func bench(requests, concurrency int, images []string, args []string) {
start := time.Now()
timings := make([]float64, requests)
// Create a buffered channel so our display goroutine can't slow down the workers.
completeCh := make(chan time.Duration, requests)
doneCh := make(chan struct{})
current := 0
go func() {
for timing := range completeCh {
timings = append(timings, timing.Seconds())
current++
percent := float64(current) / float64(requests) * 100
fmt.Printf("[%3.f%%] %d/%d containers started\n", percent, current, requests)
}
doneCh <- struct{}{}
}()
session(requests, concurrency, images, args, completeCh)
close(completeCh)
<-doneCh
total := time.Since(start)
mean, _ := stats.Mean(timings)
p90th, _ := stats.Percentile(timings, 90)
p99th, _ := stats.Percentile(timings, 99)
meanMillis := mean * MILLIS_IN_SECOND
p90thMillis := p90th * MILLIS_IN_SECOND
p99thMillis := p99th * MILLIS_IN_SECOND
fmt.Printf("\n")
fmt.Printf("Time taken for tests: %.3fs\n", total.Seconds())
fmt.Printf("Time per container: %.3fms [mean] | %.3fms [90th] | %.3fms [99th]\n", meanMillis, p90thMillis, p99thMillis)
}
func bench(requests, concurrency int, image string) {
start := time.Now()
timings := make([]float64, requests)
completeCh := make(chan time.Duration)
current := 0
go func() {
for timing := range completeCh {
timings = append(timings, timing.Seconds())
current++
percent := float64(current) / float64(requests) * 100
fmt.Printf("[%3.f%%] %d/%d containers started\n", percent, current, requests)
}
}()
session(requests, concurrency, image, completeCh)
close(completeCh)
total := time.Since(start)
p50th, _ := stats.Median(timings)
p90th, _ := stats.Percentile(timings, 90)
p99th, _ := stats.Percentile(timings, 99)
fmt.Println("")
fmt.Printf("Time taken for tests: %s\n", total.String())
fmt.Printf("Time per container: %vms [50th] | %vms [90th] | %vms [99th]\n", int(p50th*1000), int(p90th*1000), int(p99th*1000))
}
func statString(data []float64) (string, error) {
strs := make([]string, 3)
for i, pct := range []float64{50, 90, 99} {
stat, err := stats.Percentile(data, pct)
if err != nil {
return "", err
}
strs[i] = strconv.FormatFloat(stat, 'f', 2, 64)
}
return strings.Join(strs, "/"), nil
}
func (hist *History) PrintSummary() {
nanos := []float64{}
for _, duration := range hist.values {
nanos = append(nanos, float64(duration))
}
fmt.Printf("%10s", hist.name)
fmt.Printf(" %10s", time.Duration(stats.Min(nanos)))
for _, p := range percentiles {
nano := time.Duration(stats.Percentile(nanos, p))
fmt.Printf(" %10s", nano)
}
fmt.Printf(" %10s", time.Duration(stats.Max(nanos)))
fmt.Println()
}
func FprintSummary(out io.Writer, hists ...*History) {
fmt.Fprintf(out, "%10s", "")
fmt.Fprintf(out, " %10s", "MIN")
for _, p := range percentiles {
fmt.Fprintf(out, " %9d%%", int(p))
}
fmt.Fprintf(out, " %10s", "MAX")
fmt.Fprintln(out)
for _, hist := range hists {
nanos := []float64{}
for _, duration := range hist.values {
nanos = append(nanos, float64(duration))
}
fmt.Fprintf(out, "%10s", hist.name)
fmt.Fprintf(out, " %10s", time.Duration(stats.Min(nanos)))
for _, p := range percentiles {
fmt.Fprintf(out, " %10s", time.Duration(stats.Percentile(nanos, p)))
}
fmt.Fprintf(out, " %10s", time.Duration(stats.Max(nanos)))
fmt.Fprintln(out)
}
}
func main() {
d := stats.LoadRawData([]interface{}{1.1, "2", 3.0, 4, "5"})
a, _ := stats.Min(d)
fmt.Println(a) // 1.1
a, _ = stats.Max(d)
fmt.Println(a) // 5
a, _ = stats.Sum([]float64{1.1, 2.2, 3.3})
fmt.Println(a) // 6.6
a, _ = stats.Mean([]float64{1, 2, 3, 4, 5})
fmt.Println(a) // 3
a, _ = stats.Median([]float64{1, 2, 3, 4, 5, 6, 7})
fmt.Println(a) // 4
m, _ := stats.Mode([]float64{5, 5, 3, 3, 4, 2, 1})
fmt.Println(m) // [5 3]
a, _ = stats.PopulationVariance([]float64{1, 2, 3, 4, 5})
fmt.Println(a) // 2
a, _ = stats.SampleVariance([]float64{1, 2, 3, 4, 5})
fmt.Println(a) // 2.5
a, _ = stats.MedianAbsoluteDeviationPopulation([]float64{1, 2, 3})
fmt.Println(a) // 1
a, _ = stats.StandardDeviationPopulation([]float64{1, 2, 3})
fmt.Println(a) // 0.816496580927726
a, _ = stats.StandardDeviationSample([]float64{1, 2, 3})
fmt.Println(a) // 1
a, _ = stats.Percentile([]float64{1, 2, 3, 4, 5}, 75)
fmt.Println(a) // 4
a, _ = stats.PercentileNearestRank([]float64{35, 20, 15, 40, 50}, 75)
fmt.Println(a) // 40
c := []stats.Coordinate{
{1, 2.3},
{2, 3.3},
{3, 3.7},
{4, 4.3},
{5, 5.3},
}
r, _ := stats.LinearRegression(c)
fmt.Println(r) // [{1 2.3800000000000026} {2 3.0800000000000014} {3 3.7800000000000002} {4 4.479999999999999} {5 5.179999999999998}]
r, _ = stats.ExponentialRegression(c)
fmt.Println(r) // [{1 2.5150181024736638} {2 3.032084111136781} {3 3.6554544271334493} {4 4.406984298281804} {5 5.313022222665875}]
r, _ = stats.LogarithmicRegression(c)
fmt.Println(r) // [{1 2.1520822363811702} {2 3.3305559222492214} {3 4.019918836568674} {4 4.509029608117273} {5 4.888413396683663}]
s, _ := stats.Sample([]float64{0.1, 0.2, 0.3, 0.4}, 3, false)
fmt.Println(s) // [0.2,0.4,0.3]
s, _ = stats.Sample([]float64{0.1, 0.2, 0.3, 0.4}, 10, true)
fmt.Println(s) // [0.2,0.2,0.4,0.1,0.2,0.4,0.3,0.2,0.2,0.1]
q, _ := stats.Quartile([]float64{7, 15, 36, 39, 40, 41})
fmt.Println(q) // {15 37.5 40}
iqr, _ := stats.InterQuartileRange([]float64{102, 104, 105, 107, 108, 109, 110, 112, 115, 116, 118})
fmt.Println(iqr) // 10
mh, _ := stats.Midhinge([]float64{1, 3, 4, 4, 6, 6, 6, 6, 7, 7, 7, 8, 8, 9, 9, 10, 11, 12, 13})
fmt.Println(mh) // 7.5
tr, _ := stats.Trimean([]float64{1, 3, 4, 4, 6, 6, 6, 6, 7, 7, 7, 8, 8, 9, 9, 10, 11, 12, 13})
fmt.Println(tr) // 7.25
o, _ := stats.QuartileOutliers([]float64{-1000, 1, 3, 4, 4, 6, 6, 6, 6, 7, 8, 15, 18, 100})
fmt.Printf("%+v\n", o) // {Mild:[15 18] Extreme:[-1000 100]}
gm, _ := stats.GeometricMean([]float64{10, 51.2, 8})
fmt.Println(gm) // 15.999999999999991
hm, _ := stats.HarmonicMean([]float64{1, 2, 3, 4, 5})
fmt.Println(hm) // 2.18978102189781
a, _ = stats.Round(2.18978102189781, 3)
fmt.Println(a) // 2.189
}
func main() {
verbose := flag.Bool("v", false, "verbose output")
flag.Parse()
file, err := os.Open("delta_data.bin")
check(err)
defer file.Close()
buffer := bufio.NewReader(file)
sizes := make([]float64, 0)
speeds := make([]float64, 0)
encode := qpc.NewHistory("encode")
decode := qpc.NewHistory("decode")
server := physics.NewState(901)
client := physics.NewState(901)
// initialize the base state
for i := 0; i < 6; i += 1 {
server.ReadNext(buffer)
client.IncFrame()
client.Current().Assign(server.Current())
}
frame := 6
for {
err = server.ReadNext(buffer)
if err == io.EOF {
break
}
check(err)
frame += 1
runtime.GC()
// Server side
encode.Start()
snapshot := server.Encode()
encode.Stop()
// ===
runtime.GC()
// Client side
decode.Start()
client.IncFrame()
client.Decode(snapshot)
decode.Stop()
// ===
size := float64(len(snapshot)*8) / 1000.0
sizes = append(sizes, size)
speed := size * 60.0
speeds = append(speeds, speed)
equal := server.Current().Equals(client.Current())
if *verbose {
if !equal {
fmt.Print("! ")
}
fmt.Printf("%04d %8.3fkbps %10s %10s\n", frame, speed, encode.Last(), decode.Last())
} else {
if equal {
fmt.Print(".")
} else {
fmt.Print("X")
}
}
}
fmt.Println()
fmt.Printf("#%d %.3fkbps ±%.3fkbps\n", len(sizes), stats.Mean(speeds), stats.StdDevS(speeds))
fmt.Println()
fmt.Printf("MIN %10.3f kbps\n", stats.Min(speeds))
for _, p := range []float64{5, 10, 25, 50, 75, 90, 95} {
fmt.Printf("P%02.f %10.3f kbps\n", p, stats.Percentile(speeds, p))
}
fmt.Printf("MAX %10.3f kbps\n", stats.Max(speeds))
fmt.Println()
fmt.Printf("TOTAL %10.3f kb\n", stats.Sum(sizes))
fmt.Printf(" AVG %10.3f kb per frame\n", stats.Mean(sizes))
fmt.Printf(" AVG %10.3f bits per cube\n", stats.Mean(sizes)*1000/float64(len(sizes)))
fmt.Println()
fmt.Println("TIMING:")
qpc.PrintSummary(encode, decode)
}
