rewrite cci indicator in v2 indicator

pkg/indicator/cci.go

@@ -11,6 +11,12 @@ import (
 // Refer URL: http://www.andrewshamlet.net/2017/07/08/python-tutorial-cci
 // with modification of ddof=0 to let standard deviation to be divided by N instead of N-1
 //
+// CCI = (Typical Price  -  n-period SMA of TP) / (Constant x Mean Deviation)
+//
+// Typical Price (TP) = (High + Low + Close)/3
+//
+// Constant = .015
+//
 // The Commodity Channel Index (CCI) is a technical analysis indicator that is used to identify potential overbought or oversold conditions
 // in a security's price. It was originally developed for use in commodity markets, but can be applied to any security that has a sufficient
 // amount of price data. The CCI is calculated by taking the difference between the security's typical price (the average of its high, low, and
@@ -43,16 +49,18 @@ func (inc *CCI) Update(value float64) {
 	}
 
 	inc.Input.Push(value)
-	tp := inc.TypicalPrice.Last(0) - inc.Input.Index(inc.Window) + value
+	tp := inc.TypicalPrice.Last(0) - inc.Input.Last(inc.Window) + value
 	inc.TypicalPrice.Push(tp)
 	if len(inc.Input) < inc.Window {
 		return
 	}
+
 	ma := tp / float64(inc.Window)
 	inc.MA.Push(ma)
 	if len(inc.MA) > MaxNumOfEWMA {
 		inc.MA = inc.MA[MaxNumOfEWMATruncateSize-1:]
 	}
+
 	md := 0.
 	for i := 0; i < inc.Window; i++ {
 		diff := inc.Input.Last(i) - ma

pkg/indicator/cci_test.go

@@ -4,8 +4,9 @@ import (
 	"encoding/json"
 	"testing"
 
-	"github.com/c9s/bbgo/pkg/types"
 	"github.com/stretchr/testify/assert"
+
+	"github.com/c9s/bbgo/pkg/types"
 )
 
 /*
@@ -19,7 +20,7 @@ print(cci)
 func Test_CCI(t *testing.T) {
 	var randomPrices = []byte(`[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]`)
 	var input []float64
-	var Delta = 4.3e-2
+	var delta = 4.3e-2
 	if err := json.Unmarshal(randomPrices, &input); err != nil {
 		panic(err)
 	}
@@ -30,8 +31,8 @@ func Test_CCI(t *testing.T) {
 		}
 
 		last := cci.Last(0)
-		assert.InDelta(t, 93.250481, last, Delta)
+		assert.InDelta(t, 93.250481, last, delta)
-		assert.InDelta(t, 81.813449, cci.Index(1), Delta)
+		assert.InDelta(t, 81.813449, cci.Index(1), delta)
 		assert.Equal(t, 50-16+1, cci.Length())
 	})
 }

pkg/indicator/v2/cci.go

@@ -0,0 +1,65 @@
+package indicatorv2
+
+import (
+	"math"
+
+	"github.com/c9s/bbgo/pkg/types"
+)
+
+// Refer: Commodity Channel Index
+// Refer URL: http://www.andrewshamlet.net/2017/07/08/python-tutorial-cci
+// with modification of ddof=0 to let standard deviation to be divided by N instead of N-1
+//
+// CCI = (Typical Price  -  n-period SMA of TP) / (Constant x Mean Deviation)
+//
+// Typical Price (TP) = (High + Low + Close)/3
+//
+// Constant = .015
+//
+// The Commodity Channel Index (CCI) is a technical analysis indicator that is used to identify potential overbought or oversold conditions
+// in a security's price. It was originally developed for use in commodity markets, but can be applied to any security that has a sufficient
+// amount of price data. The CCI is calculated by taking the difference between the security's typical price (the average of its high, low, and
+// closing prices) and its moving average, and then dividing the result by the mean absolute deviation of the typical price. This resulting value
+// is then plotted as a line on the price chart, with values above +100 indicating overbought conditions and values below -100 indicating
+// oversold conditions. The CCI can be used by traders to identify potential entry and exit points for trades, or to confirm other technical
+// analysis signals.
+
+type CCIStream struct {
+	*types.Float64Series
+
+	TypicalPrice *types.Float64Series
+
+	source types.Float64Source
+	window int
+}
+
+func CCI(source types.Float64Source, window int) *CCIStream {
+	s := &CCIStream{
+		Float64Series: types.NewFloat64Series(),
+		TypicalPrice:  types.NewFloat64Series(),
+		source:        source,
+		window:        window,
+	}
+	s.Bind(source, s)
+	return s
+}
+
+func (s *CCIStream) Calculate(value float64) float64 {
+	var tp = value
+	if s.TypicalPrice.Length() > 0 {
+		tp = s.TypicalPrice.Last(0) - s.source.Last(s.window) + value
+	}
+
+	s.TypicalPrice.Push(tp)
+
+	ma := tp / float64(s.window)
+	md := 0.
+	for i := 0; i < s.window; i++ {
+		diff := s.source.Last(i) - ma
+		md += diff * diff
+	}
+
+	md = math.Sqrt(md / float64(s.window))
+	cci := (value - ma) / (0.015 * md)
+	return cci
+}

pkg/indicator/v2/cci_test.go

@@ -0,0 +1,39 @@
+package indicatorv2
+
+import (
+	"encoding/json"
+	"testing"
+
+	"github.com/stretchr/testify/assert"
+)
+
+/*
+python:
+
+import pandas as pd
+s = pd.Series([0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9])
+cci = pd.Series((s - s.rolling(16).mean()) / (0.015 * s.rolling(16).std(ddof=0)), name="CCI")
+print(cci)
+*/
+func Test_CCI(t *testing.T) {
+	var randomPrices = []byte(`[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]`)
+	var input []float64
+	var delta = 4.3e-2
+	if err := json.Unmarshal(randomPrices, &input); err != nil {
+		panic(err)
+	}
+	t.Run("random_case", func(t *testing.T) {
+		price := Price(nil, nil)
+		cci := CCI(price, 16)
+		for _, value := range input {
+			price.PushAndEmit(value)
+		}
+
+		t.Logf("cci: %+v", cci.Slice)
+
+		last := cci.Last(0)
+		assert.InDelta(t, 93.250481, last, delta)
+		assert.InDelta(t, 81.813449, cci.Index(1), delta)
+		assert.Equal(t, 50, cci.Length(), "length")
+	})
+}

pkg/indicator/v2/const.go

@@ -0,0 +1,5 @@
+package indicatorv2
+
+import "github.com/c9s/bbgo/pkg/fixedpoint"
+
+var three = fixedpoint.NewFromInt(3)

pkg/indicator/v2/price.go

@@ -65,3 +65,7 @@ func OpenPrices(source KLineSubscription) *PriceStream {
 func Volumes(source KLineSubscription) *PriceStream {
 	return Price(source, types.KLineVolumeMapper)
 }
+
+func HLC3(source KLineSubscription) *PriceStream {
+	return Price(source, types.KLineHLC3Mapper)
+}

pkg/indicator/v2/stoch.go

@@ -47,8 +47,8 @@ func Stoch(source KLineSubscription, window, dPeriod int) *StochStream {
 		lowest := s.lowPrices.Slice.Tail(s.window).Min()
 		highest := s.highPrices.Slice.Tail(s.window).Max()
 
-		var k float64 = 50.0
+		var k = 50.0
-		var d float64 = 0.0
+		var d = 0.0
 
 		if highest != lowest {
 			k = 100.0 * (kLine.Close.Float64() - lowest) / (highest - lowest)

pkg/types/kline.go

@@ -10,14 +10,15 @@ import (
 	"github.com/c9s/bbgo/pkg/style"
 )
 
+var Two = fixedpoint.NewFromInt(2)
+var Three = fixedpoint.NewFromInt(3)
+
 type Direction int
 
 const DirectionUp = 1
 const DirectionNone = 0
 const DirectionDown = -1
 
-var Two = fixedpoint.NewFromInt(2)
-
 type KLineOrWindow interface {
 	GetInterval() string
 	Direction() Direction
@@ -668,6 +669,10 @@ func KLineVolumeMapper(k KLine) float64 {
 	return k.Volume.Float64()
 }
 
+func KLineHLC3Mapper(k KLine) float64 {
+	return k.High.Add(k.Low).Add(k.Close).Div(Three).Float64()
+}
+
 func MapKLinePrice(kLines []KLine, f KLineValueMapper) (prices []float64) {
 	for _, k := range kLines {
 		prices = append(prices, f(k))

pkg/types/series_float64.go

@@ -29,6 +29,10 @@ func (f *Float64Series) Length() int {
 	return len(f.Slice)
 }
 
+func (f *Float64Series) Push(x float64) {
+	f.Slice.Push(x)
+}
+
 func (f *Float64Series) PushAndEmit(x float64) {
 	f.Slice.Push(x)
 	f.EmitUpdate(x)