init

.hgignore

@@ -0,0 +1,2 @@
+tags
+.*.swp

ostat.go

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+package ostat
+
+import (
+	"errors"
+	"math"
+)
+
+// from http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Online_algorithm
+
+type OnlineStat struct {
+	n    int64
+	mean float64
+	m2   float64
+	Max  float64
+	Min  float64
+}
+
+func NewOnlineStat() *OnlineStat {
+	return &OnlineStat{
+		Min: math.Inf(1),
+		Max: math.Inf(-1),
+	}
+}
+
+func (os *OnlineStat) Push(v float64) {
+	os.n += 1
+	if v < os.Min {
+		os.Min = v
+	}
+	if v > os.Max {
+		os.Max = v
+	}
+
+	delta := v - os.mean
+	os.mean = os.mean + delta/float64(os.n)
+	os.m2 = os.m2 + delta*(v-os.mean)
+}
+
+func (os *OnlineStat) Mean() (float64, error) {
+	if os.n == 0 {
+		return 0.0, errors.New("no data")
+	}
+	return os.mean, nil
+}
+
+func (os *OnlineStat) Variance() (float64, error) {
+	if os.n == 0 {
+		return 0.0, errors.New("no data")
+	}
+	return os.m2 / float64(os.n-1), nil
+}
+
+func (os *OnlineStat) StdDev() (float64, error) {
+	variance, err := os.Variance()
+	return math.Sqrt(variance), err
+}

ostat_test.go

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+package ostat
+
+import (
+	"math"
+	"testing"
+)
+
+func TestInsert(t *testing.T) {
+	os := NewOnlineStat()
+	v := []float64{4, 7, 13, 16}
+	for _, i := range v {
+		os.Push(i)
+	}
+	if os.Min != 4 {
+		t.Errorf("incorrectly calculated min")
+	}
+	if os.Max != 16 {
+		t.Errorf("incorrectly calculated max")
+	}
+	if m, _ := os.Mean(); m != 10.0 {
+		t.Errorf("incorrect mean")
+	}
+	if variance, _ := os.Variance(); variance != 30.0 {
+		t.Errorf("incorrect variance: %f", variance)
+	}
+	if stdev, _ := os.StdDev(); stdev != math.Sqrt(30.0) {
+		t.Errorf("incorrect stdev: %f", stdev)
+	}
+}
+
+func TestEmpty(t *testing.T) {
+	os := NewOnlineStat()
+	_, err := os.Mean()
+	if err == nil {
+		t.Errorf("failure to notify the running stat was empty")
+	}
+	_, err = os.Variance()
+	if err == nil {
+		t.Errorf("failure to notify the running stat was empty")
+	}
+	_, err = os.StdDev()
+	if err == nil {
+		t.Errorf("failure to notify the running stat was empty")
+	}
+}