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import sys
from ml import ml
import numpy as np
from cPickle import load
from itertools import product
from math import exp
if __name__ == "__main__":
if len(sys.argv) < 2:
sys.exit("usage: {0} <file>".format(sys.argv[0]))
root_victims, victims, non_victims, age = load(open(sys.argv[1]))
alphas = 1. / np.arange(1., 1000., 50.) # parameter of the time component
deltas = np.arange(0.01, 0.5, 0.1) # parameter of the structural component
with open("out.log", "w") as fh:
for alpha, delta in product(alphas, deltas):
beta, roots, ll = ml(root_victims, victims, non_victims, age, alpha, delta)
print "\t".join(map(str, [1/alpha, delta, beta, roots, ll, exp(ll)]))
fh.write("\t".join(map(str, [alpha, delta, beta, roots, ll])) + "\n")
fh.flush()
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