go(stats): actually calculate median

stats/table.go

@@ -5,6 +5,7 @@
 
 import (
 	"fmt"
+	"sort"
 
 	"git.dotya.ml/wanderer/math-optim/report"
 	"gonum.org/v1/gonum/floats"
@@ -97,8 +98,29 @@ func statsFromBest(best []float64) []float64 {
 	s[0] = floats.Min(best)
 	s[1] = floats.Max(best)
 	s[2] = stat.Mean(best, nil)
-	s[3] = stat.Mean(best, nil)
+	s[3] = median(best)
 	s[4] = stat.StdDev(best, nil)
 
 	return s
 }
+
+// as per https://gosamples.dev/calculate-median/.
+func median(data []float64) float64 {
+	dataCopy := make([]float64, len(data))
+	copy(dataCopy, data)
+
+	sort.Float64s(dataCopy)
+
+	var median float64
+
+	//nolint: gocritic
+	if l := len(dataCopy); l == 0 {
+		return 0
+	} else if l%2 == 0 {
+		median = (dataCopy[l/2-1] + dataCopy[l/2]) / 2
+	} else {
+		median = dataCopy[l/2]
+	}
+
+	return median
+}

stats/table_test.go

@@ -40,7 +40,7 @@ func TestParseBenchStats(t *testing.T) {
 		},
 	}
 
-	wantResults := []float64{1336.3261400058473, 2169.7378893600176, 1737.765688971335, 1737.765688971335, 342.37072192259393}
+	wantResults := []float64{1336.3261400058473, 2169.7378893600176, 1737.765688971335, 1722.4993632597375, 342.37072192259393}
 	want := report.Row{
 		Title:  "D=5, f=De Jong 5th, G=3, I=4",
 		Values: wantResults,