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