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running_stats_test.go
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running_stats_test.go
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package statsd
import (
"math"
"testing"
)
// Test that a single metric is handled correctly
func TestRunningStats_Single(t *testing.T) {
rs := RunningStats{}
values := []float64{10.1}
for _, v := range values {
rs.AddValue(v)
}
if rs.Mean() != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Mean())
}
if rs.Upper() != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Upper())
}
if rs.Lower() != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Lower())
}
if rs.Percentile(90) != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Percentile(90))
}
if rs.Percentile(50) != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Percentile(50))
}
if rs.Count() != 1 {
t.Errorf("Expected %v, got %v", 1, rs.Count())
}
if rs.Variance() != 0 {
t.Errorf("Expected %v, got %v", 0, rs.Variance())
}
if rs.Stddev() != 0 {
t.Errorf("Expected %v, got %v", 0, rs.Stddev())
}
}
// Test that duplicate values are handled correctly
func TestRunningStats_Duplicate(t *testing.T) {
rs := RunningStats{}
values := []float64{10.1, 10.1, 10.1, 10.1}
for _, v := range values {
rs.AddValue(v)
}
if rs.Mean() != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Mean())
}
if rs.Upper() != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Upper())
}
if rs.Lower() != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Lower())
}
if rs.Percentile(90) != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Percentile(90))
}
if rs.Percentile(50) != 10.1 {
t.Errorf("Expected %v, got %v", 10.1, rs.Percentile(50))
}
if rs.Count() != 4 {
t.Errorf("Expected %v, got %v", 4, rs.Count())
}
if rs.Variance() != 0 {
t.Errorf("Expected %v, got %v", 0, rs.Variance())
}
if rs.Stddev() != 0 {
t.Errorf("Expected %v, got %v", 0, rs.Stddev())
}
}
// Test a list of sample values, returns all correct values
func TestRunningStats(t *testing.T) {
rs := RunningStats{}
values := []float64{10, 20, 10, 30, 20, 11, 12, 32, 45, 9, 5, 5, 5, 10, 23, 8}
for _, v := range values {
rs.AddValue(v)
}
if rs.Mean() != 15.9375 {
t.Errorf("Expected %v, got %v", 15.9375, rs.Mean())
}
if rs.Upper() != 45 {
t.Errorf("Expected %v, got %v", 45, rs.Upper())
}
if rs.Lower() != 5 {
t.Errorf("Expected %v, got %v", 5, rs.Lower())
}
if rs.Percentile(90) != 32 {
t.Errorf("Expected %v, got %v", 32, rs.Percentile(90))
}
if rs.Percentile(50) != 11 {
t.Errorf("Expected %v, got %v", 11, rs.Percentile(50))
}
if rs.Count() != 16 {
t.Errorf("Expected %v, got %v", 4, rs.Count())
}
if !fuzzyEqual(rs.Variance(), 124.93359, .00001) {
t.Errorf("Expected %v, got %v", 124.93359, rs.Variance())
}
if !fuzzyEqual(rs.Stddev(), 11.17736, .00001) {
t.Errorf("Expected %v, got %v", 11.17736, rs.Stddev())
}
}
// Test that the percentile limit is respected.
func TestRunningStats_PercentileLimit(t *testing.T) {
rs := RunningStats{}
rs.PercLimit = 10
values := []float64{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}
for _, v := range values {
rs.AddValue(v)
}
if rs.Count() != 11 {
t.Errorf("Expected %v, got %v", 11, rs.Count())
}
if len(rs.perc) != 10 {
t.Errorf("Expected %v, got %v", 10, len(rs.perc))
}
}
func fuzzyEqual(a, b, epsilon float64) bool {
if math.Abs(a-b) > epsilon {
return false
}
return true
}