text: #!/usr/bin/python
  import os, sys, json
  from DNN import Connection, Neuron, Net
  if not os.path.exists(sys.argv[4]):
  	eta = float(sys.argv[5])
  	alpha = float(sys.argv[6])
  	topology = [int(number) for number in sys.argv[7:]]
  	myNet = Net(topology = topology, eta = eta, alpha = alpha)
  	with open(sys.argv[4], mode = 'w') as f:
  		json.dump(myNet.toJSON(), f, indent = 4)
  lines = open(sys.argv[1], 'r').readlines()
  divider = int(sys.argv[3])
  test = float(sys.argv[2]) * len(lines)
  count = 0
  f = None
  for line in lines:
  	if count % divider == 0:
  		if not f == None:
  			f.close()
  		if count < test:
  			f = open('testdata/'+str(int(count/divider))+'.in', 'w')
  		else:
  			f = open('traindata/'+str(int(count/divider))+'.in', 'w')
  	f.write(line)
  	count += 1
  if not f == None:
  	f.close()
  