lnd version, "hacked" to enable seedless restore from xprv + scb
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package autopilot
import (
"errors"
"fmt"
"math/rand"
)
// ErrNoPositive is returned from weightedChoice when there are no positive
// weights left to choose from.
var ErrNoPositive = errors.New("no positive weights left")
// weightedChoice draws a random index from the slice of weights, with a
// probability propotional to the weight at the given index.
func weightedChoice(w []float64) (int, error) {
// Calculate the sum of weights.
var sum float64
for _, v := range w {
sum += v
}
if sum <= 0 {
return 0, ErrNoPositive
}
// Pick a random number in the range [0.0, 1.0) and multiply it with
// the sum of weights. Then we'll iterate the weights until the number
// goes below 0. This means that each index is picked with a probablity
// equal to their normalized score.
//
// Example:
// Items with scores [1, 5, 2, 2]
// Normalized scores [0.1, 0.5, 0.2, 0.2]
// Imagine they each occupy a "range" equal to their normalized score
// in [0, 1.0]:
// [|-0.1-||-----0.5-----||--0.2--||--0.2--|]
// The following loop is now equivalent to "hitting" the intervals.
r := rand.Float64() * sum
for i := range w {
r -= w[i]
if r <= 0 {
return i, nil
}
}
return 0, fmt.Errorf("unable to make choice")
}
// chooseN picks at random min[n, len(s)] nodes if from the NodeScore map, with
// a probability weighted by their score.
func chooseN(n uint32, s map[NodeID]*NodeScore) (
map[NodeID]*NodeScore, error) {
// Keep track of the number of nodes not yet chosen, in addition to
// their scores and NodeIDs.
rem := len(s)
scores := make([]float64, len(s))
nodeIDs := make([]NodeID, len(s))
i := 0
for k, v := range s {
scores[i] = v.Score
nodeIDs[i] = k
i++
}
// Pick a weighted choice from the remaining nodes as long as there are
// nodes left, and we haven't already picked n.
chosen := make(map[NodeID]*NodeScore)
for len(chosen) < int(n) && rem > 0 {
choice, err := weightedChoice(scores)
if err == ErrNoPositive {
return chosen, nil
} else if err != nil {
return nil, err
}
nID := nodeIDs[choice]
chosen[nID] = s[nID]
// We set the score of the chosen node to 0, so it won't be
// picked the next iteration.
scores[choice] = 0
}
return chosen, nil
}