feat: change statistics render of metric plot to min/max/median

- #263
This commit is contained in:
Christoph Kluge
2024-05-08 16:17:42 +02:00
parent 597bccc080
commit 684cb5a376
9 changed files with 163 additions and 31 deletions

View File

@@ -10,6 +10,8 @@ import (
"math"
"sort"
"unsafe"
"github.com/ClusterCockpit/cc-backend/internal/util"
)
type JobData map[string]map[MetricScope]*JobMetric
@@ -36,6 +38,7 @@ type MetricStatistics struct {
type StatsSeries struct {
Mean []Float `json:"mean"`
Median []Float `json:"median"`
Min []Float `json:"min"`
Max []Float `json:"max"`
Percentiles map[int][]Float `json:"percentiles,omitempty"`
@@ -120,7 +123,7 @@ func (jd *JobData) Size() int {
for _, metric := range scopes {
if metric.StatisticsSeries != nil {
n += len(metric.StatisticsSeries.Max)
n += len(metric.StatisticsSeries.Mean)
n += len(metric.StatisticsSeries.Median)
n += len(metric.StatisticsSeries.Min)
}
@@ -149,53 +152,74 @@ func (jm *JobMetric) AddStatisticsSeries() {
}
}
min, mean, max := make([]Float, n), make([]Float, n), make([]Float, n)
// mean := make([]Float, n)
min, median, max := make([]Float, n), make([]Float, n), make([]Float, n)
i := 0
for ; i < m; i++ {
smin, ssum, smax := math.MaxFloat32, 0.0, -math.MaxFloat32
seriesCount := len(jm.Series)
// ssum := 0.0
smin, smed, smax := math.MaxFloat32, make([]float64, seriesCount), -math.MaxFloat32
notnan := 0
for j := 0; j < len(jm.Series); j++ {
for j := 0; j < seriesCount; j++ {
x := float64(jm.Series[j].Data[i])
if math.IsNaN(x) {
continue
}
notnan += 1
ssum += x
// ssum += x
smed[j] = x
smin = math.Min(smin, x)
smax = math.Max(smax, x)
}
if notnan < 3 {
min[i] = NaN
mean[i] = NaN
// mean[i] = NaN
median[i] = NaN
max[i] = NaN
} else {
min[i] = Float(smin)
mean[i] = Float(ssum / float64(notnan))
// mean[i] = Float(ssum / float64(notnan))
max[i] = Float(smax)
medianRaw, err := util.Median(smed)
if err != nil {
median[i] = NaN
} else {
median[i] = Float(medianRaw)
}
}
}
for ; i < n; i++ {
min[i] = NaN
mean[i] = NaN
// mean[i] = NaN
median[i] = NaN
max[i] = NaN
}
if smooth {
for i := 2; i < len(mean)-2; i++ {
for i := 2; i < len(median)-2; i++ {
if min[i].IsNaN() {
continue
}
min[i] = (min[i-2] + min[i-1] + min[i] + min[i+1] + min[i+2]) / 5
max[i] = (max[i-2] + max[i-1] + max[i] + max[i+1] + max[i+2]) / 5
mean[i] = (mean[i-2] + mean[i-1] + mean[i] + mean[i+1] + mean[i+2]) / 5
// mean[i] = (mean[i-2] + mean[i-1] + mean[i] + mean[i+1] + mean[i+2]) / 5
// Reduce Median further
smoothRaw := []float64{float64(median[i-2]), float64(median[i-1]), float64(median[i]), float64(median[i+1]), float64(median[i+2])}
smoothMedian, err := util.Median(smoothRaw)
if err != nil {
median[i] = NaN
} else {
median[i] = Float(smoothMedian)
}
}
}
jm.StatisticsSeries = &StatsSeries{Mean: mean, Min: min, Max: max}
jm.StatisticsSeries = &StatsSeries{Median: median, Min: min, Max: max} // Mean: mean
}
func (jd *JobData) AddNodeScope(metric string) bool {