lotus/lib/stati/meanvar.go

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package stati
import (
"fmt"
"math"
)
type MeanVar struct {
n float64
mean float64
m2 float64
}
func (v1 *MeanVar) AddPoint(value float64) {
// based on https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Welford's_online_algorithm
v1.n++
delta := value - v1.mean
v1.mean += delta / v1.n
delta2 := value - v1.mean
v1.m2 += delta * delta2
}
func (v1 *MeanVar) Mean() float64 {
return v1.mean
}
func (v1 *MeanVar) N() float64 {
return v1.n
}
func (v1 *MeanVar) Variance() float64 {
return v1.m2 / (v1.n - 1)
}
func (v1 *MeanVar) Stddev() float64 {
return math.Sqrt(v1.Variance())
}
func (v1 MeanVar) String() string {
return fmt.Sprintf("%f stddev: %f (%.0f)", v1.Mean(), v1.Stddev(), v1.N())
}
func (v1 *MeanVar) Combine(v2 *MeanVar) {
if v1.n == 0 {
*v1 = *v2
return
}
if v2.n == 0 {
return
}
if v1.n == 1 {
cpy := *v2
cpy.AddPoint(v1.mean)
*v1 = cpy
return
}
if v2.n == 1 {
v1.AddPoint(v2.mean)
return
}
newCount := v1.n + v2.n
delta := v2.mean - v1.mean
meanDelta := delta * v2.n / newCount
m2 := v1.m2 + v2.m2 + delta*meanDelta*v1.n
v1.n = newCount
v1.mean += meanDelta
v1.m2 = m2
}