1 files changed, 0 insertions, 363 deletions
diff --git a/Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go b/Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go
deleted file mode 100644
index d60e99c5b..000000000
--- a/Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go
+++ /dev/null
@@ -1,363 +0,0 @@
-package metrics
-
-import (
-	"math/rand"
-	"runtime"
-	"testing"
-	"time"
-)
-
-// Benchmark{Compute,Copy}{1000,1000000} demonstrate that, even for relatively
-// expensive computations like Variance, the cost of copying the Sample, as
-// approximated by a make and copy, is much greater than the cost of the
-// computation for small samples and only slightly less for large samples.
-func BenchmarkCompute1000(b *testing.B) {
-	s := make([]int64, 1000)
-	for i := 0; i < len(s); i++ {
-		s[i] = int64(i)
-	}
-	b.ResetTimer()
-	for i := 0; i < b.N; i++ {
-		SampleVariance(s)
-	}
-}
-func BenchmarkCompute1000000(b *testing.B) {
-	s := make([]int64, 1000000)
-	for i := 0; i < len(s); i++ {
-		s[i] = int64(i)
-	}
-	b.ResetTimer()
-	for i := 0; i < b.N; i++ {
-		SampleVariance(s)
-	}
-}
-func BenchmarkCopy1000(b *testing.B) {
-	s := make([]int64, 1000)
-	for i := 0; i < len(s); i++ {
-		s[i] = int64(i)
-	}
-	b.ResetTimer()
-	for i := 0; i < b.N; i++ {
-		sCopy := make([]int64, len(s))
-		copy(sCopy, s)
-	}
-}
-func BenchmarkCopy1000000(b *testing.B) {
-	s := make([]int64, 1000000)
-	for i := 0; i < len(s); i++ {
-		s[i] = int64(i)
-	}
-	b.ResetTimer()
-	for i := 0; i < b.N; i++ {
-		sCopy := make([]int64, len(s))
-		copy(sCopy, s)
-	}
-}
-
-func BenchmarkExpDecaySample257(b *testing.B) {
-	benchmarkSample(b, NewExpDecaySample(257, 0.015))
-}
-
-func BenchmarkExpDecaySample514(b *testing.B) {
-	benchmarkSample(b, NewExpDecaySample(514, 0.015))
-}
-
-func BenchmarkExpDecaySample1028(b *testing.B) {
-	benchmarkSample(b, NewExpDecaySample(1028, 0.015))
-}
-
-func BenchmarkUniformSample257(b *testing.B) {
-	benchmarkSample(b, NewUniformSample(257))
-}
-
-func BenchmarkUniformSample514(b *testing.B) {
-	benchmarkSample(b, NewUniformSample(514))
-}
-
-func BenchmarkUniformSample1028(b *testing.B) {
-	benchmarkSample(b, NewUniformSample(1028))
-}
-
-func TestExpDecaySample10(t *testing.T) {
-	rand.Seed(1)
-	s := NewExpDecaySample(100, 0.99)
-	for i := 0; i < 10; i++ {
-		s.Update(int64(i))
-	}
-	if size := s.Count(); 10 != size {
-		t.Errorf("s.Count(): 10 != %v\n", size)
-	}
-	if size := s.Size(); 10 != size {
-		t.Errorf("s.Size(): 10 != %v\n", size)
-	}
-	if l := len(s.Values()); 10 != l {
-		t.Errorf("len(s.Values()): 10 != %v\n", l)
-	}
-	for _, v := range s.Values() {
-		if v > 10 || v < 0 {
-			t.Errorf("out of range [0, 10): %v\n", v)
-		}
-	}
-}
-
-func TestExpDecaySample100(t *testing.T) {
-	rand.Seed(1)
-	s := NewExpDecaySample(1000, 0.01)
-	for i := 0; i < 100; i++ {
-		s.Update(int64(i))
-	}
-	if size := s.Count(); 100 != size {
-		t.Errorf("s.Count(): 100 != %v\n", size)
-	}
-	if size := s.Size(); 100 != size {
-		t.Errorf("s.Size(): 100 != %v\n", size)
-	}
-	if l := len(s.Values()); 100 != l {
-		t.Errorf("len(s.Values()): 100 != %v\n", l)
-	}
-	for _, v := range s.Values() {
-		if v > 100 || v < 0 {
-			t.Errorf("out of range [0, 100): %v\n", v)
-		}
-	}
-}
-
-func TestExpDecaySample1000(t *testing.T) {
-	rand.Seed(1)
-	s := NewExpDecaySample(100, 0.99)
-	for i := 0; i < 1000; i++ {
-		s.Update(int64(i))
-	}
-	if size := s.Count(); 1000 != size {
-		t.Errorf("s.Count(): 1000 != %v\n", size)
-	}
-	if size := s.Size(); 100 != size {
-		t.Errorf("s.Size(): 100 != %v\n", size)
-	}
-	if l := len(s.Values()); 100 != l {
-		t.Errorf("len(s.Values()): 100 != %v\n", l)
-	}
-	for _, v := range s.Values() {
-		if v > 1000 || v < 0 {
-			t.Errorf("out of range [0, 1000): %v\n", v)
-		}
-	}
-}
-
-// This test makes sure that the sample's priority is not amplified by using
-// nanosecond duration since start rather than second duration since start.
-// The priority becomes +Inf quickly after starting if this is done,
-// effectively freezing the set of samples until a rescale step happens.
-func TestExpDecaySampleNanosecondRegression(t *testing.T) {
-	rand.Seed(1)
-	s := NewExpDecaySample(100, 0.99)
-	for i := 0; i < 100; i++ {
-		s.Update(10)
-	}
-	time.Sleep(1 * time.Millisecond)
-	for i := 0; i < 100; i++ {
-		s.Update(20)
-	}
-	v := s.Values()
-	avg := float64(0)
-	for i := 0; i < len(v); i++ {
-		avg += float64(v[i])
-	}
-	avg /= float64(len(v))
-	if avg > 16 || avg < 14 {
-		t.Errorf("out of range [14, 16]: %v\n", avg)
-	}
-}
-
-func TestExpDecaySampleRescale(t *testing.T) {
-	s := NewExpDecaySample(2, 0.001).(*ExpDecaySample)
-	s.update(time.Now(), 1)
-	s.update(time.Now().Add(time.Hour+time.Microsecond), 1)
-	for _, v := range s.values.Values() {
-		if v.k == 0.0 {
-			t.Fatal("v.k == 0.0")
-		}
-	}
-}
-
-func TestExpDecaySampleSnapshot(t *testing.T) {
-	now := time.Now()
-	rand.Seed(1)
-	s := NewExpDecaySample(100, 0.99)
-	for i := 1; i <= 10000; i++ {
-		s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i))
-	}
-	snapshot := s.Snapshot()
-	s.Update(1)
-	testExpDecaySampleStatistics(t, snapshot)
-}
-
-func TestExpDecaySampleStatistics(t *testing.T) {
-	now := time.Now()
-	rand.Seed(1)
-	s := NewExpDecaySample(100, 0.99)
-	for i := 1; i <= 10000; i++ {
-		s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i))
-	}
-	testExpDecaySampleStatistics(t, s)
-}
-
-func TestUniformSample(t *testing.T) {
-	rand.Seed(1)
-	s := NewUniformSample(100)
-	for i := 0; i < 1000; i++ {
-		s.Update(int64(i))
-	}
-	if size := s.Count(); 1000 != size {
-		t.Errorf("s.Count(): 1000 != %v\n", size)
-	}
-	if size := s.Size(); 100 != size {
-		t.Errorf("s.Size(): 100 != %v\n", size)
-	}
-	if l := len(s.Values()); 100 != l {
-		t.Errorf("len(s.Values()): 100 != %v\n", l)
-	}
-	for _, v := range s.Values() {
-		if v > 1000 || v < 0 {
-			t.Errorf("out of range [0, 100): %v\n", v)
-		}
-	}
-}
-
-func TestUniformSampleIncludesTail(t *testing.T) {
-	rand.Seed(1)
-	s := NewUniformSample(100)
-	max := 100
-	for i := 0; i < max; i++ {
-		s.Update(int64(i))
-	}
-	v := s.Values()
-	sum := 0
-	exp := (max - 1) * max / 2
-	for i := 0; i < len(v); i++ {
-		sum += int(v[i])
-	}
-	if exp != sum {
-		t.Errorf("sum: %v != %v\n", exp, sum)
-	}
-}
-
-func TestUniformSampleSnapshot(t *testing.T) {
-	s := NewUniformSample(100)
-	for i := 1; i <= 10000; i++ {
-		s.Update(int64(i))
-	}
-	snapshot := s.Snapshot()
-	s.Update(1)
-	testUniformSampleStatistics(t, snapshot)
-}
-
-func TestUniformSampleStatistics(t *testing.T) {
-	rand.Seed(1)
-	s := NewUniformSample(100)
-	for i := 1; i <= 10000; i++ {
-		s.Update(int64(i))
-	}
-	testUniformSampleStatistics(t, s)
-}
-
-func benchmarkSample(b *testing.B, s Sample) {
-	var memStats runtime.MemStats
-	runtime.ReadMemStats(&memStats)
-	pauseTotalNs := memStats.PauseTotalNs
-	b.ResetTimer()
-	for i := 0; i < b.N; i++ {
-		s.Update(1)
-	}
-	b.StopTimer()
-	runtime.GC()
-	runtime.ReadMemStats(&memStats)
-	b.Logf("GC cost: %d ns/op", int(memStats.PauseTotalNs-pauseTotalNs)/b.N)
-}
-
-func testExpDecaySampleStatistics(t *testing.T, s Sample) {
-	if count := s.Count(); 10000 != count {
-		t.Errorf("s.Count(): 10000 != %v\n", count)
-	}
-	if min := s.Min(); 107 != min {
-		t.Errorf("s.Min(): 107 != %v\n", min)
-	}
-	if max := s.Max(); 10000 != max {
-		t.Errorf("s.Max(): 10000 != %v\n", max)
-	}
-	if mean := s.Mean(); 4965.98 != mean {
-		t.Errorf("s.Mean(): 4965.98 != %v\n", mean)
-	}
-	if stdDev := s.StdDev(); 2959.825156930727 != stdDev {
-		t.Errorf("s.StdDev(): 2959.825156930727 != %v\n", stdDev)
-	}
-	ps := s.Percentiles([]float64{0.5, 0.75, 0.99})
-	if 4615 != ps[0] {
-		t.Errorf("median: 4615 != %v\n", ps[0])
-	}
-	if 7672 != ps[1] {
-		t.Errorf("75th percentile: 7672 != %v\n", ps[1])
-	}
-	if 9998.99 != ps[2] {
-		t.Errorf("99th percentile: 9998.99 != %v\n", ps[2])
-	}
-}
-
-func testUniformSampleStatistics(t *testing.T, s Sample) {
-	if count := s.Count(); 10000 != count {
-		t.Errorf("s.Count(): 10000 != %v\n", count)
-	}
-	if min := s.Min(); 37 != min {
-		t.Errorf("s.Min(): 37 != %v\n", min)
-	}
-	if max := s.Max(); 9989 != max {
-		t.Errorf("s.Max(): 9989 != %v\n", max)
-	}
-	if mean := s.Mean(); 4748.14 != mean {
-		t.Errorf("s.Mean(): 4748.14 != %v\n", mean)
-	}
-	if stdDev := s.StdDev(); 2826.684117548333 != stdDev {
-		t.Errorf("s.StdDev(): 2826.684117548333 != %v\n", stdDev)
-	}
-	ps := s.Percentiles([]float64{0.5, 0.75, 0.99})
-	if 4599 != ps[0] {
-		t.Errorf("median: 4599 != %v\n", ps[0])
-	}
-	if 7380.5 != ps[1] {
-		t.Errorf("75th percentile: 7380.5 != %v\n", ps[1])
-	}
-	if 9986.429999999998 != ps[2] {
-		t.Errorf("99th percentile: 9986.429999999998 != %v\n", ps[2])
-	}
-}
-
-// TestUniformSampleConcurrentUpdateCount would expose data race problems with
-// concurrent Update and Count calls on Sample when test is called with -race
-// argument
-func TestUniformSampleConcurrentUpdateCount(t *testing.T) {
-	if testing.Short() {
-		t.Skip("skipping in short mode")
-	}
-	s := NewUniformSample(100)
-	for i := 0; i < 100; i++ {
-		s.Update(int64(i))
-	}
-	quit := make(chan struct{})
-	go func() {
-		t := time.NewTicker(10 * time.Millisecond)
-		for {
-			select {
-			case <-t.C:
-				s.Update(rand.Int63())
-			case <-quit:
-				t.Stop()
-				return
-			}
-		}
-	}()
-	for i := 0; i < 1000; i++ {
-		s.Count()
-		time.Sleep(5 * time.Millisecond)
-	}
-	quit <- struct{}{}
-}