def main(args):
## to obtain biological sequence for the Fission Yeast Cell-Cycle Net starting from biological inital state
EDGE_FILE = '../data/fission-net/fission-net-edges.txt'
NODE_FILE = '../data/fission-net/fission-net-nodes.txt'
BIO_INIT_FILE = '../data/fission-net/fission-net-bioSeq-initial.txt'
net = inet.read_network_from_file(EDGE_FILE, NODE_FILE)
nodes_list = inet.build_nodes_list(NODE_FILE)
#input_file_name1 = 'time-series/%s-step%d-trans0.dat'%(network_index, maxStep)
#input_file1 = open( input_file_name1, 'r')
Nbr_Initial_States = np.power(2,len(nodes_list))
maxStep = 20
Nbr_States = 2
historyLength = 5
result_ai = open('../results/fission-net/ai-step%d-trans0-h%d.dat'%(maxStep, historyLength),'w')
result_te = open('../results/fission-net/te-step%d-trans0-h%d.dat'%(maxStep, historyLength),'w')
timeSeries = tev.time_series(net, nodes_list, Nbr_Initial_States, Nbr_States, MAX_TimeStep=20)
print 'AI'
AI = {}
for n in nodes_list:
AI[n] = info.compute_AI(timeSeries[n], historyLength, Nbr_Initial_States, Nbr_States)
result_ai.write('%s\t%f\n'%(n, AI[n]))
print n, AI[n]
print 'done AI'
print 'TE'
TE = defaultdict(float)
for v in nodes_list:
for n in nodes_list:
TE[(v, n)] = info.compute_TE(timeSeries[v], timeSeries[n], historyLength, Nbr_Initial_States, Nbr_States)
result_te.write('%s\t%s\t%f\n'%(v, n,TE[(v, n)] ))
print v, n, TE[(v, n)]
print 'done TE'
net = inet.read_network_from_file(EDGE_FILE, NODE_FILE)
nodes_list = inet.build_nodes_list(NODE_FILE)
#input_file_name1 = 'time-series/%s-step%d-trans0.dat'%(network_index, maxStep)
#input_file1 = open( input_file_name1, 'r')
Nbr_Initial_States = np.power(2,len(nodes_list))
maxStep = 20
Nbr_States = 2
historyLength = 5
result_ai = open('../results/fission-net/ai-step%d-trans0-h%d.dat'%(maxStep, historyLength),'w')
result_te = open('../results/fission-net/te-step%d-trans0-h%d.dat'%(maxStep, historyLength),'w')
timeSeries = tev.time_series(net, nodes_list, Nbr_Initial_States, Nbr_States, MAX_TimeStep=20)
print 'AI'
AI = {}
for n in nodes_list:
AI[n] = info.compute_AI(timeSeries[n], historyLength, Nbr_Initial_States, Nbr_States)
result_ai.write('%s\t%f\n'%(n, AI[n]))
print n, AI[n]
print 'done AI'
print 'TE'
TE = defaultdict(float)
for v in nodes_list:
for n in nodes_list:
