code: func entropyScore(n *Node) int64 {
  	score := float64(0)
  
  	if len(n.In) == 0 {
  		score++ // Favor entry nodes
  	} else {
  		score += edgeEntropyScore(n, n.In, 0)
  	}
  
  	if len(n.Out) == 0 {
  		score++ // Favor leaf nodes
  	} else {
  		score += edgeEntropyScore(n, n.Out, n.Flat)
  	}
  
  	return int64(score*float64(n.Cum)) + n.Flat
  }
docs: // entropyScore computes a score for a node representing how important
  // it is to include this node on a graph visualization. It is used to
  // sort the nodes and select which ones to display if we have more
  // nodes than desired in the graph. This number is computed by looking
  // at the flat and cum weights of the node and the incoming/outgoing
  // edges. The fundamental idea is to penalize nodes that have a simple
  // fallthrough from their incoming to the outgoing edge.