| Index: webrtc/base/random_unittest.cc
|
| diff --git a/webrtc/base/random_unittest.cc b/webrtc/base/random_unittest.cc
|
| new file mode 100644
|
| index 0000000000000000000000000000000000000000..9f5fbe6e617a630027f4d68976c20e75568177d7
|
| --- /dev/null
|
| +++ b/webrtc/base/random_unittest.cc
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| @@ -0,0 +1,299 @@
|
| +/*
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| + * Copyright (c) 2015 The WebRTC project authors. All Rights Reserved.
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| + *
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| + * Use of this source code is governed by a BSD-style license
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| + * that can be found in the LICENSE file in the root of the source
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| + * tree. An additional intellectual property rights grant can be found
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| + * in the file PATENTS. All contributing project authors may
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| + * be found in the AUTHORS file in the root of the source tree.
|
| + */
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| +
|
| +#include <math.h>
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| +
|
| +#include <limits>
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| +#include <vector>
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| +
|
| +#include "testing/gtest/include/gtest/gtest.h"
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| +#include "webrtc/base/checks.h"
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| +#include "webrtc/base/random.h"
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| +
|
| +namespace webrtc {
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| +
|
| +namespace {
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| +template <typename T>
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| +T fdiv_remainder(T x, T n) {
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| + assert(n > 0);
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| + T remainder = x % n;
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| + if (remainder < 0)
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| + remainder += n;
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| + return remainder;
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| +}
|
| +} // namespace
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| +
|
| +template <typename T>
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| +void UniformBucketTest(T bucket_count, int samples, Random* prng) {
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| + std::vector<int> buckets(bucket_count, 0);
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| +
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| + uint64_t total_values = 1ull << (std::numeric_limits<T>::digits +
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| + std::numeric_limits<T>::is_signed);
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| + T upper_limit =
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| + std::numeric_limits<T>::max() -
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| + static_cast<T>(total_values % static_cast<uint64_t>(bucket_count));
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| + assert(upper_limit > std::numeric_limits<T>::max() / 2);
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| +
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| + for (int i = 0; i < samples; i++) {
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| + T sample;
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| + do {
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| + // We exclude a few numbers from the range so that it is divisible by
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| + // the number of buckets. If we are unlucky and hit one of the excluded
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| + // numbers we just resample. Note that if the number buckets is a power
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| + // of 2, then we don't have to exclude anything.
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| + sample = prng->Rand<T>();
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| + } while (sample > upper_limit);
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| + buckets[fdiv_remainder(sample, bucket_count)]++;
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| + }
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| +
|
| + for (T i = 0; i < bucket_count; i++) {
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| + // Expect the result to be within 3 standard deviations of the mean.
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| + EXPECT_NEAR(buckets[i], samples / bucket_count,
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| + 3 * sqrt(samples / bucket_count));
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| + }
|
| +}
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| +
|
| +TEST(RandomNumberGeneratorTest, BucketTestSignedChar) {
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| + Random prng(7297352569824ull);
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| + UniformBucketTest<signed char>(64, 640000, &prng);
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| + UniformBucketTest<signed char>(11, 440000, &prng);
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| + UniformBucketTest<signed char>(3, 270000, &prng);
|
| +}
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| +
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| +TEST(RandomNumberGeneratorTest, BucketTestUnsignedChar) {
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| + Random prng(7297352569824ull);
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| + UniformBucketTest<unsigned char>(64, 640000, &prng);
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| + UniformBucketTest<unsigned char>(11, 440000, &prng);
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| + UniformBucketTest<unsigned char>(3, 270000, &prng);
|
| +}
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| +
|
| +TEST(RandomNumberGeneratorTest, BucketTestSignedShort) {
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| + Random prng(7297352569824ull);
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| + UniformBucketTest<int16_t>(64, 640000, &prng);
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| + UniformBucketTest<int16_t>(11, 440000, &prng);
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| + UniformBucketTest<int16_t>(3, 270000, &prng);
|
| +}
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| +
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| +TEST(RandomNumberGeneratorTest, BucketTestUnsignedShort) {
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| + Random prng(7297352569824ull);
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| + UniformBucketTest<uint16_t>(64, 640000, &prng);
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| + UniformBucketTest<uint16_t>(11, 440000, &prng);
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| + UniformBucketTest<uint16_t>(3, 270000, &prng);
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| +}
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| +
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| +TEST(RandomNumberGeneratorTest, BucketTestSignedInt) {
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| + Random prng(7297352569824ull);
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| + UniformBucketTest<signed int>(64, 640000, &prng);
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| + UniformBucketTest<signed int>(11, 440000, &prng);
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| + UniformBucketTest<signed int>(3, 270000, &prng);
|
| +}
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| +
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| +TEST(RandomNumberGeneratorTest, BucketTestUnsignedInt) {
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| + Random prng(7297352569824ull);
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| + UniformBucketTest<unsigned int>(64, 640000, &prng);
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| + UniformBucketTest<unsigned int>(11, 440000, &prng);
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| + UniformBucketTest<unsigned int>(3, 270000, &prng);
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| +}
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| +
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| +// The range of the random numbers is divided into bucket count intervals
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| +// of consecutive numbers. Check that approximately equally many numbers
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| +// from each inteval are generated.
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| +void BucketTestSignedInterval(unsigned int bucket_count,
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| + unsigned int samples,
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| + int32_t low,
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| + int32_t high,
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| + int sigma_level,
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| + Random* prng) {
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| + std::vector<unsigned int> buckets(bucket_count, 0);
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| +
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| + assert(high >= low);
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| + assert(bucket_count >= 2);
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| + uint32_t interval = static_cast<uint32_t>(high - low + 1);
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| + uint32_t numbers_per_bucket;
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| + if (interval == 0) {
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| + // The computation high - low + 1 should be 2^32 but overflowed
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| + // Hence, bucket_count must be a power of 2
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| + assert((bucket_count & (bucket_count - 1)) == 0);
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| + numbers_per_bucket = (0x80000000u / bucket_count) * 2;
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| + } else {
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| + assert(interval % bucket_count == 0);
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| + numbers_per_bucket = interval / bucket_count;
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| + }
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| +
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| + for (unsigned int i = 0; i < samples; i++) {
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| + int32_t sample = prng->Rand(low, high);
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| + EXPECT_LE(low, sample);
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| + EXPECT_GE(high, sample);
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| + buckets[static_cast<uint32_t>(sample - low) / numbers_per_bucket]++;
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| + }
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| +
|
| + for (unsigned int i = 0; i < bucket_count; i++) {
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| + // Expect the result to be within 3 standard deviations of the mean,
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| + // or more generally, within sigma_level standard deviations of the mean.
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| + double mean = static_cast<double>(samples) / bucket_count;
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| + EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
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| + }
|
| +}
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| +
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| +// The range of the random numbers is divided into bucket count intervals
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| +// of consecutive numbers. Check that approximately equally many numbers
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| +// from each inteval are generated.
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| +void BucketTestUnsignedInterval(unsigned int bucket_count,
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| + unsigned int samples,
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| + uint32_t low,
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| + uint32_t high,
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| + int sigma_level,
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| + Random* prng) {
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| + std::vector<unsigned int> buckets(bucket_count, 0);
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| +
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| + assert(high >= low);
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| + assert(bucket_count >= 2);
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| + uint32_t interval = static_cast<uint32_t>(high - low + 1);
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| + uint32_t numbers_per_bucket;
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| + if (interval == 0) {
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| + // The computation high - low + 1 should be 2^32 but overflowed
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| + // Hence, bucket_count must be a power of 2
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| + assert((bucket_count & (bucket_count - 1)) == 0);
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| + numbers_per_bucket = (0x80000000u / bucket_count) * 2;
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| + } else {
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| + assert(interval % bucket_count == 0);
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| + numbers_per_bucket = interval / bucket_count;
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| + }
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| +
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| + for (unsigned int i = 0; i < samples; i++) {
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| + uint32_t sample = prng->Rand(low, high);
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| + EXPECT_LE(low, sample);
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| + EXPECT_GE(high, sample);
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| + buckets[static_cast<uint32_t>(sample - low) / numbers_per_bucket]++;
|
| + }
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| +
|
| + for (unsigned int i = 0; i < bucket_count; i++) {
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| + // Expect the result to be within 3 standard deviations of the mean,
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| + // or more generally, within sigma_level standard deviations of the mean.
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| + double mean = static_cast<double>(samples) / bucket_count;
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| + EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
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| + }
|
| +}
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| +
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| +TEST(RandomNumberGeneratorTest, UniformUnsignedInterval) {
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| + Random prng(299792458ull);
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| + BucketTestUnsignedInterval(2, 100000, 0, 1, 3, &prng);
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| + BucketTestUnsignedInterval(7, 100000, 1, 14, 3, &prng);
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| + BucketTestUnsignedInterval(11, 100000, 1000, 1010, 3, &prng);
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| + BucketTestUnsignedInterval(100, 100000, 0, 99, 3, &prng);
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| + BucketTestUnsignedInterval(2, 100000, 0, 4294967295, 3, &prng);
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| + BucketTestUnsignedInterval(17, 100000, 455, 2147484110, 3, &prng);
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| + // 99.7% of all samples will be within 3 standard deviations of the mean,
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| + // but since we test 1000 buckets we allow an interval of 4 sigma.
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| + BucketTestUnsignedInterval(1000, 1000000, 0, 2147483999, 4, &prng);
|
| +}
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| +
|
| +TEST(RandomNumberGeneratorTest, UniformSignedInterval) {
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| + Random prng(66260695729ull);
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| + BucketTestSignedInterval(2, 100000, 0, 1, 3, &prng);
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| + BucketTestSignedInterval(7, 100000, -2, 4, 3, &prng);
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| + BucketTestSignedInterval(11, 100000, 1000, 1010, 3, &prng);
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| + BucketTestSignedInterval(100, 100000, 0, 99, 3, &prng);
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| + BucketTestSignedInterval(2, 100000, std::numeric_limits<int32_t>::min(),
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| + std::numeric_limits<int32_t>::max(), 3, &prng);
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| + BucketTestSignedInterval(17, 100000, -1073741826, 1073741829, 3, &prng);
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| + // 99.7% of all samples will be within 3 standard deviations of the mean,
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| + // but since we test 1000 buckets we allow an interval of 4 sigma.
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| + BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
|
| +}
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| +
|
| +// The range of the random numbers is divided into bucket count intervals
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| +// of consecutive numbers. Check that approximately equally many numbers
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| +// from each inteval are generated.
|
| +void BucketTestFloat(unsigned int bucket_count,
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| + unsigned int samples,
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| + int sigma_level,
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| + Random* prng) {
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| + assert(bucket_count >= 2);
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| + std::vector<unsigned int> buckets(bucket_count, 0);
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| +
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| + for (unsigned int i = 0; i < samples; i++) {
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| + uint32_t sample = bucket_count * prng->Rand<float>();
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| + EXPECT_LE(0u, sample);
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| + EXPECT_GE(bucket_count - 1, sample);
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| + buckets[sample]++;
|
| + }
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| +
|
| + for (unsigned int i = 0; i < bucket_count; i++) {
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| + // Expect the result to be within 3 standard deviations of the mean,
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| + // or more generally, within sigma_level standard deviations of the mean.
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| + double mean = static_cast<double>(samples) / bucket_count;
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| + EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
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| + }
|
| +}
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| +
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| +TEST(RandomNumberGeneratorTest, UniformFloatInterval) {
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| + Random prng(1380648813ull);
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| + BucketTestFloat(100, 100000, 3, &prng);
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| + // 99.7% of all samples will be within 3 standard deviations of the mean,
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| + // but since we test 1000 buckets we allow an interval of 4 sigma.
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| + // BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
|
| +}
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| +
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| +TEST(RandomNumberGeneratorTest, SignedHasSameBitPattern) {
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| + Random prng_signed(66738480ull), prng_unsigned(66738480ull);
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| +
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| + for (int i = 0; i < 1000; i++) {
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| + signed int s = prng_signed.Rand<signed int>();
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| + unsigned int u = prng_unsigned.Rand<unsigned int>();
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| + EXPECT_EQ(u, static_cast<unsigned int>(s));
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| + }
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| +
|
| + for (int i = 0; i < 1000; i++) {
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| + int16_t s = prng_signed.Rand<int16_t>();
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| + uint16_t u = prng_unsigned.Rand<uint16_t>();
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| + EXPECT_EQ(u, static_cast<uint16_t>(s));
|
| + }
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| +
|
| + for (int i = 0; i < 1000; i++) {
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| + signed char s = prng_signed.Rand<signed char>();
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| + unsigned char u = prng_unsigned.Rand<unsigned char>();
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| + EXPECT_EQ(u, static_cast<unsigned char>(s));
|
| + }
|
| +}
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| +
|
| +TEST(RandomNumberGeneratorTest, Gaussian) {
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| + const int kN = 100000;
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| + const int kBuckets = 100;
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| + const double kMean = 49;
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| + const double kStddev = 10;
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| +
|
| + Random prng(1256637061);
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| +
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| + std::vector<unsigned int> buckets(kBuckets, 0);
|
| + for (int i = 0; i < kN; i++) {
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| + int index = prng.Gaussian(kMean, kStddev) + 0.5;
|
| + if (index >= 0 && index < kBuckets) {
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| + buckets[index]++;
|
| + }
|
| + }
|
| +
|
| + const double kPi = 3.14159265358979323846;
|
| + const double kScale = 1 / (kStddev * sqrt(2.0 * kPi));
|
| + const double kDiv = -2.0 * kStddev * kStddev;
|
| + for (int n = 0; n < kBuckets; ++n) {
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| + // Use Simpsons rule to estimate the probability that a random gaussian
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| + // sample is in the interval [n-0.5, n-0.5].
|
| + double f_left = kScale * exp((n - kMean - 0.5) * (n - kMean - 0.5) / kDiv);
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| + double f_mid = kScale * exp((n - kMean) * (n - kMean) / kDiv);
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| + double f_right = kScale * exp((n - kMean + 0.5) * (n - kMean + 0.5) / kDiv);
|
| + double normal_dist = (f_left + 4 * f_mid + f_right) / 6;
|
| + // Expect the number of samples to be within 3 standard deviations
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| + // (rounded up) of the expected number of samples in the bucket.
|
| + EXPECT_NEAR(buckets[n], kN * normal_dist, 3 * sqrt(kN * normal_dist) + 1);
|
| + }
|
| +}
|
| +
|
| +} // namespace webrtc
|
|
|