Best Keploy code snippet using regression.Bind
strategy.go
Source: strategy.go
...119 iw := types.IntervalWindow{Window: 50, Interval: s.Interval}120 // construct CORR indicator121 s.pvDivergence = &Correlation{IntervalWindow: iw}122 // bind indicator to the data store, so that our callback could be triggered123 s.pvDivergence.Bind(st)124 // s.pvDivergence.OnUpdate(func(corr float64) {125 // //fmt.Printf("now we've got corr: %f\n", corr)126 // })127 windowSize := 360 / s.Interval.Minutes()128 if windowSize == 0 {129 windowSize = 3130 }131 drift := &indicator.Drift{IntervalWindow: types.IntervalWindow{Window: windowSize, Interval: s.Interval}}132 drift.Bind(st)133 s.Alpha = [][]float64{{}, {}, {}, {}, {}, {}}134 s.Ret = []float64{}135 // thetas := []float64{0, 0, 0, 0}136 preCompute := 0137 s.activeMakerOrders = bbgo.NewActiveOrderBook(s.Symbol)138 s.activeMakerOrders.BindStream(session.UserDataStream)139 s.orderStore = bbgo.NewOrderStore(s.Symbol)140 s.orderStore.BindStream(session.UserDataStream)141 if s.Position == nil {142 s.Position = types.NewPositionFromMarket(s.Market)143 }144 s.tradeCollector = bbgo.NewTradeCollector(s.Symbol, s.Position, s.orderStore)145 s.tradeCollector.BindStream(session.UserDataStream)146 session.UserDataStream.OnStart(func() {147 log.Infof("connected")148 })149 s.T = 20150 session.MarketDataStream.OnKLineClosed(func(kline types.KLine) {151 if kline.Symbol != s.Symbol || kline.Interval != s.Interval {152 return153 }154 if err := s.activeMakerOrders.GracefulCancel(ctx, s.session.Exchange); err != nil {155 log.WithError(err).Errorf("graceful cancel order error")156 }157 // amplitude volume divergence158 corr := fixedpoint.NewFromFloat(s.pvDivergence.Last()).Neg()159 // price mean reversion...
main.go
Source: main.go
1package main2import (3 "context"4 "time"5 "github.com/btcsuite/btcd/chaincfg"6 "github.com/ethereum/go-ethereum/accounts/abi/bind"7 "github.com/ethereum/go-ethereum/common"8 "github.com/ethereum/go-ethereum/ethclient"9 "github.com/renproject/enclave-testcase/ethereumbinding"10 "github.com/renproject/multichain"11 "github.com/renproject/multichain/api/utxo"12 "github.com/renproject/multichain/chain/bitcoin"13 "github.com/renproject/multichain/chain/bitcoincash"14 "github.com/renproject/multichain/chain/digibyte"15 "github.com/renproject/multichain/chain/dogecoin"16 "github.com/renproject/multichain/chain/filecoin"17 "github.com/renproject/multichain/chain/solana"18 "github.com/renproject/multichain/chain/terra"19 "github.com/renproject/multichain/chain/zcash"20)21func main() {22 useBitcoin()23 useBitcoinCash()24 useDigibyte()25 useDogecoin()26 useEthereum()27 useFilecoin()28 useSolana()29 useTerra()30 useZcash()31}32func useBitcoin() {33 client := bitcoin.NewClient(bitcoin.DefaultClientOptions())34 txBuilder := bitcoin.NewTxBuilder(&chaincfg.RegressionNetParams)35 tx, _ := txBuilder.BuildTx(nil, nil)36 ctx, cancel := context.WithTimeout(context.Background(), 0*time.Second)37 defer cancel()38 client.LatestBlock(ctx)39 client.Output(ctx, utxo.Outpoint{})40 client.UnspentOutput(ctx, utxo.Outpoint{})41 client.SubmitTx(ctx, tx)42 client.UnspentOutputs(ctx, 0, 0, "")43 client.Confirmations(ctx, []byte{})44 client.EstimateSmartFee(ctx, 0)45 client.EstimateFeeLegacy(ctx, 0)46}47func useBitcoinCash() {48 bitcoincash.NewClient(bitcoincash.DefaultClientOptions())49 bitcoincash.NewTxBuilder(&chaincfg.RegressionNetParams)50}51func useDigibyte() {52 digibyte.NewClient(digibyte.DefaultClientOptions())53 digibyte.NewTxBuilder(&digibyte.RegressionNetParams)54}55func useDogecoin() {56 dogecoin.NewClient(dogecoin.DefaultClientOptions())57 dogecoin.NewTxBuilder(&dogecoin.RegressionNetParams)58}59func useEthereum() {60 client, err := ethclient.Dial("")61 if err != nil {62 return63 }64 gatewayRegistry, err := ethereumbinding.NewGatewayRegistry(common.HexToAddress(""), client)65 if err != nil {66 return67 }68 gateways := make(map[multichain.Asset]*ethereumbinding.MintGatewayLogicV1, 0)69 assetAddrs := make(map[multichain.Address]multichain.Asset, 0)70 sourceChains := []multichain.Chain{71 multichain.Bitcoin,72 }73 for _, chain := range sourceChains {74 gatewayAddr, err := gatewayRegistry.GetGatewayBySymbol(&bind.CallOpts{}, string(chain.NativeAsset()))75 if err != nil {76 return77 }78 gateway, err := ethereumbinding.NewMintGatewayLogicV1(gatewayAddr, client)79 if err != nil {80 return81 }82 gateways[chain.NativeAsset()] = gateway83 addr, err := gateway.Token(&bind.CallOpts{})84 if err != nil {85 return86 }87 assetAddrs[multichain.Address(addr.String())] = chain.NativeAsset()88 }89}90func useFilecoin() {91 filecoin.NewClient(filecoin.DefaultClientOptions())92 filecoin.NewTxBuilder()93}94func useSolana() {95 solana.NewClient(solana.DefaultClientOptions())96}97func useTerra() {98 client := terra.NewClient(terra.DefaultClientOptions())99 terra.NewTxBuilder(terra.DefaultTxBuilderOptions(), client)100}101func useZcash() {102 zcash.NewClient(zcash.DefaultClientOptions())103 zcash.NewTxBuilder(&zcash.RegressionNetParams, 1000000)104}...
Bind
Using AI Code Generation
1import (2func main() {3 r.SetObserved("Y")4 r.SetVar(0, "X1")5 r.SetVar(1, "X2")6 r.Train(7 regression.Data{8 X: []float64{1, 2},9 },10 regression.Data{11 X: []float64{2, 3},12 },13 regression.Data{14 X: []float64{3, 4},15 },16 regression.Data{17 X: []float64{4, 5},18 },19 regression.Data{20 X: []float64{5, 6},21 },22 r.Run()23 fmt.Printf("%+v24}25regression.Data{26 X: []float64{1, 2},27},28regression.Data{29 X: []float64{2, 3},30},31regression.Data{32 X: []float64{3, 4},33},34regression.Data{35 X: []float64{4, 5},36},37regression.Data{38 X: []float64{5, 6},39},
Bind
Using AI Code Generation
1import (2func main() {3 r := new(regression.Regression)4 r.SetObserved("Y")5 r.SetVar(0, "X")6 r.Train(regression.Data{7 {X: []float64{1}, Y: 10},8 {X: []float64{2}, Y: 20},9 {X: []float64{3}, Y: 30},10 {X: []float64{4}, Y: 40},11 {X: []float64{5}, Y: 50},12 {X: []float64{6}, Y: 60},13 })14 r.Run()15 fmt.Printf("Regression Formula: %v16 fmt.Printf("Regression Formula: %v17", r.Coeff(0))18}19import (20func main() {21 r := new(regression.Regression)22 r.SetObserved("Y")23 r.SetVar(0, "X")24 r.Train(regression.Data{25 {X: []float64{1, 1}, Y: 10},26 {X: []float64{2, 2}, Y: 20},27 {X: []float64{3, 3}, Y: 30},28 {X: []float64{4, 4}, Y: 40},29 {X: []float64{5, 5}, Y: 50},30 {X: []float64{6, 6}, Y: 60},31 })32 r.Run()33 fmt.Printf("Regression Formula: %v34 fmt.Printf("Regression Formula: %v35", r.Coeff(0))36 fmt.Printf("Regression Formula: %v37", r.Coeff(1))38}39import (
Bind
Using AI Code Generation
1import (2func main() {3 xs := []float64{1, 2, 3, 4, 5}4 ys := []float64{2, 4, 6, 8, 10}5 reg.SetObserved("Y", ys)6 reg.SetVar(0, "X", xs)7 reg.LinearRegression()8 fmt.Printf("slope: %v9", reg.Coeff(0))10 fmt.Printf("intercept: %v11", reg.Coeff(1))12 r2 := reg.R2()13 fmt.Printf("R^2: %v14 stderr := regression.StdErr(reg)15 fmt.Printf("standard error: %v16 stddev := regression.StdDev(reg)17 fmt.Printf("standard deviation: %v18 ci := regression.ConfidenceInterval(reg, 0.95)19 fmt.Printf("confidence interval: %v20 pi := regression.PredictionInterval(reg, 0.95)21 fmt.Printf("prediction interval: %v22 cov := regression.Covariance(reg)23 fmt.Printf("covariance: %v24 corr := regression.Correlation(reg)25 fmt.Printf("correlation: %v26 rl := regression.Line(reg)27 fmt.Printf("regression line: %v28 rl2 := regression.LineFromX(reg, 1)29 fmt.Printf("regression line at X=1: %v30 rl3 := regression.LineFromY(reg, 2)31 fmt.Printf("
Bind
Using AI Code Generation
1import (2func main() {3 r.Train(regression.DataPoint(65.0, []float64{1, 0, 0}))4 r.Train(regression.DataPoint(72.0, []float64{0, 1, 0}))5 r.Train(regression.DataPoint(69.0, []float64{0, 0, 1}))6 r.Train(regression.DataPoint(68.0, []float64{0, 0, 1}))7 r.Train(regression.DataPoint(70.0, []float64{0, 1, 0}))8 r.Train(regression.DataPoint(75.0, []float64{1, 0, 0}))9 r.Train(regression.DataPoint(80.0, []float64{1, 0, 0}))10 r.Train(regression.DataPoint(85.0, []float64{1, 0, 0}))11 r.Run()12 fmt.Printf("Predicted %v13", r.Predict([]float64{1, 0, 0}))14 fmt.Printf("Predicted %v15", r.Predict([]float64{0, 1, 0}))16 fmt.Printf("Predicted %v17", r.Predict([]float64{0, 0, 1}))18}
Bind
Using AI Code Generation
1import (2func main() {3 r.SetObserved("Y")4 r.SetVar(0, "X")5 r.Train(6 regression.Data{7 X: []float64{1, 2, 3, 4},8 Y: []float64{2, 4, 6, 8},9 },10 r.Train(11 regression.Data{12 X: []float64{2, 3, 4, 5},13 Y: []float64{3, 5, 7, 9},14 },15 r.Run()16 fmt.Printf("%v17 fmt.Printf("R2: %0.2f18 y, err := r.Predict([]float64{6})19 if err != nil {20 log.Fatal(err)21 }22 fmt.Printf("Predicted Y: %0.2f23}
Bind
Using AI Code Generation
1import (2func main() {3 r := new(regression.Regression)4 r.SetObserved("Y")5 r.SetVar(0, "X")6 r.Train(7 regression.Data{8 X: []float64{1, 2, 3, 4, 5, 6, 7, 8, 9},9 Y: []float64{2, 4, 6, 8, 10, 12, 14, 16, 18},10 },11 r.Run()12 fmt.Printf("Regression Formula: %v13 fmt.Printf("Regression Formula: %v14 fmt.Printf("Regression Formula: %v15", r.Equation(10))16 fmt.Printf("Regression Formula: %v17", r.Predict([]float64{10}))18}19import (20func main() {21 r := new(regression.Regression)22 r.SetObserved("Y")23 r.SetVar(0, "X")24 r.Train(25 regression.Data{26 X: []float64{1, 2, 3, 4, 5, 6, 7, 8, 9},27 Y: []float64{2, 4, 6, 8, 10, 12, 14, 16, 18},28 },29 r.Run()30 fmt.Printf("Regression Formula: %v31 fmt.Printf("Regression Formula: %v32 fmt.Printf("Regression Formula: %v33", r.Equation(10))34 fmt.Printf("Regression Formula: %v
Bind
Using AI Code Generation
1import (2func main() {3 x := []float64{1, 2, 3, 4, 5}4 y := []float64{1, 3, 2, 3, 5}5 model = stat.LinearRegression{}6 params = []float64{0, 0}7 fit := stat.Regression{}8 fit.Fit(model, params, x, y, nil)9 fmt.Printf("Intercept: %0.2f10 fmt.Printf("Slope: %0.2f11}
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