Files
nofx/market/data_indicators.go
T
tinkle-community cb31782be4 refactor: split large files and clean up project structure
- Rename experience/ to telemetry/ for clarity
- Split 15+ large Go files (800-2200 lines) into focused modules:
  kernel/engine.go, backtest/runner.go, market/data.go, store/position.go,
  api/handler_trader.go, trader/auto_trader_grid.go, and 9 exchange traders
- Split frontend monoliths: types.ts, api.ts, AITradersPage.tsx, BacktestPage.tsx
  into domain-specific modules with barrel re-exports
- Remove stale files: screenshots, .yml.old, pyproject.toml
- Remove unused scripts/ and cmd/ directories
- Remove broken/outdated test files (network-dependent, stale expectations)
2026-03-12 12:53:57 +08:00

236 lines
5.6 KiB
Go

package market
import "math"
// calculateEMA calculates EMA
func calculateEMA(klines []Kline, period int) float64 {
if len(klines) < period {
return 0
}
// Calculate SMA as initial EMA
sum := 0.0
for i := 0; i < period; i++ {
sum += klines[i].Close
}
ema := sum / float64(period)
// Calculate EMA
multiplier := 2.0 / float64(period+1)
for i := period; i < len(klines); i++ {
ema = (klines[i].Close-ema)*multiplier + ema
}
return ema
}
// calculateMACD calculates MACD
func calculateMACD(klines []Kline) float64 {
if len(klines) < 26 {
return 0
}
// Calculate 12-period and 26-period EMA
ema12 := calculateEMA(klines, 12)
ema26 := calculateEMA(klines, 26)
// MACD = EMA12 - EMA26
return ema12 - ema26
}
// calculateRSI calculates RSI
func calculateRSI(klines []Kline, period int) float64 {
if len(klines) <= period {
return 0
}
gains := 0.0
losses := 0.0
// Calculate initial average gain/loss
for i := 1; i <= period; i++ {
change := klines[i].Close - klines[i-1].Close
if change > 0 {
gains += change
} else {
losses += -change
}
}
avgGain := gains / float64(period)
avgLoss := losses / float64(period)
// Use Wilder smoothing method to calculate subsequent RSI
for i := period + 1; i < len(klines); i++ {
change := klines[i].Close - klines[i-1].Close
if change > 0 {
avgGain = (avgGain*float64(period-1) + change) / float64(period)
avgLoss = (avgLoss * float64(period-1)) / float64(period)
} else {
avgGain = (avgGain * float64(period-1)) / float64(period)
avgLoss = (avgLoss*float64(period-1) + (-change)) / float64(period)
}
}
if avgLoss == 0 {
return 100
}
rs := avgGain / avgLoss
rsi := 100 - (100 / (1 + rs))
return rsi
}
// calculateATR calculates ATR
func calculateATR(klines []Kline, period int) float64 {
if len(klines) <= period {
return 0
}
trs := make([]float64, len(klines))
for i := 1; i < len(klines); i++ {
high := klines[i].High
low := klines[i].Low
prevClose := klines[i-1].Close
tr1 := high - low
tr2 := math.Abs(high - prevClose)
tr3 := math.Abs(low - prevClose)
trs[i] = math.Max(tr1, math.Max(tr2, tr3))
}
// Calculate initial ATR
sum := 0.0
for i := 1; i <= period; i++ {
sum += trs[i]
}
atr := sum / float64(period)
// Wilder smoothing
for i := period + 1; i < len(klines); i++ {
atr = (atr*float64(period-1) + trs[i]) / float64(period)
}
return atr
}
// calculateBOLL calculates Bollinger Bands (upper, middle, lower)
// period: typically 20, multiplier: typically 2
func calculateBOLL(klines []Kline, period int, multiplier float64) (upper, middle, lower float64) {
if len(klines) < period {
return 0, 0, 0
}
// Calculate SMA (middle band)
sum := 0.0
for i := len(klines) - period; i < len(klines); i++ {
sum += klines[i].Close
}
sma := sum / float64(period)
// Calculate standard deviation
variance := 0.0
for i := len(klines) - period; i < len(klines); i++ {
diff := klines[i].Close - sma
variance += diff * diff
}
stdDev := math.Sqrt(variance / float64(period))
// Calculate bands
middle = sma
upper = sma + multiplier*stdDev
lower = sma - multiplier*stdDev
return upper, middle, lower
}
// calculateDonchian calculates Donchian channel (highest high, lowest low) for given period
func calculateDonchian(klines []Kline, period int) (upper, lower float64) {
if len(klines) == 0 || period <= 0 {
return 0, 0
}
// Use all available klines if period > len(klines)
start := len(klines) - period
if start < 0 {
start = 0
}
upper = klines[start].High
lower = klines[start].Low
for i := start + 1; i < len(klines); i++ {
if klines[i].High > upper {
upper = klines[i].High
}
if klines[i].Low < lower {
lower = klines[i].Low
}
}
return upper, lower
}
// Box period constants (in 1h candles)
const (
ShortBoxPeriod = 72 // 3 days of 1h candles
MidBoxPeriod = 240 // 10 days of 1h candles
LongBoxPeriod = 500 // ~21 days of 1h candles
)
// calculateBoxData calculates multi-period box data from klines
func calculateBoxData(klines []Kline, currentPrice float64) *BoxData {
box := &BoxData{
CurrentPrice: currentPrice,
}
if len(klines) == 0 {
return box
}
box.ShortUpper, box.ShortLower = calculateDonchian(klines, ShortBoxPeriod)
box.MidUpper, box.MidLower = calculateDonchian(klines, MidBoxPeriod)
box.LongUpper, box.LongLower = calculateDonchian(klines, LongBoxPeriod)
return box
}
// ========== Exported indicator calculation functions (for testing) ==========
// ExportCalculateEMA exports calculateEMA for testing
func ExportCalculateEMA(klines []Kline, period int) float64 {
return calculateEMA(klines, period)
}
// ExportCalculateMACD exports calculateMACD for testing
func ExportCalculateMACD(klines []Kline) float64 {
return calculateMACD(klines)
}
// ExportCalculateRSI exports calculateRSI for testing
func ExportCalculateRSI(klines []Kline, period int) float64 {
return calculateRSI(klines, period)
}
// ExportCalculateATR exports calculateATR for testing
func ExportCalculateATR(klines []Kline, period int) float64 {
return calculateATR(klines, period)
}
// ExportCalculateBOLL exports calculateBOLL for testing
func ExportCalculateBOLL(klines []Kline, period int, multiplier float64) (upper, middle, lower float64) {
return calculateBOLL(klines, period, multiplier)
}
// ExportCalculateDonchian exports calculateDonchian for testing
func ExportCalculateDonchian(klines []Kline, period int) (float64, float64) {
return calculateDonchian(klines, period)
}
// ExportCalculateBoxData exports calculateBoxData for testing
func ExportCalculateBoxData(klines []Kline, currentPrice float64) *BoxData {
return calculateBoxData(klines, currentPrice)
}