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How to use Median method of stats Package

Best Syzkaller code snippet using stats.Median

riak.go

Source:riak.go

...36	NodeGetFsmObjsize100     int64  `json:"node_get_fsm_objsize_100"`37	NodeGetFsmObjsize95      int64  `json:"node_get_fsm_objsize_95"`38	NodeGetFsmObjsize99      int64  `json:"node_get_fsm_objsize_99"`39	NodeGetFsmObjsizeMean    int64  `json:"node_get_fsm_objsize_mean"`40	NodeGetFsmObjsizeMedian  int64  `json:"node_get_fsm_objsize_median"`41	NodeGetFsmSiblings100    int64  `json:"node_get_fsm_siblings_100"`42	NodeGetFsmSiblings95     int64  `json:"node_get_fsm_siblings_95"`43	NodeGetFsmSiblings99     int64  `json:"node_get_fsm_siblings_99"`44	NodeGetFsmSiblingsMean   int64  `json:"node_get_fsm_siblings_mean"`45	NodeGetFsmSiblingsMedian int64  `json:"node_get_fsm_siblings_median"`46	NodeGetFsmTime100        int64  `json:"node_get_fsm_time_100"`47	NodeGetFsmTime95         int64  `json:"node_get_fsm_time_95"`48	NodeGetFsmTime99         int64  `json:"node_get_fsm_time_99"`49	NodeGetFsmTimeMean       int64  `json:"node_get_fsm_time_mean"`50	NodeGetFsmTimeMedian     int64  `json:"node_get_fsm_time_median"`51	NodeGets                 int64  `json:"node_gets"`52	NodeGetsTotal            int64  `json:"node_gets_total"`53	Nodename                 string `json:"nodename"`54	NodePutFsmTime100        int64  `json:"node_put_fsm_time_100"`55	NodePutFsmTime95         int64  `json:"node_put_fsm_time_95"`56	NodePutFsmTime99         int64  `json:"node_put_fsm_time_99"`57	NodePutFsmTimeMean       int64  `json:"node_put_fsm_time_mean"`58	NodePutFsmTimeMedian     int64  `json:"node_put_fsm_time_median"`59	NodePuts                 int64  `json:"node_puts"`60	NodePutsTotal            int64  `json:"node_puts_total"`61	PbcActive                int64  `json:"pbc_active"`62	PbcConnects              int64  `json:"pbc_connects"`63	PbcConnectsTotal         int64  `json:"pbc_connects_total"`64	VnodeGets                int64  `json:"vnode_gets"`65	VnodeGetsTotal           int64  `json:"vnode_gets_total"`66	VnodeIndexReads          int64  `json:"vnode_index_reads"`67	VnodeIndexReadsTotal     int64  `json:"vnode_index_reads_total"`68	VnodeIndexWrites         int64  `json:"vnode_index_writes"`69	VnodeIndexWritesTotal    int64  `json:"vnode_index_writes_total"`70	VnodePuts                int64  `json:"vnode_puts"`71	VnodePutsTotal           int64  `json:"vnode_puts_total"`72}73// A sample configuration to only gather stats from localhost, default port.74const sampleConfig = `75  # Specify a list of one or more riak http servers76  servers = ["http://localhost:8098"]77`78// Returns a sample configuration for the plugin79func (r *Riak) SampleConfig() string {80	return sampleConfig81}82// Returns a description of the plugin83func (r *Riak) Description() string {84	return "Read metrics one or many Riak servers"85}86// Reads stats from all configured servers.87func (r *Riak) Gather(acc telegraf.Accumulator) error {88	// Default to a single server at localhost (default port) if none specified89	if len(r.Servers) == 0 {90		r.Servers = []string{"http://127.0.0.1:8098"}91	}92	// Range over all servers, gathering stats. Returns early in case of any error.93	for _, s := range r.Servers {94		if err := r.gatherServer(s, acc); err != nil {95			return err96		}97	}98	return nil99}100// Gathers stats from a single server, adding them to the accumulator101func (r *Riak) gatherServer(s string, acc telegraf.Accumulator) error {102	// Parse the given URL to extract the server tag103	u, err := url.Parse(s)104	if err != nil {105		return fmt.Errorf("riak unable to parse given server url %s: %s", s, err)106	}107	// Perform the GET request to the riak /stats endpoint108	resp, err := r.client.Get(s + "/stats")109	if err != nil {110		return err111	}112	defer resp.Body.Close()113	// Successful responses will always return status code 200114	if resp.StatusCode != http.StatusOK {115		return fmt.Errorf("riak responded with unexepcted status code %d", resp.StatusCode)116	}117	// Decode the response JSON into a new stats struct118	stats := &riakStats{}119	if err := json.NewDecoder(resp.Body).Decode(stats); err != nil {120		return fmt.Errorf("unable to decode riak response: %s", err)121	}122	// Build a map of tags123	tags := map[string]string{124		"nodename": stats.Nodename,125		"server":   u.Host,126	}127	// Build a map of field values128	fields := map[string]interface{}{129		"cpu_avg1":                     stats.CpuAvg1,130		"cpu_avg15":                    stats.CpuAvg15,131		"cpu_avg5":                     stats.CpuAvg5,132		"memory_code":                  stats.MemoryCode,133		"memory_ets":                   stats.MemoryEts,134		"memory_processes":             stats.MemoryProcesses,135		"memory_system":                stats.MemorySystem,136		"memory_total":                 stats.MemoryTotal,137		"node_get_fsm_objsize_100":     stats.NodeGetFsmObjsize100,138		"node_get_fsm_objsize_95":      stats.NodeGetFsmObjsize95,139		"node_get_fsm_objsize_99":      stats.NodeGetFsmObjsize99,140		"node_get_fsm_objsize_mean":    stats.NodeGetFsmObjsizeMean,141		"node_get_fsm_objsize_median":  stats.NodeGetFsmObjsizeMedian,142		"node_get_fsm_siblings_100":    stats.NodeGetFsmSiblings100,143		"node_get_fsm_siblings_95":     stats.NodeGetFsmSiblings95,144		"node_get_fsm_siblings_99":     stats.NodeGetFsmSiblings99,145		"node_get_fsm_siblings_mean":   stats.NodeGetFsmSiblingsMean,146		"node_get_fsm_siblings_median": stats.NodeGetFsmSiblingsMedian,147		"node_get_fsm_time_100":        stats.NodeGetFsmTime100,148		"node_get_fsm_time_95":         stats.NodeGetFsmTime95,149		"node_get_fsm_time_99":         stats.NodeGetFsmTime99,150		"node_get_fsm_time_mean":       stats.NodeGetFsmTimeMean,151		"node_get_fsm_time_median":     stats.NodeGetFsmTimeMedian,152		"node_gets":                    stats.NodeGets,153		"node_gets_total":              stats.NodeGetsTotal,154		"node_put_fsm_time_100":        stats.NodePutFsmTime100,155		"node_put_fsm_time_95":         stats.NodePutFsmTime95,156		"node_put_fsm_time_99":         stats.NodePutFsmTime99,157		"node_put_fsm_time_mean":       stats.NodePutFsmTimeMean,158		"node_put_fsm_time_median":     stats.NodePutFsmTimeMedian,159		"node_puts":                    stats.NodePuts,160		"node_puts_total":              stats.NodePutsTotal,161		"pbc_active":                   stats.PbcActive,162		"pbc_connects":                 stats.PbcConnects,163		"pbc_connects_total":           stats.PbcConnectsTotal,164		"vnode_gets":                   stats.VnodeGets,165		"vnode_gets_total":             stats.VnodeGetsTotal,166		"vnode_index_reads":            stats.VnodeIndexReads,167		"vnode_index_reads_total":      stats.VnodeIndexReadsTotal,168		"vnode_index_writes":           stats.VnodeIndexWrites,169		"vnode_index_writes_total":     stats.VnodeIndexWritesTotal,170		"vnode_puts":                   stats.VnodePuts,171		"vnode_puts_total":             stats.VnodePutsTotal,172	}...

rank.go

Source:rank.go

...10type RankingCriteria uint11const (12	LowerMeanIsBetter RankingCriteria = iota13	HigherMeanIsBetter14	LowerMedianIsBetter15	HigherMedianIsBetter16	LowerMinIsBetter17	HigherMinIsBetter18	LowerMaxIsBetter19	HigherMaxIsBetter20)21var rcEnumSupport = newEnumSupport(map[uint]string{uint(LowerMeanIsBetter): "Lower Mean is Better", uint(HigherMeanIsBetter): "Higher Mean is Better", uint(LowerMedianIsBetter): "Lower Median is Better", uint(HigherMedianIsBetter): "Higher Median is Better", uint(LowerMinIsBetter): "Lower Mins is Better", uint(HigherMinIsBetter): "Higher Min is Better", uint(LowerMaxIsBetter): "Lower Max is Better", uint(HigherMaxIsBetter): "Higher Max is Better"})22func (s RankingCriteria) String() string { return rcEnumSupport.String(uint(s)) }23func (s *RankingCriteria) UnmarshalJSON(b []byte) error {24	out, err := rcEnumSupport.UnmarshJSON(b)25	*s = RankingCriteria(out)26	return err27}28func (s RankingCriteria) MarshalJSON() ([]byte, error) { return rcEnumSupport.MarshJSON(uint(s)) }29/*30Ranking ranks a set of Stats by a specified RankingCritera.  Use RankStats to create a Ranking.31When using Ginkgo, you can register Rankings as Report Entries via AddReportEntry.  This will emit a formatted table representing the Stats in rank-order when Ginkgo generates the report.32*/33type Ranking struct {34	Criteria RankingCriteria35	Stats    []Stats36}37/*38RankStats creates a new ranking of the passed-in stats according to the passed-in criteria.39*/40func RankStats(criteria RankingCriteria, stats ...Stats) Ranking {41	sort.Slice(stats, func(i int, j int) bool {42		switch criteria {43		case LowerMeanIsBetter:44			return stats[i].FloatFor(StatMean) < stats[j].FloatFor(StatMean)45		case HigherMeanIsBetter:46			return stats[i].FloatFor(StatMean) > stats[j].FloatFor(StatMean)47		case LowerMedianIsBetter:48			return stats[i].FloatFor(StatMedian) < stats[j].FloatFor(StatMedian)49		case HigherMedianIsBetter:50			return stats[i].FloatFor(StatMedian) > stats[j].FloatFor(StatMedian)51		case LowerMinIsBetter:52			return stats[i].FloatFor(StatMin) < stats[j].FloatFor(StatMin)53		case HigherMinIsBetter:54			return stats[i].FloatFor(StatMin) > stats[j].FloatFor(StatMin)55		case LowerMaxIsBetter:56			return stats[i].FloatFor(StatMax) < stats[j].FloatFor(StatMax)57		case HigherMaxIsBetter:58			return stats[i].FloatFor(StatMax) > stats[j].FloatFor(StatMax)59		}60		return false61	})62	out := Ranking{63		Criteria: criteria,64		Stats:    stats,65	}66	return out67}68/*69Winner returns the Stats with the most optimal rank based on the specified ranking criteria.  For example, if the RankingCriteria is LowerMaxIsBetter then the Stats with the lowest value or duration for StatMax will be returned as the "winner"70*/71func (c Ranking) Winner() Stats {72	if len(c.Stats) == 0 {73		return Stats{}74	}75	return c.Stats[0]76}77func (c Ranking) report(enableStyling bool) string {78	if len(c.Stats) == 0 {79		return "Empty Ranking"80	}81	t := table.NewTable()82	t.TableStyle.EnableTextStyling = enableStyling83	t.AppendRow(table.R(84		table.C("Experiment"), table.C("Name"), table.C("N"), table.C("Min"), table.C("Median"), table.C("Mean"), table.C("StdDev"), table.C("Max"),85		table.Divider("="),86		"{{bold}}",87	))88	for idx, stats := range c.Stats {89		name := stats.MeasurementName90		if stats.Units != "" {91			name = name + " [" + stats.Units + "]"92		}93		experimentName := stats.ExperimentName94		style := stats.Style95		if idx == 0 {96			style = "{{bold}}" + style97			name += "\n*Winner*"98			experimentName += "\n*Winner*"...

biostatics.go

Source:biostatics.go

...5  "math"6  "fmt"7)8type TwoTwelw struct {9	Height VarMeanMedian10	Weight VarMeanMedian11}12type VarMeanMedian struct {13	variability float6414	mean float6415	median float6416  q1 float6417  q3 float6418}19/*20func Initer(path string) {21	res := bioreader.Constructor(ReadCsvFile(path))22	from2to12(res)23}24*/25func From2to12(res *bioreader.Table) *TwoTwelw {26  var ms1, ms2 []float6427  for _, val := range res.Height {28    if val != 0.0 {29      ms1 = append(ms1, val)30    }31  }32  mean1, _ := stats.Mean(ms1)33	median1, _ := stats.Median(ms1)34	variance1, _ := stats.VarS(ms1)35	quartiles1, _ := stats.Quartile(ms1)36  for _, val := range res.Weight {37    if val != 0.0 {38      ms2 = append(ms2, val)39    }40  }41  mean2, _ := stats.Mean(ms2)42	median2, _ := stats.Median(ms2)43	variance2, _ := stats.VarS(ms2)44  quartiles2, _ := stats.Quartile(ms2)45  fmt.Println(len(res.Height), len(res.Weight))46  47  return &TwoTwelw{48    Height: VarMeanMedian{49      variability: variance1,50      mean: mean1,51      median: median1,52      q1: quartiles1.Q1,53      q3: quartiles1.Q3,54      },55    Weight: VarMeanMedian{56      variability: variance2,57      mean: mean2,58      median: median2,59      q1: quartiles2.Q1,60      q3: quartiles2.Q3,61    },62  }63}64func From13to18(res *bioreader.Table) {65  var ms1, ms2 []float6466  var ms3, ms4 []float6467  for _, val := range res.Height {68    if val != 0 {69      ms1 = append(ms1, val)70    }71  }72	quartiles1, _ := stats.Quartile(ms1)73  hiqr, _ := stats.InterQuartileRange(ms1)74  lheight25, uheight75 := quartiles1.Q1 - hiqr, quartiles1.Q3 + hiqr75  fmt.Println(lheight25, uheight75)76  for _, val := range res.Height {77    if val > uheight75 {78      ms3 = append(ms3, 0.0)79    } else if val < lheight25 {80      ms3 = append(ms3, 0.0)81    } else {82      ms3 = append(ms3, val)83    }84  }85  for _, val := range res.Weight {86    if val != 0 {87      ms2 = append(ms2, val)88    }89  }90  quartiles2, _ := stats.Quartile(ms2)91  wiqr, _ := stats.InterQuartileRange(ms2)92  lweight25, uweight75 := quartiles2.Q1 - wiqr, quartiles2.Q3 + wiqr93  fmt.Println(lweight25, uweight75)94    for _, val := range res.Weight {95    if val > uweight75 {96      ms4 = append(ms4, 0.0)97    } else if val < lweight25 {98      ms4 = append(ms4, 0.0)99    } else {100      ms4 = append(ms4, val)101    }102  }103  var bm1 []float64104  bmi := BMI(ms3, ms4)105  for _, val := range bmi {106    if val != 0 {107      bm1 = append(bm1, val)108    }109  }110  mean, median, variance := bmistat(bm1)111  fmt.Println(mean, median, variance)112}113func BMI(height, weight []float64) []float64 {114  var res []float64115  for i := 0; i < len(height); i ++ {116    if height[i] != 0 {117      res = append(res, weight[i]/math.Pow(height[i] * 0.01, 2))118    } else {119      res = append(res, 0.0)120    }121  }122  return res123}124func bmistat(mass []float64) (float64, float64, float64) {125  mean, _ := stats.Mean(mass)126	median, _ := stats.Median(mass)127	variance, _ := stats.VarS(mass)128  return mean, median, variance129}...

Median

Using AI Code Generation

1import (2func main() {3    fmt.Println(stringutil.Reverse("!oG ,olleH"))4    fmt.Println(stringutil.MyName)5    fmt.Println(icomefromalaska.BearName)6    fmt.Println(icomefromindia.Hello())7    vis.Visit()8}9import (10func main() {11    fmt.Println(stringutil.Reverse("!oG ,olleH"))12    fmt.Println(stringutil.MyName)13    fmt.Println(icomefromalaska.BearName)14    fmt.Println(icomefromindia.Hello())15    vis.Visit()16}17import (18func main() {19    fmt.Println(stringutil.Reverse("!oG ,olleH"))20    fmt.Println(stringutil.MyName)21    fmt.Println(icomefromalaska.BearName)22    fmt.Println(icomefromindia.Hello())23    vis.Visit()24}25import (

Median

Using AI Code Generation

1import (2func main() {3    for i := 0; i < 100; i++ {4        a[i] = rand.Float64() * 1005    }6    fmt.Println("Median of a is ", stats.Median(a[:]))7}8import (9func Median(data []float64) float64 {10    sort.Float64s(data)11    n := len(data)12    if n%2 == 0 {13        return (data[n/2] + data[n/2-1]) / 214    }15}

Median

Using AI Code Generation

1import (2func main() {3	s := stats.Stats{1,2,3,4,5}4	fmt.Println(s.Median())5}6import (7func main() {8	s := stats.Stats{1,2,3,4,5}9	fmt.Println(s.Median())10}11func (s Stats) Median() float64 {12}13import (14func main() {15	s := stats.Stats{1,2,3,4,5}16	fmt.Println(s.Median())17}18import (19func main() {20	s := stats.Stats{1,2,3,4,5}21	fmt.Println(s.Median())22}23func (s Stats) Median() float64 {24}25import (26func main() {27	s := stats.Stats{1,2,3,4,5}28	fmt.Println(s.Median())29}30import (31func main() {32	s := stats.Stats{1,2,3,4,5}33	fmt.Println(s.Median())34}

Median

Using AI Code Generation

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

Median

Using AI Code Generation

1import (2func main() {3    s := stats.Stats{1, 2, 3, 4, 5}4    m := s.Median()5    fmt.Println(m)6}7import (8func main() {9    s := stats.Stats{1, 2, 3, 4, 5}10    m := s.Mode()11    fmt.Println(m)12}13import (14func main() {15    s := stats.Stats{1, 2, 3, 4, 5}16    m := s.Mean()17    fmt.Println(m)18}19import (20func main() {21    s := stats.Stats{1, 2, 3, 4, 5}22    m := s.Sum()23    fmt.Println(m)24}25import (26func main() {27    s := stats.Stats{1, 2, 3, 4, 5}28    m := s.Min()29    fmt.Println(m)30}31import (32func main() {33    s := stats.Stats{1, 2, 3, 4, 5}34    m := s.Max()35    fmt.Println(m)36}37import (38func main() {39    s := stats.Stats{

Median

Using AI Code Generation

1import (2func main() {3	data := []float64{3, 4, 5, 6, 7, 8, 9, 10}4	median := stats.Median(data)5	fmt.Printf("The median of the data is %0.2f6}7func Median(data []float64) float64 {8	sort.Float64s(data)9	middle := len(data) / 210	if len(data)%2 == 0 {11		return (data[middle-1] + data[middle]) / 212	}13}

Median

Using AI Code Generation

1import "fmt"2import "stats"3func main() {4 a := []float64{1,2,3,4,5}5 fmt.Println(stats.Median(a))6}

Median

Using AI Code Generation

1import (2func main() {3    s := stats.Stats{10, 20, 30, 40, 50}4    m := s.Median()5    fmt.Println(m)6}7    func Median(s []float64) float648    func Mean(s []float64) float649    func Mode(s []float64) float6410    func Range(s []float64) float6411    func Variance(s []float64) float6412        func New(data []float64) *Stats13        func (s Stats) Median() float6414        func (s Stats) Mean() float6415        func (s Stats) Mode() float6416        func (s Stats) Range() float6417        func (s Stats) Variance() float6418func Median(s []float64) float6419func Mean(s []float64) float6420func Mode(s []float64) float6421func Range(s []float64) float6422func Variance(s []float64) float6423type Stats struct {24}25func New(data []float64) *Stats26func (s Stats) Median27func (s Stats) Median() float6428func (s Stats) Mean29func (s Stats) Mean() float6430func (s Stats) Mode

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