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from csv import DictReader
import sys
from ml import ml
import numpy as np
from cPickle import dump, load
from itertools import product
def build_network(filename):
victims = {}
non_victims = {}
with open(filename) as fh:
reader = DictReader(fh)
for row in reader:
from_, to = int(float(row["from"])), int(float(row["to"]))
if row["t2"] != "NA":
dt = int(row["t2"]) - int(row["t1"])
parent = (int(row["dist"]), dt)
if to not in victims:
victims[to] = []
victims[to].append(parent)
if from_ not in victims:
victims[from_] = []
else:
from_, to = int(float(row["from"])), int(float(row["to"]))
parent = (int(row["dist"]), 3012 - int(row["t1"]))
if to not in victims:
non_victims[to] = []
non_victims[to].append(parent)
if from_ not in victims:
victims[from_] = []
root_victims = {}
for victim in victims.keys():
if not victims[victim]:
del victims[victim]
root_victims[victim] = []
return root_victims, victims, non_victims
if __name__ == "__main__":
#root_victims, victims, non_victims = build_network(sys.argv[1])
#dump((root_victims, victims, non_victims), open("network.pickle", "w"))
root_victims, victims, non_victims = load(open("network.pickle"))
alpha = np.arange(0.0000005, 0.00000051, 0.000001)
delta = np.arange(1., 1.000001, 0.001)
with open("out.log", "a") as fh:
for a, d in product(alpha, delta):
beta, roots, ll = ml(root_victims, victims, non_victims, a, d)
fh.write("\t".join(map(str, [a, d, beta, roots, ll])) + "\n")
fh.flush()
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