A Python memory and computational optimized version of Harmonic Centrality

harmonicCentrality.py

#This function compute the harminic distance of graph's nodes
#graph is a dictionary implementation of adjacency list  { 1 : [1,2,3], ...}
#return a dictionary where keys are nodes name and values are node harmonic distances
def harmonic2(graph):
	#for dynamic programming
	harmRes = dict()
	for i in graph.keys():
		harmRes[i] = 0.0

	#for each node compute the distance from reachable nodes
	for s in graph.keys():
		queue = [s] #visited node
       
		###BFS###
		distance = dict()
		for i in graph.keys():
			distance[i] = -1 #not visited
		distance[s] = 0
			 
		#BFS
		while queue != []:
			c = queue.pop(0)
			#for each neighbour 'i' 
			for i in graph[c]:
				if i in distance and distance[i] == -1: #not visited
					queue.append(i)
					dist = distance[c] + 1
					distance[i] = dist
					# dist is d(s,i)
					harmRes[i] += 1.0 / dist #h(i) = sum 1/d(s,i)
		
	return harmRes