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How to use UTest method of stats Package

Best Syzkaller code snippet using stats.UTest

delta.go

Source:delta.go

...34		return -1, convertErr(err)35	}36	return t.P, nil37}38// UTest is a DeltaTest using the Mann-Whitney U test.39func UTest(old, new *Metrics) (pval float64, err error) {40	u, err := stats.MannWhitneyUTest(old.RValues, new.RValues, stats.LocationDiffers)41	if err != nil {42		return -1, convertErr(err)43	}44	return u.P, nil45}46// convertErr converts from the stats package's internal errors47// to errors exported by this package and expected from48// a DeltaTest.49// Using different errors makes it possible for clients to use50// package benchstat without access to the internal stats package,51// and it also gives us a chance to use shorter error messages.52func convertErr(err error) error {53	switch err {54	case stats.ErrZeroVariance:...

pvalue.go

Source:pvalue.go

2// Use of this source code is governed by Apache 2 LICENSE that can be found in the LICENSE file.3package stats4import "golang.org/x/perf/benchstat"5// Mann-Whitney U test.6func UTest(old, new *Sample) (pval float64, err error) {7	// Unfortunately we cannot just invoke MannWhitneyUTest from x/perf/benchstat/internal/stats,8	// so we first wrap the data in Metrics.9	mOld := benchstat.Metrics{10		RValues: old.Xs,11	}12	mNew := benchstat.Metrics{13		RValues: new.Xs,14	}15	return benchstat.UTest(&mOld, &mNew)16}...

UTest

Using AI Code Generation

1import (2func main() {3    s.UTest()4}5import (6func main() {7    s.UTest()8}9import (10func main() {11    s.UTest()12}13import (14func main() {15    s.UTest()16}17import (18func main() {19    s.UTest()20}21import (22func main() {23    s.UTest()24}25import (26func main() {27    s.UTest()28}29import (30func main() {31    s.UTest()32}33import (34func main() {35    s.UTest()36}37import (38func main() {39    s.UTest()40}

UTest

Using AI Code Generation

1import (2type stats struct{}3func (s stats) UTest(x, y []float64) (float64, error) {4	if len(x) != len(y) {5		return 0, fmt.Errorf("x and y have different lengths")6	}7	n := float64(len(x))8	for i := 0; i < len(x); i++ {9	}10	for i := 0; i < len(x); i++ {11		sumSqDiffX += math.Pow(x[i]-diff, 2)12		sumSqDiffY += math.Pow(y[i]-diff, 2)13		sumSqDiffXY += math.Pow(x[i]-y[i], 2)14	}15	sxx := math.Sqrt(sumSqDiffX / n)16	syy := math.Sqrt(sumSqDiffY / n)17	sxy := math.Sqrt(sumSqDiffXY / n)18	if sxx*syy == 0 {19		return 0, fmt.Errorf("one or both of the samples has zero variance")20	}21	return sxy / (sxx * syy), nil22}23func main() {24	s := stats{}25	x := make([]float64, 100)26	y := make([]float64, 100)27	for i := range x {28		x[i] = rand.NormFloat64()29		y[i] = rand.NormFloat64()30	}31	utest, err := s.UTest(x, y)32	if err != nil {33		fmt.Println(err)34	}35	fmt.Println(utest)36}

UTest

Using AI Code Generation

1import (2func main() {3    data := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}4    s := stats.Stats{}5    res := s.UTest(data, 5)6    fmt.Println(res)7}

UTest

Using AI Code Generation

1import (2func main() {3	s1 := []float64{1.2, 2.3, 3.4, 4.5, 5.6}4	s2 := []float64{1.1, 2.2, 3.3, 4.4, 5.5}5	t, _ := stats.UTest(s1, s2)6	fmt.Println(t)7}8func main() {9	s1 := []float64{1.2, 2.3, 3.4, 4.5, 5.6}10	s2 := []float64{1.1, 2.2, 3.3, 4.4, 5.5}11	t, _ := stats.UTest(s1, s2)12	fmt.Println(t)13}

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