How to use putTC method of regression Package

Best Keploy code snippet using regression.putTC

regression.go

Source:regression.go Github

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...129 }130 r.tele.EditTc(r.client, ctx)131 return nil132}133func (r *Regression) putTC(ctx context.Context, cid string, t models.TestCase) (string, error) {134 t.CID = cid135 var err error136 if r.EnableDeDup {137 // check if already exists138 dup, err := r.isDup(ctx, &t)139 if err != nil {140 r.log.Error("failed to run deduplication on the testcase", zap.String("cid", cid), zap.String("appID", t.AppID), zap.Error(err))141 return "", errors.New("internal failure")142 }143 if dup {144 r.log.Info("found duplicate testcase", zap.String("cid", cid), zap.String("appID", t.AppID), zap.String("uri", t.URI))145 return "", nil146 }147 }148 err = r.tdb.Upsert(ctx, t)149 if err != nil {150 r.log.Error("failed to insert testcase into DB", zap.String("cid", cid), zap.String("appID", t.AppID), zap.Error(err))151 return "", errors.New("internal failure")152 }153 return t.ID, nil154}155func (r *Regression) Put(ctx context.Context, cid string, tcs []models.TestCase) ([]string, error) {156 var ids []string157 if len(tcs) == 0 {158 return ids, errors.New("no testcase to update")159 }160 for _, t := range tcs {161 id, err := r.putTC(ctx, cid, t)162 if err != nil {163 msg := "failed saving testcase"164 r.log.Error(msg, zap.Error(err), zap.String("cid", cid), zap.String("id", t.ID), zap.String("app", t.AppID))165 return ids, errors.New(msg)166 }167 ids = append(ids, id)168 }169 return ids, nil170}171func (r *Regression) test(ctx context.Context, cid, id, app string, resp models.HttpResp) (bool, *run.Result, *models.TestCase, error) {172 tc, err := r.tdb.Get(ctx, cid, id)173 if err != nil {174 r.log.Error("failed to get testcase from DB", zap.String("id", id), zap.String("cid", cid), zap.String("appID", app), zap.Error(err))175 return false, nil, nil, err...

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putTC

Using AI Code Generation

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1import (2func main() {3 r.SetObserved("Y")4 r.SetVar(0, "X")5 r.Train(regression.Data{6 X: []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},7 Y: []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},8 })9 r.Run()10 fmt.Printf("Regression Formula: %v11 fmt.Printf("Regression Formula: %v12 fmt.Printf("R2: %0.2f13 fmt.Printf("StdErr: %0.2f14}

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putTC

Using AI Code Generation

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1import (2func main() {3 r := regression.NewRegression()4 r.PutTC(1, 1)5 fmt.Println(r.GetTC(1))6 r.PutTC(2, 2)7 fmt.Println(r.GetTC(2))8 r.PutTC(3, 3)9 fmt.Println(r.GetTC(3))10}11import (12func main() {13 r := regression.NewRegression()14 r.PutTC(1, 1)15 fmt.Println(r.GetTC(1))16 r.PutTC(2, 2)17 fmt.Println(r.GetTC(2))18 r.PutTC(3, 3)19 fmt.Println(r.GetTC(3))20}21import (22func main() {23 r := regression.NewRegression()24 r.PutTC(1, 1)25 fmt.Println(r.GetTC(1))26 r.PutTC(2, 2)27 fmt.Println(r.GetTC(2))28 r.PutTC(3, 3)

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putTC

Using AI Code Generation

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1import "fmt"2func main() {3 var x = make([]float64, 3)4 var y = make([]float64, 3)5 var reg = make([]Regression, 1)6 reg[0] = NewRegression(x, y)7 var x1 = make([]float64, 3)8 var y1 = make([]float64, 3)9 reg[0].PutTC(x1, y1)10 fmt.Println(reg[0].Predict(4.0))11 fmt.Println(reg[0].Predict(5.0))12 fmt.Println(reg[0].Predict(6.0))13 fmt.Println(reg[0].Predict(7.0))14 fmt.Println(reg[0].Predict(8.0))15 fmt.Println(reg[0].Predict(9.0))16 fmt.Println(reg[0].Predict(10.0))17}18import "fmt"19func main() {20 var x = make([]float64, 3)21 var y = make([]float64, 3)22 var reg = make([]Regression, 1)23 reg[0] = NewRegression(x,

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putTC

Using AI Code Generation

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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, 2, 3, 4, 5},8 Y: []float64{5, 4, 3, 2, 1},9 })10 r.Train(regression.Data{11 X: []float64{1, 2, 3, 4, 5},12 Y: []float64{5, 4, 3, 2, 1},13 })14 r.Train(regression.Data{15 X: []float64{1, 2, 3, 4, 5},16 Y: []float64{5, 4, 3, 2, 1},17 })18 r.Train(regression.Data{19 X: []float64{1, 2, 3, 4, 5},20 Y: []float64{5, 4, 3, 2, 1},21 })22 r.Train(regression.Data{23 X: []float64{1, 2, 3, 4, 5},24 Y: []float64{5, 4, 3, 2, 1},25 })26 r.Train(regression.Data{27 X: []float64{1, 2, 3, 4, 5},28 Y: []float64{5, 4, 3, 2, 1},29 })30 r.Train(regression.Data{31 X: []float64{1, 2, 3, 4, 5},32 Y: []float64{5, 4, 3, 2, 1},33 })34 r.Train(regression.Data{35 X: []float64{1, 2, 3, 4, 5},36 Y: []float64{5, 4, 3, 2, 1},37 })38 r.Train(regression.Data{39 X: []float64{1, 2, 3, 4

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putTC

Using AI Code Generation

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1import (2func main() {3 r.Train(regression.DataPoint(2.5, 2.4))4 r.Train(regression.DataPoint(0.5, 0.7))5 r.Train(regression.DataPoint(2.2, 2.1))6 r.Train(regression.DataPoint(8.5, 7.5))7 r.Train(regression.DataPoint(3.5, 1.9))8 r.Train(regression.DataPoint(1.5, 0.6))9 r.Run()10 fmt.Printf("\nRegression formula:\n%v11 fmt.Printf("\nR2: %v12}

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putTC

Using AI Code Generation

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1import (2func main() {3 fmt.Println("Enter number of data points")4 fmt.Scanln(&num)5 fmt.Println("Enter the data points in format x1 y1 x2 y2 ...")6 reader := bufio.NewReader(os.Stdin)7 input, _ := reader.ReadString('8 input = strings.TrimSpace(input)9 data := strings.Split(input, " ")10 for i := 0; i < num*2; i += 2 {11 x1, _ := strconv.ParseFloat(data[i], 64)12 y1, _ := strconv.ParseFloat(data[i+1], 64)13 x = append(x, x1)14 y = append(y, y1)15 }16 reg.putTC(x, y)17 fmt.Println(reg)18}19import (20func main() {21 fmt.Println("Enter number of data points")22 fmt.Scanln(&num)23 fmt.Println("Enter the data points in format x1 y1 x2 y2 ...")24 reader := bufio.NewReader(os.Stdin)25 input, _ := reader.ReadString('26 input = strings.TrimSpace(input)27 data := strings.Split(input, " ")28 for i := 0; i < num*2; i += 2 {29 x1, _ := strconv.ParseFloat(data[i], 64)30 y1, _ := strconv.ParseFloat(data[i+1], 64)31 x = append(x, x1)32 y = append(y, y1)33 }34 reg.putTC(x, y)35 fmt.Println(reg)36}37import (38func main() {39 fmt.Println("Enter number of data points")40 fmt.Scanln(&num)41 fmt.Println("Enter the data points in format x1 y1 x2 y2 ...")42 reader := bufio.NewReader(os.Stdin)

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