How to use Bind method of regression Package

...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...

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}...

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},

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 (

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("

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}

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}

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

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}