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Define the new Rand and Source types to allow creating
isolated sources of random values. Add normal and exponential distributions. Add some tests for the normal and exponential distributions. R=rsc APPROVED=rsc DELTA=1005 (904 added, 80 deleted, 21 changed) OCL=35501 CL=35779
This commit is contained in:
Dave Bort
parent
18325313fb
commit
3342574206
6 changed files with 921 additions and 97 deletions
314
src/pkg/rand/rand_test.go
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314
src/pkg/rand/rand_test.go
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// Copyright 2009 The Go Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package rand
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import (
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"math";
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"fmt";
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"os";
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"testing";
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)
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const (
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numTestSamples = 10000;
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)
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type statsResults struct {
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mean float64;
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stddev float64;
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closeEnough float64;
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maxError float64;
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}
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func max(a, b float64) float64 {
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if a > b {
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return a;
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}
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return b;
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}
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func nearEqual(a, b, closeEnough, maxError float64) bool {
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absDiff := math.Fabs(a-b);
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if absDiff < closeEnough { // Necessary when one value is zero and one value is close to zero.
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return true;
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}
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return absDiff / max(math.Fabs(a), math.Fabs(b)) < maxError;
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}
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var testSeeds = []int64{1, 1754801282, 1698661970, 1550503961}
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// checkSimilarDistribution returns success if the mean and stddev of the
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// two statsResults are similar.
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func (this *statsResults) checkSimilarDistribution(expected *statsResults) os.Error {
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if !nearEqual(this.mean, expected.mean, expected.closeEnough, expected.maxError) {
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s := fmt.Sprintf("mean %v != %v (allowed error %v, %v)", this.mean, expected.mean, expected.closeEnough, expected.maxError);
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fmt.Println(s);
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return os.ErrorString(s);
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}
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if !nearEqual(this.stddev, expected.stddev, 0, expected.maxError) {
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s := fmt.Sprintf("stddev %v != %v (allowed error %v, %v)", this.stddev, expected.stddev, expected.closeEnough, expected.maxError);
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fmt.Println(s);
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return os.ErrorString(s);
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}
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return nil;
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}
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func getStatsResults(samples []float64) *statsResults {
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res := new(statsResults);
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var sum float64;
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for i := range samples {
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sum += samples[i];
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}
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res.mean = sum/float64(len(samples));
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var devsum float64;
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for i := range samples {
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devsum += math.Pow(samples[i] - res.mean, 2);
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}
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res.stddev = math.Sqrt(devsum/float64(len(samples)));
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return res;
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}
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func checkSampleDistribution(t *testing.T, samples []float64, expected *statsResults) {
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actual := getStatsResults(samples);
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err := actual.checkSimilarDistribution(expected);
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if err != nil {
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t.Errorf(err.String());
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}
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}
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func checkSampleSliceDistributions(t *testing.T, samples []float64, nslices int, expected *statsResults) {
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chunk := len(samples)/nslices;
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for i := 0; i < nslices; i++ {
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low := i*chunk;
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var high int;
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if i == nslices-1 {
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high = len(samples)-1;
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} else {
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high = (i+1)*chunk;
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}
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checkSampleDistribution(t, samples[low:high], expected);
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}
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}
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//
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// Normal distribution tests
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//
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func generateNormalSamples(nsamples int, mean, stddev float64, seed int64) []float64 {
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r := New(NewSource(seed));
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samples := make([]float64, nsamples);
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for i := range samples {
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samples[i] = r.NormFloat64() * stddev + mean;
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}
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return samples;
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}
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func testNormalDistribution(t *testing.T, nsamples int, mean, stddev float64, seed int64) {
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//fmt.Printf("testing nsamples=%v mean=%v stddev=%v seed=%v\n", nsamples, mean, stddev, seed);
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samples := generateNormalSamples(nsamples, mean, stddev, seed);
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errorScale := max(1.0, stddev); // Error scales with stddev
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expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.08 * errorScale};
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// Make sure that the entire set matches the expected distribution.
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checkSampleDistribution(t, samples, expected);
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// Make sure that each half of the set matches the expected distribution.
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checkSampleSliceDistributions(t, samples, 2, expected);
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// Make sure that each 7th of the set matches the expected distribution.
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checkSampleSliceDistributions(t, samples, 7, expected);
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}
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// Actual tests
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func TestStandardNormalValues(t *testing.T) {
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for _, seed := range testSeeds {
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testNormalDistribution(t, numTestSamples, 0, 1, seed);
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}
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}
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func TestNonStandardNormalValues(t *testing.T) {
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for sd := float64(0.5); sd < 1000; sd *= 2 {
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for m := float64(0.5); m < 1000; m *= 2 {
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for _, seed := range testSeeds {
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testNormalDistribution(t, numTestSamples, m, sd, seed);
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}
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}
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}
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}
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//
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// Exponential distribution tests
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//
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func generateExponentialSamples(nsamples int, rate float64, seed int64) []float64 {
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r := New(NewSource(seed));
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samples := make([]float64, nsamples);
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for i := range samples {
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samples[i] = r.ExpFloat64() / rate;
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}
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return samples;
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}
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func testExponentialDistribution(t *testing.T, nsamples int, rate float64, seed int64) {
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//fmt.Printf("testing nsamples=%v rate=%v seed=%v\n", nsamples, rate, seed);
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mean := 1/rate;
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stddev := mean;
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samples := generateExponentialSamples(nsamples, rate, seed);
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errorScale := max(1.0, 1/rate); // Error scales with the inverse of the rate
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expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.20 * errorScale};
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// Make sure that the entire set matches the expected distribution.
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checkSampleDistribution(t, samples, expected);
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// Make sure that each half of the set matches the expected distribution.
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checkSampleSliceDistributions(t, samples, 2, expected);
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// Make sure that each 7th of the set matches the expected distribution.
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checkSampleSliceDistributions(t, samples, 7, expected);
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}
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// Actual tests
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func TestStandardExponentialValues(t *testing.T) {
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for _, seed := range testSeeds {
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testExponentialDistribution(t, numTestSamples, 1, seed);
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}
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}
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func TestNonStandardExponentialValues(t *testing.T) {
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for rate := float64(0.05); rate < 10; rate *= 2 {
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for _, seed := range testSeeds {
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testExponentialDistribution(t, numTestSamples, rate, seed);
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}
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}
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}
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//
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// Table generation tests
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//
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func initNorm() (testKn []uint32, testWn, testFn []float32) {
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const m1 = 1<<31;
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var (
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dn float64 = rn;
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tn = dn;
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vn float64 = 9.91256303526217e-3;
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)
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testKn = make([]uint32, 128);
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testWn = make([]float32, 128);
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testFn = make([]float32, 128);
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q := vn / math.Exp(-0.5 * dn * dn);
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testKn[0] = uint32((dn/q)*m1);
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testKn[1] = 0;
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testWn[0] = float32(q/m1);
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testWn[127] = float32(dn/m1);
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testFn[0] = 1.0;
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testFn[127] = float32(math.Exp(-0.5 * dn * dn));
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for i := 126; i >= 1; i-- {
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dn = math.Sqrt(-2.0 * math.Log(vn/dn + math.Exp(-0.5 * dn * dn)));
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testKn[i+1] = uint32((dn/tn)*m1);
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tn = dn;
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testFn[i] = float32(math.Exp(-0.5 * dn * dn));
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testWn[i] = float32(dn/m1);
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}
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return;
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}
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func initExp() (testKe []uint32, testWe, testFe []float32) {
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const m2 = 1<<32;
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var (
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de float64 = re;
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te = de;
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ve float64 = 3.9496598225815571993e-3;
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)
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testKe = make([]uint32, 256);
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testWe = make([]float32, 256);
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testFe = make([]float32, 256);
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q := ve / math.Exp(-de);
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testKe[0] = uint32((de/q)*m2);
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testKe[1] = 0;
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testWe[0] = float32(q/m2);
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testWe[255] = float32(de/m2);
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testFe[0] = 1.0;
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testFe[255] = float32(math.Exp(-de));
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for i := 254; i >= 1; i-- {
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de = -math.Log(ve/de + math.Exp(-de));
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testKe[i+1] = uint32((de/te)*m2);
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te = de;
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testFe[i] = float32(math.Exp(-de));
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testWe[i] = float32(de/m2);
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}
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return;
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}
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// compareUint32Slices returns the first index where the two slices
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// disagree, or <0 if the lengths are the same and all elements
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// are identical.
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func compareUint32Slices(s1, s2 []uint32) int {
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if len(s1) != len(s2) {
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if len(s1) > len(s2) {
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return len(s2)+1;
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}
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return len(s1)+1;
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}
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for i := range s1 {
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if s1[i] != s2[i] {
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return i;
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}
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}
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return -1;
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}
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// compareFloat32Slices returns the first index where the two slices
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// disagree, or <0 if the lengths are the same and all elements
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// are identical.
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func compareFloat32Slices(s1, s2 []float32) int {
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if len(s1) != len(s2) {
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if len(s1) > len(s2) {
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return len(s2)+1;
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}
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return len(s1)+1;
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}
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for i := range s1 {
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if !nearEqual(float64(s1[i]), float64(s2[i]), 0, 1e-7) {
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return i;
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}
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}
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return -1;
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}
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func TestNormTables(t *testing.T) {
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testKn, testWn, testFn := initNorm();
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if i := compareUint32Slices(kn[0:len(kn)], testKn); i >= 0 {
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t.Errorf("kn disagrees at index %v; %v != %v\n", i, kn[i], testKn[i]);
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}
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if i := compareFloat32Slices(wn[0:len(wn)], testWn); i >= 0 {
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t.Errorf("wn disagrees at index %v; %v != %v\n", i, wn[i], testWn[i]);
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}
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if i := compareFloat32Slices(fn[0:len(fn)], testFn); i >= 0 {
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t.Errorf("fn disagrees at index %v; %v != %v\n", i, fn[i], testFn[i]);
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}
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}
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func TestExpTables(t *testing.T) {
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testKe, testWe, testFe := initExp();
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if i := compareUint32Slices(ke[0:len(ke)], testKe); i >= 0 {
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t.Errorf("ke disagrees at index %v; %v != %v\n", i, ke[i], testKe[i]);
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}
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if i := compareFloat32Slices(we[0:len(we)], testWe); i >= 0 {
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t.Errorf("we disagrees at index %v; %v != %v\n", i, we[i], testWe[i]);
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}
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if i := compareFloat32Slices(fe[0:len(fe)], testFe); i >= 0 {
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t.Errorf("fe disagrees at index %v; %v != %v\n", i, fe[i], testFe[i]);
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}
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}
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