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continuous_averager.go
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continuous_averager.go
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// Copyright (C) 2019-2023, Ava Labs, Inc. All rights reserved.
// See the file LICENSE for licensing terms.
package math
import (
"math"
"time"
)
var convertEToBase2 = math.Log(2)
type continuousAverager struct {
halflife float64
weightedSum float64
normalizer float64
lastUpdated time.Time
}
// NewUninitializedAverager creates a new averager with the given halflife. If
// [Read] is called before [Observe], the zero value will be returned. When
// [Observe] is called the first time, the averager will be initialized with
// [value] at that time.
func NewUninitializedAverager(halfLife time.Duration) Averager {
// Use 0 as the initialPrediction and 0 as the currentTime, so that when the
// first observation occurs (at a non-zero time) the initial prediction's
// weight will become negligible.
return NewAverager(0, halfLife, time.Time{})
}
func NewAverager(
initialPrediction float64,
halflife time.Duration,
currentTime time.Time,
) Averager {
return &continuousAverager{
halflife: float64(halflife) / convertEToBase2,
weightedSum: initialPrediction,
normalizer: 1,
lastUpdated: currentTime,
}
}
func (a *continuousAverager) Observe(value float64, currentTime time.Time) {
delta := a.lastUpdated.Sub(currentTime)
switch {
case delta < 0:
// If the times are called in order, scale the previous values to keep the
// sizes manageable
newWeight := math.Exp(float64(delta) / a.halflife)
a.weightedSum = value + newWeight*a.weightedSum
a.normalizer = 1 + newWeight*a.normalizer
a.lastUpdated = currentTime
case delta == 0:
// If this is called multiple times at the same wall clock time, no
// scaling needs to occur
a.weightedSum += value
a.normalizer++
default:
// If the times are called out of order, don't scale the previous values
newWeight := math.Exp(float64(-delta) / a.halflife)
a.weightedSum += newWeight * value
a.normalizer += newWeight
}
}
func (a *continuousAverager) Read() float64 {
return a.weightedSum / a.normalizer
}