// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package rand
import (
"math";
"fmt";
"os";
"testing";
)
const (
numTestSamples = 10000;
)
type statsResults struct {
mean float64;
stddev float64;
closeEnough float64;
maxError float64;
}
func max(a, b float64) float64 {
if a > b {
return a
}
return b;
}
func nearEqual(a, b, closeEnough, maxError float64) bool {
absDiff := math.Fabs(a - b);
if absDiff < closeEnough { // Necessary when one value is zero and one value is close to zero.
return true
}
return absDiff/max(math.Fabs(a), math.Fabs(b)) < maxError;
}
var testSeeds = []int64{1, 1754801282, 1698661970, 1550503961}
// checkSimilarDistribution returns success if the mean and stddev of the
// two statsResults are similar.
func (this *statsResults) checkSimilarDistribution(expected *statsResults) os.Error {
if !nearEqual(this.mean, expected.mean, expected.closeEnough, expected.maxError) {
s := fmt.Sprintf("mean %v != %v (allowed error %v, %v)", this.mean, expected.mean, expected.closeEnough, expected.maxError);
fmt.Println(s);
return os.ErrorString(s);
}
if !nearEqual(this.stddev, expected.stddev, 0, expected.maxError) {
s := fmt.Sprintf("stddev %v != %v (allowed error %v, %v)", this.stddev, expected.stddev, expected.closeEnough, expected.maxError);
fmt.Println(s);
return os.ErrorString(s);
}
return nil;
}
func getStatsResults(samples []float64) *statsResults {
res := new(statsResults);
var sum float64;
for i := range samples {
sum += samples[i]
}
res.mean = sum / float64(len(samples));
var devsum float64;
for i := range samples {
devsum += math.Pow(samples[i]-res.mean, 2)
}
res.stddev = math.Sqrt(devsum / float64(len(samples)));
return res;
}
func checkSampleDistribution(t *testing.T, samples []float64, expected *statsResults) {
actual := getStatsResults(samples);
err := actual.checkSimilarDistribution(expected);
if err != nil {
t.Errorf(err.String())
}
}
func checkSampleSliceDistributions(t *testing.T, samples []float64, nslices int, expected *statsResults) {
chunk := len(samples) / nslices;
for i := 0; i < nslices; i++ {
low := i * chunk;
var high int;
if i == nslices-1 {
high = len(samples) - 1
} else {
high = (i + 1) * chunk
}
checkSampleDistribution(t, samples[low:high], expected);
}
}
//
// Normal distribution tests
//
func generateNormalSamples(nsamples int, mean, stddev float64, seed int64) []float64 {
r := New(NewSource(seed));
samples := make([]float64, nsamples);
for i := range samples {
samples[i] = r.NormFloat64()*stddev + mean
}
return samples;
}
func testNormalDistribution(t *testing.T, nsamples int, mean, stddev float64, seed int64) {
//fmt.Printf("testing nsamples=%v mean=%v stddev=%v seed=%v\n", nsamples, mean, stddev, seed);
samples := generateNormalSamples(nsamples, mean, stddev, seed);
errorScale := max(1.0, stddev); // Error scales with stddev
expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.08 * errorScale};
// Make sure that the entire set matches the expected distribution.
checkSampleDistribution(t, samples, expected);
// Make sure that each half of the set matches the expected distribution.
checkSampleSliceDistributions(t, samples, 2, expected);
// Make sure that each 7th of the set matches the expected distribution.
checkSampleSliceDistributions(t, samples, 7, expected);
}
// Actual tests
func TestStandardNormalValues(t *testing.T) {
for _, seed := range testSeeds {
testNormalDistribution(t, numTestSamples, 0, 1, seed)
}
}
func TestNonStandardNormalValues(t *testing.T) {
for sd := float64(0.5); sd < 1000; sd *= 2 {
for m := float64(0.5); m < 1000; m *= 2 {
for _, seed := range testSeeds {
testNormalDistribution(t, numTestSamples, m, sd, seed)
}
}
}
}
//
// Exponential distribution tests
//
func generateExponentialSamples(nsamples int, rate float64, seed int64) []float64 {
r := New(NewSource(seed));
samples := make([]float64, nsamples);
for i := range samples {
samples[i] = r.ExpFloat64() / rate
}
return samples;
}
func testExponentialDistribution(t *testing.T, nsamples int, rate float64, seed int64) {
//fmt.Printf("testing nsamples=%v rate=%v seed=%v\n", nsamples, rate, seed);
mean := 1 / rate;
stddev := mean;
samples := generateExponentialSamples(nsamples, rate, seed);
errorScale := max(1.0, 1/rate); // Error scales with the inverse of the rate
expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.20 * errorScale};
// Make sure that the entire set matches the expected distribution.
checkSampleDistribution(t, samples, expected);
// Make sure that each half of the set matches the expected distribution.
checkSampleSliceDistributions(t, samples, 2, expected);
// Make sure that each 7th of the set matches the expected distribution.
checkSampleSliceDistributions(t, samples, 7, expected);
}
// Actual tests
func TestStandardExponentialValues(t *testing.T) {
for _, seed := range testSeeds {
testExponentialDistribution(t, numTestSamples, 1, seed)
}
}
func TestNonStandardExponentialValues(t *testing.T) {
for rate := float64(0.05); rate < 10; rate *= 2 {
for _, seed := range testSeeds {
testExponentialDistribution(t, numTestSamples, rate, seed)
}
}
}
//
// Table generation tests
//
func initNorm() (testKn []uint32, testWn, testFn []float32) {
const m1 = 1 << 31;
var (
dn float64 = rn;
tn = dn;
vn float64 = 9.91256303526217e-3;
)
testKn = make([]uint32, 128);
testWn = make([]float32, 128);
testFn = make([]float32, 128);
q := vn / math.Exp(-0.5*dn*dn);
testKn[0] = uint32((dn / q) * m1);
testKn[1] = 0;
testWn[0] = float32(q / m1);
testWn[127] = float32(dn / m1);
testFn[0] = 1.0;
testFn[127] = float32(math.Exp(-0.5 * dn * dn));
for i := 126; i >= 1; i-- {
dn = math.Sqrt(-2.0 * math.Log(vn/dn+math.Exp(-0.5*dn*dn)));
testKn[i+1] = uint32((dn / tn) * m1);
tn = dn;
testFn[i] = float32(math.Exp(-0.5 * dn * dn));
testWn[i] = float32(dn / m1);
}
return;
}
func initExp() (testKe []uint32, testWe, testFe []float32) {
const m2 = 1 << 32;
var (
de float64 = re;
te = de;
ve float64 = 3.9496598225815571993e-3;
)
testKe = make([]uint32, 256);
testWe = make([]float32, 256);
testFe = make([]float32, 256);
q := ve / math.Exp(-de);
testKe[0] = uint32((de / q) * m2);
testKe[1] = 0;
testWe[0] = float32(q / m2);
testWe[255] = float32(de / m2);
testFe[0] = 1.0;
testFe[255] = float32(math.Exp(-de));
for i := 254; i >= 1; i-- {
de = -math.Log(ve/de + math.Exp(-de));
testKe[i+1] = uint32((de / te) * m2);
te = de;
testFe[i] = float32(math.Exp(-de));
testWe[i] = float32(de / m2);
}
return;
}
// compareUint32Slices returns the first index where the two slices
// disagree, or <0 if the lengths are the same and all elements
// are identical.
func compareUint32Slices(s1, s2 []uint32) int {
if len(s1) != len(s2) {
if len(s1) > len(s2) {
return len(s2) + 1
}
return len(s1) + 1;
}
for i := range s1 {
if s1[i] != s2[i] {
return i
}
}
return -1;
}
// compareFloat32Slices returns the first index where the two slices
// disagree, or <0 if the lengths are the same and all elements
// are identical.
func compareFloat32Slices(s1, s2 []float32) int {
if len(s1) != len(s2) {
if len(s1) > len(s2) {
return len(s2) + 1
}
return len(s1) + 1;
}
for i := range s1 {
if !nearEqual(float64(s1[i]), float64(s2[i]), 0, 1e-7) {
return i
}
}
return -1;
}
func TestNormTables(t *testing.T) {
testKn, testWn, testFn := initNorm();
if i := compareUint32Slices(kn[0:], testKn); i >= 0 {
t.Errorf("kn disagrees at index %v; %v != %v\n", i, kn[i], testKn[i])
}
if i := compareFloat32Slices(wn[0:], testWn); i >= 0 {
t.Errorf("wn disagrees at index %v; %v != %v\n", i, wn[i], testWn[i])
}
if i := compareFloat32Slices(fn[0:], testFn); i >= 0 {
t.Errorf("fn disagrees at index %v; %v != %v\n", i, fn[i], testFn[i])
}
}
func TestExpTables(t *testing.T) {
testKe, testWe, testFe := initExp();
if i := compareUint32Slices(ke[0:], testKe); i >= 0 {
t.Errorf("ke disagrees at index %v; %v != %v\n", i, ke[i], testKe[i])
}
if i := compareFloat32Slices(we[0:], testWe); i >= 0 {
t.Errorf("we disagrees at index %v; %v != %v\n", i, we[i], testWe[i])
}
if i := compareFloat32Slices(fe[0:], testFe); i >= 0 {
t.Errorf("fe disagrees at index %v; %v != %v\n", i, fe[i], testFe[i])
}
}
// Benchmarks
func BenchmarkInt63Threadsafe(b *testing.B) {
for n := b.N; n > 0; n-- {
Int63()
}
}
func BenchmarkInt63Unthreadsafe(b *testing.B) {
r := New(NewSource(1));
for n := b.N; n > 0; n-- {
r.Int63()
}
}
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