def makeNet(self):
net = NeuralNet(self.inSize, self.outSize, self.hidSize)
weights = [[0]*self.size() for i in xrange(self.size())]
for c in self.conn:
weights[c.fro][c.to] += c.w if c.on else 0
for i in xrange(self.size()):
for j in xrange(self.size()):
net.addSynapse(i,j,weights[i][j]) if weights[i][j] != 0 else 0 #[net.addSynapse(s.fro, s.to, s.w) for s in self.conn if s.on]
return net
