14 changed files with 564 additions and 62 deletions
@ -1,21 +1,65 @@
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package sig |
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import "sig-pub/pkg/indicator" |
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import ( |
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"fmt" |
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"sig-pub/pkg/indicator" |
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) |
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type IndicatorSummary struct { |
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indicator.IIndicatorSummary |
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indicatorContext IOffsetIndicatorContext |
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summaryIndicator indicator.ISummaryIndicator |
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summaryIndicatorNewer func() indicator.ISummaryIndicator |
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cachedSummaryIndicators map[string]indicator.ISummaryIndicator |
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} |
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func NewIndicatorSummary(summaryIndicator indicator.ISummaryIndicator, indicatorContext IOffsetIndicatorContext) *IndicatorSummary { |
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func NewIndicatorSummary(summaryIndicatorNewer func() indicator.ISummaryIndicator, indicatorContext IOffsetIndicatorContext) *IndicatorSummary { |
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return &IndicatorSummary{ |
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summaryIndicator: summaryIndicator, |
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summaryIndicatorNewer: summaryIndicatorNewer, |
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indicatorContext: indicatorContext, |
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cachedSummaryIndicators: make(map[string]indicator.ISummaryIndicator), |
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} |
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} |
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func (s *IndicatorSummary) Summary(offset, count int16) (summary any, ok bool) { |
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// Summary 0 10, 0 20, 1 30
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func (s *IndicatorSummary) Summary(offset, count int16) (summary any, rok bool) { |
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key := fmt.Sprintf("%d,%d", offset, count) |
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summaryIndicator, ok := s.cachedSummaryIndicators[key] |
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if ok { |
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s.indicatorContext.AddOffset(offset + count + 1) |
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eliminater, ok := summaryIndicator.(indicator.ISummaryIndicatorEliminater) |
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if ok { |
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eliminater.Eliminate(s.indicatorContext) |
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} |
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s.indicatorContext.AddOffset(-(offset + count + 1)) |
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s.indicatorContext.AddOffset(offset) |
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summaryIndicator.Accumulate(s.indicatorContext) |
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summary, ok = summaryIndicator.Summary(s.indicatorContext) |
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s.indicatorContext.AddOffset(-offset) |
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return |
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} |
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// 初始化, 计算全量数据
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summaryIndicator = s.summaryIndicatorNewer() |
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if err := summaryIndicator.Init(s.indicatorContext.Input()); err != nil { |
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panic(err) |
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} |
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s.cachedSummaryIndicators[key] = summaryIndicator |
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// 设置当前相对offset
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offset = offset + count |
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s.indicatorContext.AddOffset(offset) |
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for range count { |
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summaryIndicator.Accumulate(s.indicatorContext) |
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offset-- |
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s.indicatorContext.AddOffset(-1) |
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} |
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// 获取结果
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summary, rok = summaryIndicator.Summary(s.indicatorContext) |
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// 计算结束后还原offset
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s.indicatorContext.AddOffset(-offset) |
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return |
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} |
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@ -1,47 +1,259 @@
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package indicator |
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import "sig-pub/pkg/types" |
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import ( |
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"math" |
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"sig-pub/pkg/types" |
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"sig-pub/pkg/zlog" |
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) |
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// VRVP 成交量分布图
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const ( |
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MaxRawBuckets = 2000 // 最大原始分桶数量，超过此数量将进行合并
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) |
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// VRVP Volume Profile (Visible Range Volume Profile)
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// 成交量分布图: 显示特定时间段内各价格水平的成交量分布
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type VRVP struct { |
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buckets int // 价格行数
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minPrice float64 // 最低价
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maxPrice float64 // 最高价
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// 流式计算状态
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baseStep float64 // 当前的基础步长
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rawBuckets map[int64]*types.VRVPBucket // 原始分桶数据, key = int64(price / baseStep)
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klines int64 // 累计K线数量
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skts, ekts int64 // 开始时间戳, 结束时间戳
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} |
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func (c *VRVP) Meta() IndicatorMeta { |
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return IndicatorMeta{ |
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Name: "VRVP", |
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Desc: "成交量分布图", |
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Input: []types.InputArg{ |
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{Name: "window", Type: types.InputTypeUInt, Desc: "窗口大小", Default: 10}, |
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}, |
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State: []string{"sig"}, |
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Plots: []Plot{ |
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{Name: "RVI", State: "vector", Type: PlotLine, Props: PlotProps{"color": ColorGreen}}, |
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{Name: "Signal", State: "sig", Type: PlotLine, Props: PlotProps{"color": ColorRed}}, |
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{Name: "buckets", Type: types.InputTypeUInt, Desc: "价格分桶数量", Default: 24}, |
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}, |
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} |
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} |
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func (s *VRVP) Init(input types.Input) (err error) { // 校验参数并初始化
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// s.rate = input.Float("rate")
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// s.rate2 = input.Float("rate2")
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// Init 初始化参数
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func (v *VRVP) Init(input types.Input) (err error) { |
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v.buckets = input.Int("buckets") |
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if v.buckets <= 0 { |
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v.buckets = 24 |
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} |
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v.minPrice = math.MaxFloat64 |
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v.maxPrice = -math.MaxFloat64 |
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v.rawBuckets = make(map[int64]*types.VRVPBucket) |
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v.baseStep = 0 |
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return |
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} |
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// Accumulate 计算累加值
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func (v *VRVP) Accumulate(ctx IIndicatorContext) { |
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func (v *VRVP) CandlePeriods(ctx IIndicatorContext) int16 { |
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return 1 |
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} |
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// Summary 计算完毕获取计算结果
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func (v *VRVP) Summary(ctx IIndicatorContext) (summary any, ok bool) { |
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// Eliminate 清除这根K线的数据
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func (v *VRVP) Eliminate(ctx IIndicatorContext) { |
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k := ctx.Get(0) |
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high := k.HighF64() |
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low := k.LowF64() |
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vol := k.VolF64() |
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if vol <= 0 { |
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return |
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} |
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v.klines-- |
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// 限制说明 ：在流式计算模式下，无法精确回滚 minPrice 、 maxPrice 以及 baseStep 的历史变化。
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// 这意味着在长期运行后，分布图的统计范围可能会比实际存在的 K 线范围略大，但这不影响分布形状的准确性。
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if v.baseStep <= 0 { |
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return |
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} |
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// 将成交量从原始桶中移除
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startIdx := int64(math.Floor(low / v.baseStep)) |
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endIdx := int64(math.Floor(high / v.baseStep)) |
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coveredBuckets := float64(endIdx - startIdx + 1) |
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volPerBucket := vol / coveredBuckets |
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isUp := k.CloseF64() >= k.OpenF64() |
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for i := startIdx; i <= endIdx; i++ { |
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bucket, exists := v.rawBuckets[i] |
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if !exists { |
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continue |
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} |
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bucket.Volume -= volPerBucket |
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if isUp { |
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bucket.BuyVol -= volPerBucket |
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} else { |
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bucket.SellVol -= volPerBucket |
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} |
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// 如果桶的成交量归零（考虑浮点误差），则移除该桶以节省内存
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if bucket.Volume < 1e-8 { |
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delete(v.rawBuckets, i) |
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} |
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} |
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} |
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// Accumulate 累积每根K线的数据
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func (v *VRVP) Accumulate(ctx IIndicatorContext) { |
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k := ctx.Get(0) |
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high := k.HighF64() |
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low := k.LowF64() |
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vol := k.VolF64() |
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v.klines++ |
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if v.skts == 0 { |
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v.skts = k.Ts |
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} |
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v.ekts = k.Ts |
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if vol <= 0 { |
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return |
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} |
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// 更新全局极值
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if high > v.maxPrice { |
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v.maxPrice = high |
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} |
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if low < v.minPrice { |
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v.minPrice = low |
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} |
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// 初始化 baseStep
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if v.baseStep == 0 { |
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// 如果 K 线有波动，使用波动的一小部分作为初始精度
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// 如果无波动(High==Low)，使用价格的万分之一
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if high > low { |
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v.baseStep = (high - low) / 100.0 |
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} else { |
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if low > 0 { |
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v.baseStep = low * 0.0001 |
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} else { |
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v.baseStep = 0.01 // 默认值
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} |
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} |
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} |
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// 将成交量分配到原始桶中
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startIdx := int64(math.Floor(low / v.baseStep)) |
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endIdx := int64(math.Floor(high / v.baseStep)) |
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coveredBuckets := float64(endIdx - startIdx + 1) |
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volPerBucket := vol / coveredBuckets |
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isUp := k.CloseF64() >= k.OpenF64() |
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for i := startIdx; i <= endIdx; i++ { |
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bucket, exists := v.rawBuckets[i] |
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if !exists { |
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bucket = &types.VRVPBucket{ |
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Price: float64(i)*v.baseStep + v.baseStep/2, // 暂存中心价
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} |
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v.rawBuckets[i] = bucket |
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} |
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bucket.Volume += volPerBucket |
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if isUp { |
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bucket.BuyVol += volPerBucket |
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} else { |
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bucket.SellVol += volPerBucket |
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} |
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} |
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// 检查是否需要合并桶
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if len(v.rawBuckets) > MaxRawBuckets { |
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v.halveResolution() |
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} |
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} |
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type RVVPSummary struct { |
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TotalVolume float64 |
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Buckets []PriceBucket |
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// halveResolution 将分辨率减半（步长翻倍）
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func (v *VRVP) halveResolution() { |
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newBaseStep := v.baseStep * 2 |
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newBuckets := make(map[int64]*types.VRVPBucket, len(v.rawBuckets)/2+1) |
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for key, bucket := range v.rawBuckets { |
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// 计算新的 key
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// oldPrice ~= key * oldStep
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// newKey = floor(oldPrice / newStep) = floor(key * oldStep / (2 * oldStep)) = floor(key / 2)
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newKey := key >> 1 // key / 2
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newBucket, exists := newBuckets[newKey] |
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if !exists { |
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newBucket = &types.VRVPBucket{ |
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Price: float64(newKey)*newBaseStep + newBaseStep/2, |
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} |
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newBuckets[newKey] = newBucket |
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} |
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newBucket.Volume += bucket.Volume |
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newBucket.BuyVol += bucket.BuyVol |
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newBucket.SellVol += bucket.SellVol |
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} |
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v.baseStep = newBaseStep |
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v.rawBuckets = newBuckets |
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} |
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type PriceBucket struct { |
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Price float64 |
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Volume float64 |
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// Summary 计算最终的成交量分布结果
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// 在所有K线Accumulate完成后调用
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func (v *VRVP) Summary(ctx IIndicatorContext) (summary any, ok bool) { |
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zlog.Debugf("VRVP Summary: klines=%d, skts=%d, ekts=%d, minPrice=%.2f, maxPrice=%.2f, baseStep=%.2f", |
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v.klines, v.skts, v.ekts, v.minPrice, v.maxPrice, v.baseStep) |
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if v.minPrice >= v.maxPrice { |
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return nil, false |
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} |
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// 计算最终的目标步长
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rangeHeight := v.maxPrice - v.minPrice |
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finalStep := rangeHeight / float64(v.buckets) |
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// 如果 finalStep 小于当前的 baseStep，说明数据太稀疏，无法满足 rowCount 的精度要求
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// 但通常情况下，由于我们只在桶过多时才合并，baseStep 应该相对较小
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// 初始化最终分桶
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buckets := make([]types.VRVPBucket, v.buckets) |
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for i := 0; i < v.buckets; i++ { |
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buckets[i].Price = v.minPrice + float64(i)*finalStep + finalStep/2 |
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} |
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// 将 rawBuckets 聚合到最终 buckets
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for _, rawB := range v.rawBuckets { |
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// 计算原始桶对应的价格范围中心
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// 注意：rawB.Price 在合并过程中可能不再准确，重新计算更稳妥，或者在合并时更新 Price
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// 这里我们使用 key 重新计算，更准确
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// 但由于 map key 不在 value 中，我们无法直接获取 key
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// 所以我们需要遍历 map 的 key
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// 修正：在上面的循环中我们无法获得 key，所以需要修改遍历方式
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// 或者我们在 PriceBucket 中存储准确的 Price
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// 在 halveResolution 中，我们更新了 Price，所以 rawB.Price 是当前 baseStep 下的中心价
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price := rawB.Price |
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// 找到对应的最终桶索引
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idx := int((price - v.minPrice) / finalStep) |
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if idx < 0 { |
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idx = 0 |
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} else if idx >= v.buckets { |
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idx = v.buckets - 1 |
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} |
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buckets[idx].Volume += rawB.Volume |
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buckets[idx].BuyVol += rawB.BuyVol |
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buckets[idx].SellVol += rawB.SellVol |
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} |
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ok, summary = true, &types.VRVPSummary{ |
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Klines: v.klines, |
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Step: finalStep, |
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MinPrice: v.minPrice, |
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MaxPrice: v.maxPrice, |
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Buckets: buckets, |
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} |
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return |
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} |
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@ -0,0 +1,16 @@
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package types |
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// VRVPSummary 成交量分布图指标计算结果
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type VRVPSummary struct { |
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Klines int64 `json:"klines"` |
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Step float64 `json:"step"` // 每个桶的价格高度
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MinPrice float64 `json:"minPrice"` // 统计范围最低价
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MaxPrice float64 `json:"maxPrice"` // 统计范围最高价
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Buckets []VRVPBucket `json:"buckets"` |
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} |
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type VRVPBucket struct { |
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Price float64 `json:"price"` // 桶代表价格
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Volume float64 `json:"volume"` // 总成交量
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BuyVol float64 `json:"buyVol"` // 主动买入量(近似)
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SellVol float64 `json:"sellVol"` // 主动卖出量(近似)
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} |
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Reference in new issue