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
|
from cPickle import load
from math import log, exp
#import numpy as np
#from scipy.optimize import basinhopping
from itertools import product
def iter_events(events):
for n, s in events.iteritems():
for t in s:
yield (n, t)
def ll(a):
lamb, alpha, mu = a
r1 = sum(log(lamb + sum(alpha * w * mu * exp(-mu * (t1 - t2))
for (n2, t2, w) in s))
for ((n1, t1), s) in event_edges.iteritems())
r2 = sum(sum(alpha * w * (1 - exp(-mu * (nodes[n2] - t1)))
for n2, w in edges[n1].iteritems() if nodes[n2] > t1)
for (n1, t1) in iter_events(events))
r3 = lamb * sum(nodes.itervalues())
return -(r1 - r2 - r3)
if __name__ == "__main__":
nodes, edges, events, event_edges = load(open("data.pickle", "rb"))
d = {}
for line in open("values.txt"):
v = map(float, line.strip().split())
d[tuple(v[:3])] = v[3]
# lamb = [20. ** i for i in range(-15, 15)]
# alpha = [20. ** i for i in range(-15, 15)]
# mu = [20. ** i for i in range(-15, 15)]
# for l, a, m in product(lamb, alpha, mu):
# if (l, a, m) in d:
# continue
# print l, a, m, ll((l, a, m))
print ll((2, 10000000000., 0.000000000000000000001))
#r = basinhopping(ll, init, disp=True, stepsize=0.1, T=10000., niter=500)
#print r.x
|
