def orig_test():
from pprint import pprint
# large test of max flow.
#
# notes.
#
# this test is to double-check that if you have a large
# group of nodes that are interlinked to each other, and
# another group that is interlinked to itself and the first
# group, that none of the second group gets any flow.
#
# it's also quite a good test of the amount of
# time / memory this takes up (about 1k per node).
# try 100,000: it's fun!
from random import randint
f = NetFlow()
f.netflow_add_edge("-", 0)
len = 10000
for i in range(len):
f.netflow_add_edge(randint(0, len/4), randint(0, len/4))
f.netflow_add_edge(randint(len/4+1, len/2), randint(0, len/2))
e = f.netflow_max_flow_extract("-", [800, 200, 50, 12, 4, 2, 1])
for x in e.keys():
if type(x) == type(0) and x > (len/4) and e[x] != 0:
raise ("untrusted group (%d->%d) linked to trusted (0->%d)\n" % \
(len/4+1, len/2, len/4))
print "random test passed ok"
print
# pretty test of max flow.
#
# notes.
#
# mary and bob like each other, but the seeds aren't
# interested in mary and bob, so they don't show up
# in the max flow diagram.
#
# fleas ad infinitum is so far down from the seeds that
# despite being linked, no flow reaches it: the
# available capacity, which is limited in this test to
# 7 degrees away from the supersink ("-") _anyway_,
# is all used up.
#
# 1: -, 2: seed, 3: heather, 4: rob,
# 5: fleas, 6: lit-f, 7: less-f - whoops! 8: fad.
# yeah, that's right. the capacity chain is only 7-long
# so anything beyond 7 degrees from the supersink isn't
# included. cool.
# the second test is what heather likes, and heather's likes'
# likes, and heather's likes' likes' likes... etc., up to
# 7 degrees. which is why fleas ad infinitum _is_ shown
# in the flow, this time. cool.
f = NetFlow()
f.set_debuglevel(1)
f.netflow_add_edge("-", "seed")
f.netflow_add_edge("-", "seed2")
f.netflow_add_edge("seed", "heather")
f.netflow_add_edge("seed2", "heather")
f.netflow_add_edge("seed", 55)
f.netflow_add_edge("seed", u"luke")
f.netflow_add_edge(55, 10)
f.netflow_add_edge(10, u"luke")
f.netflow_add_edge(u"luke", "heather")
f.netflow_add_edge("heather", u"luke")
f.netflow_add_edge("heather", "flat-faced cat")
f.netflow_add_edge("flat-faced cat", "heather")
f.netflow_add_edge("luke", "flat-faced cat")
f.netflow_add_edge("heather", "mo the mad orange pony")
f.netflow_add_edge("heather", "robbie the old crock pony")
f.netflow_add_edge("robbie the old crock pony", "fleas")
f.netflow_add_edge("fleas", "little fleas")
f.netflow_add_edge("little fleas", "lesser fleas")
f.netflow_add_edge("lesser fleas", "fleas ad infinitum")
f.netflow_add_edge("bob", "heather")
f.netflow_add_edge("bob", "mary")
f.netflow_add_edge("mary", "bob")
print "pretty node graph (yes, the numbers 55 and 10 are nodes):"
pprint(f.succs)
print
e = f.netflow_max_flow_extract("-", [800, 200, 50, 12, 4, 2, 1])
print "supersink as seed - avg_capacity:", f.get_avg_capacity()
pprint(e)
print
e = f.netflow_max_flow_extract("heather", [800, 200, 50, 12, 4, 2, 1])
print "heather as seed - avg_capacity:", f.get_avg_capacity()
pprint(e)
print
if __name__ == '__main__':
if True:
orig_test()
else:
a = Advogato()
print "Loading Advogato dataset"
G = networkx.read_dot(a.numbersfilepath)
# use G.edges(node)
f = NetFlow(G)
print "netflow"
# f.netflow_add_edge("-", "raph")
# FIX: multiple edges from source
# f.netflow_add_edge("-", "miguel")
f.netflow_add_edge("-", "alan")
f.netflow_add_edge("-", "federico")
# Do this 3 times
e = f.netflow_max_flow_extract("-")
# masters = ..
# journeyors =
# apprentices =
trusted = filter(lambda x: e[x], e)
trusted.sort()
print len(trusted), "trusted nodes"