = [np.zeros(shape=(n[0],n[0]))]
#Append matrices to list m
for i in range(ll-1):
#Sum n for each level
n.append(G.out_degree(glevel[i]+1))
for j in range(glevel[i]+2, glevel[i+1]+1):
n[i+1] += G.out_degree(j)
#Append zero-filled matrix to list m
m.append(np.zeros(shape=(n[i+1],n[i+1])))
#Haploid initial state probabilities. allele: allele number.
