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