def allsp(start):
# initialize distances and predecessor edges
all_edges=gi.alive_edges() # gi.edges()# damaged= start ? end#if len(damaged) !=0:# all_edges.discard(damaged.pop())
dist, prev , distinv= {}, {}, {}
for v in gi.nodes():
dist[v], distinv[v], prev[v] = float('inf'), float('inf'), None
dist[start] , distinv[start]= 0, 0
for i in range(len(gi.nodes())): # Bellman-Ford algorithm, tweaked so that high weight = shorter distance
for e in all_edges:
if distinv[e.target] > distinv[e.source] + 1./ e.weight: #... + 1./ e.weight
distinv[e.target] = distinv[e.source] + 1./ e.weight #... + 1./ e.weight
dist[e.target] = dist[e.source] + e.weight
prev[e.target] = e
if e.source==start or e.target ==start:
prev[start]=e
if distinv[e.source] > distinv[e.target] + 1./ e.weight: #... + 1./ e.weight
distinv[e.source] = distinv[e.target] + 1./ e.weight #... + 1./ e.weight
dist[e.source] = dist[e.target] + e.weight
prev[e.source] = e
if e.target==start or e.source ==start:
pass
d,dinv=[],[]
for v in gi.nodes():
if v!=start:
d.append((dist[v])) #int
dinv.append(distinv[v])
return d,dinv,dist,distinv # return the total weight of the path (distance)
def path_length():
"""
average path length
"""
dist = floyd_warshall.run(gi.nodes(),gi.edges())
ret = floyd_warshall.avg(dist)
return ret
def getpl():
allhm,allhminv,hm,hminv=[],[],[],[]
for s in gi.nodes():
[d,dinv,dist,distinv]=allsp(s)
allhm.append(utils.harmean(d))
allhminv.append(utils.harmean(dinv))
hm=float(utils.harmean(allhm)) # distance with the real weights (high means good)
hminv=utils.harmean(allhminv)
return hminv
def initialize():
"""
initialization procedures. For example: attaching methods to nodes.
"""
global count_steps
count_steps = 0
stats.new_collector()
for node in gi.nodes():
if node is not None:
setattr(node, "weight", 1.0)