mirror of
https://github.com/autc04/Retro68.git
synced 2024-11-28 05:51:04 +00:00
363 lines
8.9 KiB
Go
363 lines
8.9 KiB
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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"errors"
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"fmt"
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"math"
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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.Abs(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.Abs(a), math.Abs(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) 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 errors.New(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 errors.New(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.Error())
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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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sdmax := 1000.0
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mmax := 1000.0
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if testing.Short() {
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sdmax = 5
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mmax = 5
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}
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for sd := 0.5; sd < sdmax; sd *= 2 {
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for m := 0.5; m < mmax; m *= 2 {
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for _, seed := range testSeeds {
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testNormalDistribution(t, numTestSamples, m, sd, seed)
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if testing.Short() {
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break
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}
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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 := 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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if testing.Short() {
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break
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}
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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:], testKn); i >= 0 {
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t.Errorf("kn disagrees at index %v; %v != %v", i, kn[i], testKn[i])
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}
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if i := compareFloat32Slices(wn[0:], testWn); i >= 0 {
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t.Errorf("wn disagrees at index %v; %v != %v", i, wn[i], testWn[i])
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}
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if i := compareFloat32Slices(fn[0:], testFn); i >= 0 {
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t.Errorf("fn disagrees at index %v; %v != %v", 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:], testKe); i >= 0 {
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t.Errorf("ke disagrees at index %v; %v != %v", i, ke[i], testKe[i])
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}
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if i := compareFloat32Slices(we[0:], testWe); i >= 0 {
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t.Errorf("we disagrees at index %v; %v != %v", i, we[i], testWe[i])
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}
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if i := compareFloat32Slices(fe[0:], testFe); i >= 0 {
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t.Errorf("fe disagrees at index %v; %v != %v", i, fe[i], testFe[i])
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}
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}
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// Benchmarks
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func BenchmarkInt63Threadsafe(b *testing.B) {
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for n := b.N; n > 0; n-- {
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Int63()
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}
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}
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func BenchmarkInt63Unthreadsafe(b *testing.B) {
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r := New(NewSource(1))
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for n := b.N; n > 0; n-- {
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r.Int63()
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}
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}
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func BenchmarkIntn1000(b *testing.B) {
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r := New(NewSource(1))
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for n := b.N; n > 0; n-- {
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r.Intn(1000)
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}
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}
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func BenchmarkInt63n1000(b *testing.B) {
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r := New(NewSource(1))
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for n := b.N; n > 0; n-- {
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r.Int63n(1000)
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}
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}
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func BenchmarkInt31n1000(b *testing.B) {
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r := New(NewSource(1))
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for n := b.N; n > 0; n-- {
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r.Int31n(1000)
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}
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}
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