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feature: dmi add test, fix: rma with Adjust setting (follow the implementation of pandas.DataFrame.ewm)
This commit is contained in:
zenix
parent
0a4379eec9
commit
126974cd79
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@ -25,7 +25,10 @@ func (inc *ATR) Update(high, low, cloze float64) {
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}
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if inc.RMA == nil {
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inc.RMA = &RMA{IntervalWindow: types.IntervalWindow{Window: inc.Window}}
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inc.RMA = &RMA{
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IntervalWindow: types.IntervalWindow{Window: inc.Window},
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Adjust: true,
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}
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inc.PreviousClose = cloze
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return
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}
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@ -9,6 +9,25 @@ import (
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"github.com/c9s/bbgo/pkg/types"
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)
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/*
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python
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import pandas as pd
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import pandas_ta as ta
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data = {
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"high": [40145.0, 40186.36, 40196.39, 40344.6, 40245.48, 40273.24, 40464.0, 40699.0, 40627.48, 40436.31, 40370.0, 40376.8, 40227.03, 40056.52, 39721.7, 39597.94, 39750.15, 39927.0, 40289.02, 40189.0],
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"low": [39870.71, 39834.98, 39866.31, 40108.31, 40016.09, 40094.66, 40105.0, 40196.48, 40154.99, 39800.0, 39959.21, 39922.98, 39940.02, 39632.0, 39261.39, 39254.63, 39473.91, 39555.51, 39819.0, 40006.84],
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"close": [40105.78, 39935.23, 40183.97, 40182.03, 40212.26, 40149.99, 40378.0, 40618.37, 40401.03, 39990.39, 40179.13, 40097.23, 40014.72, 39667.85, 39303.1, 39519.99,
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39693.79, 39827.96, 40074.94, 40059.84]
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}
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high = pd.Series(data['high'])
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low = pd.Series(data['low'])
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close = pd.Series(data['close'])
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result = ta.atr(high, low, close, length=14)
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print(result)
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*/
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func Test_calculateATR(t *testing.T) {
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var bytes = []byte(`{
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"high": [40145.0, 40186.36, 40196.39, 40344.6, 40245.48, 40273.24, 40464.0, 40699.0, 40627.48, 40436.31, 40370.0, 40376.8, 40227.03, 40056.52, 39721.7, 39597.94, 39750.15, 39927.0, 40289.02, 40189.0],
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@ -35,7 +54,7 @@ func Test_calculateATR(t *testing.T) {
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name: "test_binance_btcusdt_1h",
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kLines: buildKLines(bytes),
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window: 14,
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want: 364.048648,
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want: 367.913903,
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},
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}
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@ -28,9 +28,9 @@ type DMI struct {
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func (inc *DMI) Update(high, low, cloze float64) {
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if inc.DMP == nil || inc.DMN == nil {
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inc.DMP = &RMA{IntervalWindow: inc.IntervalWindow}
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inc.DMN = &RMA{IntervalWindow: inc.IntervalWindow}
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inc.ADX = &RMA{IntervalWindow: types.IntervalWindow{Window: inc.ADXSmoothing}}
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inc.DMP = &RMA{IntervalWindow: inc.IntervalWindow, Adjust: true}
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inc.DMN = &RMA{IntervalWindow: inc.IntervalWindow, Adjust: true}
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inc.ADX = &RMA{IntervalWindow: types.IntervalWindow{Window: inc.ADXSmoothing}, Adjust: true}
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}
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if inc.atr == nil {
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inc.atr = &ATR{IntervalWindow: inc.IntervalWindow}
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@ -56,15 +56,19 @@ func (inc *DMI) Update(high, low, cloze float64) {
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neg = dn
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}
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k := 100. / inc.atr.Last()
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inc.DMP.Update(pos)
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inc.DMN.Update(neg)
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if inc.atr.Length() < inc.Window {
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return
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}
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k := 100. / inc.atr.Last()
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dmp := inc.DMP.Last()
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dmn := inc.DMN.Last()
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inc.DIPlus.Update(k * dmp)
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inc.DIMinus.Update(k * dmn)
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dx := 100. * k * math.Abs(dmp-dmn) / (dmp + dmn)
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dx := 100. * math.Abs(dmp-dmn) / (dmp + dmn)
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inc.ADX.Update(dx)
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}
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func (inc *DMI) GetDIPlus() types.Series {
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83
pkg/indicator/dmi_test.go
Normal file
83
pkg/indicator/dmi_test.go
Normal file
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@ -0,0 +1,83 @@
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package indicator
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import (
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"encoding/json"
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"testing"
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"fmt"
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"github.com/c9s/bbgo/pkg/fixedpoint"
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"github.com/c9s/bbgo/pkg/types"
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"github.com/stretchr/testify/assert"
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)
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/*
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python:
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import pandas as pd
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import pandas_ta as ta
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data = 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])
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high = pd.Series([100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109])
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low = pd.Series([80,81,82,83,84,85,86,87,88,89,80,81,82,83,84,85,86,87,88,89,80,81,82,83,84,85,86,87,88,89])
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close = pd.Series([90,91,92,93,94,95,96,97,98,99,90,91,92,93,94,95,96,97,98,99,90,91,92,93,94,95,96,97,98,99])
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result = ta.adx(high, low, close, 5, 14)
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print(result['ADX_14'])
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print(result['DMP_5'])
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print(result['DMN_5'])
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*/
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func Test_DMI(t *testing.T) {
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var Delta = 0.001
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var highb = []byte(`[100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109]`)
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var lowb = []byte(`[80,81,82,83,84,85,86,87,88,89,80,81,82,83,84,85,86,87,88,89,80,81,82,83,84,85,86,87,88,89]`)
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var clozeb = []byte(`[90,91,92,93,94,95,96,97,98,99,90,91,92,93,94,95,96,97,98,99,90,91,92,93,94,95,96,97,98,99]`)
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buildKLines := func(h, l, c []byte) (klines []types.KLine) {
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var hv, cv, lv []fixedpoint.Value
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_ = json.Unmarshal(h, &hv)
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_ = json.Unmarshal(l, &lv)
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_ = json.Unmarshal(c, &cv)
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if len(hv) != len(lv) || len(lv) != len(cv) {
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panic(fmt.Sprintf("length not equal %v %v %v", len(hv), len(lv), len(cv)))
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}
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for i, hh := range hv {
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kline := types.KLine{High: hh, Low: lv[i], Close: cv[i]}
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klines = append(klines, kline)
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}
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return klines
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}
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type output struct{dip float64; dim float64; adx float64}
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tests := []struct {
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name string
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klines []types.KLine
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want output
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next output
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total int
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}{
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{
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name: "test_dmi",
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klines: buildKLines(highb, lowb, clozeb),
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want: output{dip: 4.85114, dim: 1.339736, adx: 37.857156},
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next: output{dip: 4.813853, dim: 1.67532, adx: 36.111434},
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},
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}
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for _, tt := range tests {
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t.Run(tt.name, func(t *testing.T) {
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dmi := &DMI{
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IntervalWindow: types.IntervalWindow{Window: 5},
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ADXSmoothing: 14,
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}
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dmi.calculateAndUpdate(tt.klines)
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assert.InDelta(t, dmi.GetDIPlus().Last(), tt.want.dip, Delta)
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assert.InDelta(t, dmi.GetDIMinus().Last(), tt.want.dim, Delta)
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assert.InDelta(t, dmi.GetADX().Last(), tt.want.adx, Delta)
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})
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}
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}
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@ -6,33 +6,42 @@ import (
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"github.com/c9s/bbgo/pkg/types"
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)
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// Refer: Running Moving Average
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// Running Moving Average
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// Refer: https://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/overlap/rma.py#L5
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// Refer: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.ewm.html#pandas-dataframe-ewm
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//go:generate callbackgen -type RMA
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type RMA struct {
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types.IntervalWindow
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Values types.Float64Slice
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Sources types.Float64Slice
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counter int
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Adjust bool
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tmp float64
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sum float64
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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 *RMA) Update(x float64) {
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inc.Sources.Push(x)
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lambda := 1 / float64(inc.Window)
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if inc.counter == 0 {
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inc.sum = 1
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inc.tmp = x
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} else {
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if inc.Adjust {
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inc.sum = inc.sum*(1-lambda) + 1
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inc.tmp = inc.tmp + (x-inc.tmp)/inc.sum
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} else {
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inc.tmp = inc.tmp*(1-lambda) + x*lambda
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}
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}
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inc.counter++
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if len(inc.Sources) < inc.Window {
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if inc.counter < inc.Window {
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inc.Values.Push(0)
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return
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}
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if len(inc.Sources) == inc.Window {
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inc.Values.Push(inc.Sources.Mean())
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return
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}
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lambda := 1 / float64(inc.Window)
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rma := (1-lambda)*inc.Values.Last() + lambda*x
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inc.Values.Push(rma)
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inc.Values.Push(inc.tmp)
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}
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func (inc *RMA) Last() float64 {
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