1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
|
from cPickle import load
from math import exp, sin
from csv import reader
from data2 import parse
import sys
import networkx as nx
import matplotlib.pyplot as plt
def fatal():
with open(sys.argv[1]) as fh:
fh.readline()
r = reader(fh)
d = {i + 1: parse(row[7]) for (i, row) in enumerate(r)}
d = {k: v for k, v in d.iteritems() if v}
return d
def main(lamb, alpha, mu):
G = nx.DiGraph()
r, dr, i = 0, 0, 0
drf, iff, rf = 0, 0, 0
dnf, rnf, inf = 0, 0, 0
si = 0
f = fatal().items()
l = []
for ((n1, t1), s) in event_edges.iteritems():
G.add_node((n1, t1))
if not s:
dr += 1
if (n1, t1) in f:
drf += 1
else:
dnf += 1
continue
br = lamb * (1 + 0.43 * sin(0.0172 * t1 + 4.36))
prl = sorted([(n2, t2, alpha / d * mu * exp(-mu * (t1 - t2)))
for (n2, t2, d) in s], reverse=True)
pr = sum(e[2] for e in prl)
#if sum(e[2] for e in prl[:1]) > br:
# G.add_edge((n1, t1), tuple(prl[0][:2]))
if br > pr:
r += 1
if (n1, t1) in f:
rf += 1
else:
rnf += 1
else:
G.add_edge((n1, t1), tuple(prl[0][:2]))
l.append(prl[0][2] / br)
i += 1
if (n1, t1) in f:
iff += 1
else:
inf += 1
print "nedges:", G.number_of_edges()
cs = {}
for c in nx.weakly_connected_components(G):
cs[len(c)] = cs.get(len(c), 0) + 1
cs = sorted(cs.iteritems(), key=lambda x: x[0])
x, y = zip(*cs)
print cs
plt.loglog(x, y, "-")
plt.xlabel("Cascade size")
plt.ylabel("Number of cascades")
plt.savefig("dist.pdf")
l.sort(reverse=True)
plt.plot(l)
plt.show()
return (lamb, alpha, mu, dr, r, i, drf, rf, iff,
dnf, rnf, inf, si, len(event_edges))
if __name__ == "__main__":
nodes, edges, events, event_edges = load(open("data2.pickle", "rb"))
lamb, alpha, mu = 1.1847510744e-05, 0.00316718040144, 0.00393069204339
# print len(event_edges), sum(len(e) for e in events.itervalues())
# print len(fatal())
print main(lamb, alpha, mu)
|
