Add confidence metric to csv and json (#115)

Adding the confidence metric to the csv and json output.

closes #108

Signed-off-by: Joe Talerico <rook@redhat.com>
Co-authored-by: Joe Talerico <rook@redhat.com>

README.md

@@ -225,12 +225,11 @@ k8s-netperf will report TCP Retransmissions and UDP Loss for both workload drive
 
 Example output
 ```csv
-Profile,Same node,Host Network,Service,Duration,Parallelism,# of Samples,Message Size,Avg Throughput,Throughput Metric,99%tile Observed Latency,Latency Metric
-TCP_STREAM,false,false,false,10,1,3,1024,1131.150000,Mb/s,23,usec
-TCP_STREAM,false,false,false,10,2,3,1024,1710.150000,Mb/s,34,usec
-TCP_STREAM,false,false,false,10,1,3,8192,4437.520000,Mb/s,30,usec
-UDP_STREAM,false,false,false,10,1,3,1024,1159.790000,Mb/s,14,usec
-TCP_CRR,false,false,false,10,1,3,1024,5954.940000,OP/s,456,usec
-TCP_CRR,false,false,true,10,1,3,1024,1455.470000,OP/s,248,usec
-TCP_RR,false,false,false,10,1,3,1024,41330.000000,OP/s,85,usec
+Driver,Profile,Same node,Host Network,Service,Duration,Parallelism,# of Samples,Message Size,Confidence metric - low,Confidence metric - high,Avg Throughput,Throughput Metric,99%tile Observed Latency,Latency Metric
+netperf,TCP_STREAM,false,false,false,10,1,3,1024,861.9391413991156,885.2741919342178,873.606667,Mb/s,3.3333333333333335,usec
+netperf,TCP_STREAM,false,false,false,10,1,3,8192,178.12442996547009,1310.3422367011967,744.233333,Mb/s,2394.6666666666665,usec
+netperf,UDP_STREAM,false,false,false,10,1,3,1024,584.3478157889886,993.4588508776783,788.903333,Mb/s,23,usec
+netperf,TCP_CRR,false,false,false,10,1,3,1024,1889.3183973002176,2558.074936033115,2223.696667,OP/s,4682.666666666667,usec
+netperf,TCP_CRR,false,false,true,10,1,3,1024,1169.206855676418,2954.3464776569153,2061.776667,OP/s,4679.333333333333,usec
+netperf,TCP_RR,false,false,false,10,1,3,1024,6582.5359452538705,12085.437388079461,9333.986667,OP/s,451.3333333333333,usec
 ```

pkg/archive/archive.go

@@ -44,6 +44,7 @@ type Doc struct {
 	ClientPodCPU     []metrics.PodCPU  `json:"clientPods"`
 	ClientNodeLabels map[string]string `json:"clientNodeLabels"`
 	ServerNodeLabels map[string]string `json:"serverNodeLabels"`
+	Confidence       []float64         `json:"confidence"`
 }
 
 // Connect returns a client connected to the desired cluster.
@@ -80,6 +81,11 @@ func BuildDocs(sr result.ScenarioResults, uuid string) ([]interface{}, error) {
 		if len(r.Driver) < 1 {
 			continue
 		}
+		var lo, hi float64
+		if r.Samples > 1 {
+			_, lo, hi = result.ConfidenceInterval(r.ThroughputSummary, 0.95)
+		}
+		c := []float64{lo, hi}
 		d := Doc{
 			UUID:             uuid,
 			Timestamp:        time,
@@ -101,6 +107,7 @@ func BuildDocs(sr result.ScenarioResults, uuid string) ([]interface{}, error) {
 			ServerNodeLabels: r.ServerNodeLabels,
 			ClientNodeLabels: r.ClientNodeLabels,
 			AcrossAZ:         r.AcrossAZ,
+			Confidence:       c,
 		}
 		UDPLossPercent, e := result.Average(r.LossSummary)
 		if e != nil {
@@ -147,11 +154,17 @@ func commonCsvHeaderFields() []string {
 		"Parallelism",
 		"# of Samples",
 		"Message Size",
+		"Confidence metric - low",
+		"Confidence metric - high",
 	}
 }
 
 // Common csv data fields.
-func commonCsvDataFeilds(row result.Data) []string {
+func commonCsvDataFields(row result.Data) []string {
+	var lo, hi float64
+	if row.Samples > 1 {
+		_, lo, hi = result.ConfidenceInterval(row.ThroughputSummary, 0.95)
+	}
 	return []string{
 		fmt.Sprint(row.Driver),
 		fmt.Sprint(row.Profile),
@@ -162,15 +175,17 @@ func commonCsvDataFeilds(row result.Data) []string {
 		strconv.Itoa(row.Parallelism),
 		strconv.Itoa(row.Samples),
 		strconv.Itoa(row.MessageSize),
+		strconv.FormatFloat(lo, 'f', -1, 64),
+		strconv.FormatFloat(hi, 'f', -1, 64),
 	}
 }
 
-// Writes all the mertic feilds to the archive.
+// Writes all the mertics to the archive.
 func writeArchive(cpuarchive, podarchive *csv.Writer, role string, row result.Data, podResults []metrics.PodCPU) error {
 	roleFieldData := []string{role}
 	for _, pod := range podResults {
 		if err := podarchive.Write(append(append(roleFieldData,
-			commonCsvDataFeilds(row)...),
+			commonCsvDataFields(row)...),
 			pod.Name,
 			fmt.Sprintf("%f", pod.Value),
 		)); err != nil {
@@ -183,7 +198,7 @@ func writeArchive(cpuarchive, podarchive *csv.Writer, role string, row result.Da
 		cpu = row.ServerMetrics
 	}
 	if err := cpuarchive.Write(append(append(roleFieldData,
-		commonCsvDataFeilds(row)...),
+		commonCsvDataFields(row)...),
 		fmt.Sprintf("%f", cpu.Idle),
 		fmt.Sprintf("%f", cpu.User),
 		fmt.Sprintf("%f", cpu.System),
@@ -265,7 +280,7 @@ func WriteSpecificCSV(r result.ScenarioResults) error {
 		if strings.Contains(row.Profile, "UDP_STREAM") {
 			loss, _ := result.Average(row.LossSummary)
 			header := []string{"UDP Percent Loss"}
-			data := append(header, commonCsvDataFeilds(row)...)
+			data := append(header, commonCsvDataFields(row)...)
 			iperfdata = append(data, fmt.Sprintf("%f", loss))
 			if err := archive.Write(iperfdata); err != nil {
 				return fmt.Errorf("failed to write result archive to file")
@@ -274,7 +289,7 @@ func WriteSpecificCSV(r result.ScenarioResults) error {
 		if strings.Contains(row.Profile, "TCP_STREAM") {
 			rt, _ := result.Average(row.RetransmitSummary)
 			header := []string{"TCP Retransmissions"}
-			data := append(header, commonCsvDataFeilds(row)...)
+			data := append(header, commonCsvDataFields(row)...)
 			iperfdata = append(data, fmt.Sprintf("%f", rt))
 			if err := archive.Write(iperfdata); err != nil {
 				return fmt.Errorf("failed to write result archive to file")
@@ -322,7 +337,7 @@ func WriteCSVResult(r result.ScenarioResults) error {
 	for _, row := range r.Results {
 		avg, _ := result.Average(row.ThroughputSummary)
 		lavg, _ := result.Average(row.LatencySummary)
-		data := append(commonCsvDataFeilds(row),
+		data := append(commonCsvDataFields(row),
 			fmt.Sprintf("%f", avg),
 			row.Metric,
 			fmt.Sprint(lavg),

pkg/results/result.go

@@ -74,7 +74,7 @@ func Percentile(vals []float64, ptile float64) (float64, error) {
 }
 
 // Confidence accepts array of floats to calculate average
-func confidenceInterval(vals []float64, ci float64) (float64, float64, float64) {
+func ConfidenceInterval(vals []float64, ci float64) (float64, float64, float64) {
 	return math.MeanCI(vals, ci)
 }
 
@@ -250,7 +250,7 @@ func renderResults(s ScenarioResults, testType string) {
 				avg, _ := Average(r.ThroughputSummary)
 				var lo, hi float64
 				if r.Samples > 1 {
-					_, lo, hi = confidenceInterval(r.ThroughputSummary, 0.95)
+					_, lo, hi = ConfidenceInterval(r.ThroughputSummary, 0.95)
 				}
 				table.Append([]string{fmt.Sprintf("📊 %s Results", caser.String(strings.ToLower(testType))), r.Driver, r.Profile, strconv.Itoa(r.Parallelism), strconv.FormatBool(r.HostNetwork), strconv.FormatBool(r.Service), strconv.Itoa(r.MessageSize), strconv.FormatBool(r.SameNode), strconv.Itoa(r.Duration), strconv.Itoa(r.Samples), fmt.Sprintf("%f (%s)", avg, r.Metric), fmt.Sprintf("%f-%f (%s)", lo, hi, r.Metric)})
 			}