97 lines
2.3 KiB
Go
97 lines
2.3 KiB
Go
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package fmaker
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import (
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"fmt"
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"math"
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"time"
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"git.qtrade.icu/lychiyu/bbgo/pkg/datatype/floats"
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"git.qtrade.icu/lychiyu/bbgo/pkg/indicator"
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"git.qtrade.icu/lychiyu/bbgo/pkg/types"
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)
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//go:generate callbackgen -type S2
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type S2 struct {
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types.IntervalWindow
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Values floats.Slice
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EndTime time.Time
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UpdateCallbacks []func(value float64)
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}
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func (inc *S2) Last(int) float64 {
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if len(inc.Values) == 0 {
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return 0.0
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}
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return inc.Values[len(inc.Values)-1]
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}
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func (inc *S2) CalculateAndUpdate(klines []types.KLine) {
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if len(klines) < inc.Window {
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return
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}
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var end = len(klines) - 1
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var lastKLine = klines[end]
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if inc.EndTime != zeroTime && lastKLine.GetEndTime().Before(inc.EndTime) {
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return
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}
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var recentT = klines[end-(inc.Window-1) : end+1]
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correlation, err := calculateS2(recentT, inc.Window, types.KLineOpenPriceMapper, types.KLineVolumeMapper)
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if err != nil {
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log.WithError(err).Error("can not calculate correlation")
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return
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}
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inc.Values.Push(correlation)
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if len(inc.Values) > indicator.MaxNumOfVOL {
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inc.Values = inc.Values[indicator.MaxNumOfVOLTruncateSize-1:]
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}
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inc.EndTime = klines[end].GetEndTime().Time()
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inc.EmitUpdate(correlation)
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}
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func (inc *S2) handleKLineWindowUpdate(interval types.Interval, window types.KLineWindow) {
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if inc.Interval != interval {
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return
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}
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inc.CalculateAndUpdate(window)
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}
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func (inc *S2) Bind(updater indicator.KLineWindowUpdater) {
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updater.OnKLineWindowUpdate(inc.handleKLineWindowUpdate)
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}
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func calculateS2(klines []types.KLine, window int, valA KLineValueMapper, valB KLineValueMapper) (float64, error) {
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length := len(klines)
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if length == 0 || length < window {
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return 0.0, fmt.Errorf("insufficient elements for calculating VOL with window = %d", window)
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}
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sumA, sumB, sumAB, squareSumA, squareSumB := 0., 0., 0., 0., 0.
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for _, k := range klines {
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// sum of elements of array A
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sumA += valA(k)
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// sum of elements of array B
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sumB += valB(k)
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// sum of A[i] * B[i].
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sumAB = sumAB + valA(k)*valB(k)
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// sum of square of array elements.
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squareSumA = squareSumA + valA(k)*valA(k)
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squareSumB = squareSumB + valB(k)*valB(k)
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}
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// use formula for calculating correlation coefficient.
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corr := (float64(window)*sumAB - sumA*sumB) /
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math.Sqrt((float64(window)*squareSumA-sumA*sumA)*(float64(window)*squareSumB-sumB*sumB))
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return -corr, nil
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}
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