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: