func (q *WalkKernel) Score(n lattice.Node, population []lattice.Node) float64 {
sampleSize := 10
mean, _ := stats.Mean(stats.Sample(sampleSize, len(population)), func(i int) float64 {
o := population[i]
return n.(*digraph.EmbListNode).Pat.Metric(o.(*digraph.EmbListNode).Pat)
})
return mean
}
func (m *Miner) takeOne(queue []lattice.Node) ([]lattice.Node, lattice.Node) {
s := stats.Sample(10, len(queue))
k := m.Scorer.Kernel(queue, s)
var i int
var ms float64
if len(k) > 0 {
i, ms = stats.Max(stats.Srange(len(k)), func(i int) float64 { return k.Mean(i) })
i = s[i]
} else {
i, ms = stats.Max(s, func(i int) float64 { return m.Scorer.Score(queue[i], queue) })
}
errors.Logf("DEBUG", "max score %v, queue len %v, taking %v", ms, len(queue), queue[i])
return pop(queue, i)
}
func (m *Miner) dropOne(queue []lattice.Node) []lattice.Node {
s := stats.Sample(10, len(queue))
k := m.Scorer.Kernel(queue, s)
var i int
var ms float64
if len(k) > 0 {
i, ms = stats.Min(stats.Srange(len(k)), func(i int) float64 { return k.Mean(i) })
i = s[i]
} else {
i, ms = stats.Min(s, func(i int) float64 { return m.Scorer.Score(queue[i], queue) })
}
errors.Logf("DEBUG", "min score %v, queue len %v, dropping %v", ms, len(queue), queue[i])
queue, _ = pop(queue, i)
return queue
}