rtc_base/random_unittest.cc - src - Git at Google

 /*
  *  Copyright (c) 2015 The WebRTC project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */

 #include "rtc_base/random.h"

 #include <math.h>

 #include <limits>
 #include <vector>

 #include "rtc_base/numerics/math_utils.h"  // unsigned difference
 #include "test/gtest.h"

 namespace webrtc {

 namespace {
 // Computes the positive remainder of x/n.
 template <typename T>
 T fdiv_remainder(T x, T n) {
   RTC_CHECK_GE(n, 0);
   T remainder = x % n;
   if (remainder < 0)
     remainder += n;
   return remainder;
 }
 }  // namespace

 // Sample a number of random integers of type T. Divide them into buckets
 // based on the remainder when dividing by bucket_count and check that each
 // bucket gets roughly the expected number of elements.
 template <typename T>
 void UniformBucketTest(T bucket_count, int samples, Random* prng) {
   std::vector<int> buckets(bucket_count, 0);

   uint64_t total_values = 1ull << (std::numeric_limits<T>::digits +
                                    std::numeric_limits<T>::is_signed);
   T upper_limit =
       std::numeric_limits<T>::max() -
       static_cast<T>(total_values % static_cast<uint64_t>(bucket_count));
   ASSERT_GT(upper_limit, std::numeric_limits<T>::max() / 2);

   for (int i = 0; i < samples; i++) {
     T sample;
     do {
       // We exclude a few numbers from the range so that it is divisible by
       // the number of buckets. If we are unlucky and hit one of the excluded
       // numbers we just resample. Note that if the number of buckets is a
       // power of 2, then we don't have to exclude anything.
       sample = prng->Rand<T>();
     } while (sample > upper_limit);
     buckets[fdiv_remainder(sample, bucket_count)]++;
   }

   for (T i = 0; i < bucket_count; i++) {
     // Expect the result to be within 3 standard deviations of the mean.
     EXPECT_NEAR(buckets[i], samples / bucket_count,
                 3 * sqrt(samples / bucket_count));
   }
 }

 TEST(RandomNumberGeneratorTest, BucketTestSignedChar) {
   Random prng(7297352569824ull);
   UniformBucketTest<signed char>(64, 640000, &prng);
   UniformBucketTest<signed char>(11, 440000, &prng);
   UniformBucketTest<signed char>(3, 270000, &prng);
 }

 TEST(RandomNumberGeneratorTest, BucketTestUnsignedChar) {
   Random prng(7297352569824ull);
   UniformBucketTest<unsigned char>(64, 640000, &prng);
   UniformBucketTest<unsigned char>(11, 440000, &prng);
   UniformBucketTest<unsigned char>(3, 270000, &prng);
 }

 TEST(RandomNumberGeneratorTest, BucketTestSignedShort) {
   Random prng(7297352569824ull);
   UniformBucketTest<int16_t>(64, 640000, &prng);
   UniformBucketTest<int16_t>(11, 440000, &prng);
   UniformBucketTest<int16_t>(3, 270000, &prng);
 }

 TEST(RandomNumberGeneratorTest, BucketTestUnsignedShort) {
   Random prng(7297352569824ull);
   UniformBucketTest<uint16_t>(64, 640000, &prng);
   UniformBucketTest<uint16_t>(11, 440000, &prng);
   UniformBucketTest<uint16_t>(3, 270000, &prng);
 }

 TEST(RandomNumberGeneratorTest, BucketTestSignedInt) {
   Random prng(7297352569824ull);
   UniformBucketTest<signed int>(64, 640000, &prng);
   UniformBucketTest<signed int>(11, 440000, &prng);
   UniformBucketTest<signed int>(3, 270000, &prng);
 }

 TEST(RandomNumberGeneratorTest, BucketTestUnsignedInt) {
   Random prng(7297352569824ull);
   UniformBucketTest<unsigned int>(64, 640000, &prng);
   UniformBucketTest<unsigned int>(11, 440000, &prng);
   UniformBucketTest<unsigned int>(3, 270000, &prng);
 }

 // The range of the random numbers is divided into bucket_count intervals
 // of consecutive numbers. Check that approximately equally many numbers
 // from each inteval are generated.
 void BucketTestSignedInterval(unsigned int bucket_count,
                               unsigned int samples,
                               int32_t low,
                               int32_t high,
                               int sigma_level,
                               Random* prng) {
   std::vector<unsigned int> buckets(bucket_count, 0);

   ASSERT_GE(high, low);
   ASSERT_GE(bucket_count, 2u);
   uint32_t interval = webrtc_impl::unsigned_difference<int32_t>(high, low) + 1;
   uint32_t numbers_per_bucket;
   if (interval == 0) {
     // The computation high - low + 1 should be 2^32 but overflowed
     // Hence, bucket_count must be a power of 2
     ASSERT_EQ(bucket_count & (bucket_count - 1), 0u);
     numbers_per_bucket = (0x80000000u / bucket_count) * 2;
   } else {
     ASSERT_EQ(interval % bucket_count, 0u);
     numbers_per_bucket = interval / bucket_count;
   }

   for (unsigned int i = 0; i < samples; i++) {
     int32_t sample = prng->Rand(low, high);
     EXPECT_LE(low, sample);
     EXPECT_GE(high, sample);
     buckets[webrtc_impl::unsigned_difference<int32_t>(sample, low) /
             numbers_per_bucket]++;
   }

   for (unsigned int i = 0; i < bucket_count; i++) {
     // Expect the result to be within 3 standard deviations of the mean,
     // or more generally, within sigma_level standard deviations of the mean.
     double mean = static_cast<double>(samples) / bucket_count;
     EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
   }
 }

 // The range of the random numbers is divided into bucket_count intervals
 // of consecutive numbers. Check that approximately equally many numbers
 // from each inteval are generated.
 void BucketTestUnsignedInterval(unsigned int bucket_count,
                                 unsigned int samples,
                                 uint32_t low,
                                 uint32_t high,
                                 int sigma_level,
                                 Random* prng) {
   std::vector<unsigned int> buckets(bucket_count, 0);

   ASSERT_GE(high, low);
   ASSERT_GE(bucket_count, 2u);
   uint32_t interval = high - low + 1;
   uint32_t numbers_per_bucket;
   if (interval == 0) {
     // The computation high - low + 1 should be 2^32 but overflowed
     // Hence, bucket_count must be a power of 2
     ASSERT_EQ(bucket_count & (bucket_count - 1), 0u);
     numbers_per_bucket = (0x80000000u / bucket_count) * 2;
   } else {
     ASSERT_EQ(interval % bucket_count, 0u);
     numbers_per_bucket = interval / bucket_count;
   }

   for (unsigned int i = 0; i < samples; i++) {
     uint32_t sample = prng->Rand(low, high);
     EXPECT_LE(low, sample);
     EXPECT_GE(high, sample);
     buckets[(sample - low) / numbers_per_bucket]++;
   }

   for (unsigned int i = 0; i < bucket_count; i++) {
     // Expect the result to be within 3 standard deviations of the mean,
     // or more generally, within sigma_level standard deviations of the mean.
     double mean = static_cast<double>(samples) / bucket_count;
     EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
   }
 }

 TEST(RandomNumberGeneratorTest, UniformUnsignedInterval) {
   Random prng(299792458ull);
   BucketTestUnsignedInterval(2, 100000, 0, 1, 3, &prng);
   BucketTestUnsignedInterval(7, 100000, 1, 14, 3, &prng);
   BucketTestUnsignedInterval(11, 100000, 1000, 1010, 3, &prng);
   BucketTestUnsignedInterval(100, 100000, 0, 99, 3, &prng);
   BucketTestUnsignedInterval(2, 100000, 0, 4294967295, 3, &prng);
   BucketTestUnsignedInterval(17, 100000, 455, 2147484110, 3, &prng);
   // 99.7% of all samples will be within 3 standard deviations of the mean,
   // but since we test 1000 buckets we allow an interval of 4 sigma.
   BucketTestUnsignedInterval(1000, 1000000, 0, 2147483999, 4, &prng);
 }

 TEST(RandomNumberGeneratorTest, UniformSignedInterval) {
   Random prng(66260695729ull);
   BucketTestSignedInterval(2, 100000, 0, 1, 3, &prng);
   BucketTestSignedInterval(7, 100000, -2, 4, 3, &prng);
   BucketTestSignedInterval(11, 100000, 1000, 1010, 3, &prng);
   BucketTestSignedInterval(100, 100000, 0, 99, 3, &prng);
   BucketTestSignedInterval(2, 100000, std::numeric_limits<int32_t>::min(),
                            std::numeric_limits<int32_t>::max(), 3, &prng);
   BucketTestSignedInterval(17, 100000, -1073741826, 1073741829, 3, &prng);
   // 99.7% of all samples will be within 3 standard deviations of the mean,
   // but since we test 1000 buckets we allow an interval of 4 sigma.
   BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
 }

 // The range of the random numbers is divided into bucket_count intervals
 // of consecutive numbers. Check that approximately equally many numbers
 // from each inteval are generated.
 void BucketTestFloat(unsigned int bucket_count,
                      unsigned int samples,
                      int sigma_level,
                      Random* prng) {
   ASSERT_GE(bucket_count, 2u);
   std::vector<unsigned int> buckets(bucket_count, 0);

   for (unsigned int i = 0; i < samples; i++) {
     uint32_t sample = bucket_count * prng->Rand<float>();
     EXPECT_LE(0u, sample);
     EXPECT_GE(bucket_count - 1, sample);
     buckets[sample]++;
   }

   for (unsigned int i = 0; i < bucket_count; i++) {
     // Expect the result to be within 3 standard deviations of the mean,
     // or more generally, within sigma_level standard deviations of the mean.
     double mean = static_cast<double>(samples) / bucket_count;
     EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
   }
 }

 TEST(RandomNumberGeneratorTest, UniformFloatInterval) {
   Random prng(1380648813ull);
   BucketTestFloat(100, 100000, 3, &prng);
   // 99.7% of all samples will be within 3 standard deviations of the mean,
   // but since we test 1000 buckets we allow an interval of 4 sigma.
   // BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
 }

 TEST(RandomNumberGeneratorTest, SignedHasSameBitPattern) {
   Random prng_signed(66738480ull), prng_unsigned(66738480ull);

   for (int i = 0; i < 1000; i++) {
     signed int s = prng_signed.Rand<signed int>();
     unsigned int u = prng_unsigned.Rand<unsigned int>();
     EXPECT_EQ(u, static_cast<unsigned int>(s));
   }

   for (int i = 0; i < 1000; i++) {
     int16_t s = prng_signed.Rand<int16_t>();
     uint16_t u = prng_unsigned.Rand<uint16_t>();
     EXPECT_EQ(u, static_cast<uint16_t>(s));
   }

   for (int i = 0; i < 1000; i++) {
     signed char s = prng_signed.Rand<signed char>();
     unsigned char u = prng_unsigned.Rand<unsigned char>();
     EXPECT_EQ(u, static_cast<unsigned char>(s));
   }
 }

 TEST(RandomNumberGeneratorTest, Gaussian) {
   const int kN = 100000;
   const int kBuckets = 100;
   const double kMean = 49;
   const double kStddev = 10;

   Random prng(1256637061);

   std::vector<unsigned int> buckets(kBuckets, 0);
   for (int i = 0; i < kN; i++) {
     int index = prng.Gaussian(kMean, kStddev) + 0.5;
     if (index >= 0 && index < kBuckets) {
       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) {
     // Use Simpsons rule to estimate the probability that a random gaussian
     // 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);
     double f_mid = kScale * exp((n - kMean) * (n - kMean) / kDiv);
     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
     // (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
	/*
	* Copyright (c) 2015 The WebRTC project authors. All Rights Reserved.
	*
	* Use of this source code is governed by a BSD-style license
	* that can be found in the LICENSE file in the root of the source
	* tree. An additional intellectual property rights grant can be found
	* in the file PATENTS. All contributing project authors may
	* be found in the AUTHORS file in the root of the source tree.
	*/

	#include "rtc_base/random.h"

	#include <math.h>

	#include <limits>
	#include <vector>

	#include "rtc_base/numerics/math_utils.h" // unsigned difference
	#include "test/gtest.h"

	namespace webrtc {

	namespace {
	// Computes the positive remainder of x/n.
	template <typename T>
	T fdiv_remainder(T x, T n) {
	RTC_CHECK_GE(n, 0);
	T remainder = x % n;
	if (remainder < 0)
	remainder += n;
	return remainder;
	}
	} // namespace

	// Sample a number of random integers of type T. Divide them into buckets
	// based on the remainder when dividing by bucket_count and check that each
	// bucket gets roughly the expected number of elements.
	template <typename T>
	void UniformBucketTest(T bucket_count, int samples, Random* prng) {
	std::vector<int> buckets(bucket_count, 0);

	uint64_t total_values = 1ull << (std::numeric_limits<T>::digits +
	std::numeric_limits<T>::is_signed);
	T upper_limit =
	std::numeric_limits<T>::max() -
	static_cast<T>(total_values % static_cast<uint64_t>(bucket_count));
	ASSERT_GT(upper_limit, std::numeric_limits<T>::max() / 2);

	for (int i = 0; i < samples; i++) {
	T sample;
	do {
	// We exclude a few numbers from the range so that it is divisible by
	// the number of buckets. If we are unlucky and hit one of the excluded
	// numbers we just resample. Note that if the number of buckets is a
	// power of 2, then we don't have to exclude anything.
	sample = prng->Rand<T>();
	} while (sample > upper_limit);
	buckets[fdiv_remainder(sample, bucket_count)]++;
	}

	for (T i = 0; i < bucket_count; i++) {
	// Expect the result to be within 3 standard deviations of the mean.
	EXPECT_NEAR(buckets[i], samples / bucket_count,
	3 * sqrt(samples / bucket_count));
	}
	}

	TEST(RandomNumberGeneratorTest, BucketTestSignedChar) {
	Random prng(7297352569824ull);
	UniformBucketTest<signed char>(64, 640000, &prng);
	UniformBucketTest<signed char>(11, 440000, &prng);
	UniformBucketTest<signed char>(3, 270000, &prng);
	}

	TEST(RandomNumberGeneratorTest, BucketTestUnsignedChar) {
	Random prng(7297352569824ull);
	UniformBucketTest<unsigned char>(64, 640000, &prng);
	UniformBucketTest<unsigned char>(11, 440000, &prng);
	UniformBucketTest<unsigned char>(3, 270000, &prng);
	}

	TEST(RandomNumberGeneratorTest, BucketTestSignedShort) {
	Random prng(7297352569824ull);
	UniformBucketTest<int16_t>(64, 640000, &prng);
	UniformBucketTest<int16_t>(11, 440000, &prng);
	UniformBucketTest<int16_t>(3, 270000, &prng);
	}

	TEST(RandomNumberGeneratorTest, BucketTestUnsignedShort) {
	Random prng(7297352569824ull);
	UniformBucketTest<uint16_t>(64, 640000, &prng);
	UniformBucketTest<uint16_t>(11, 440000, &prng);
	UniformBucketTest<uint16_t>(3, 270000, &prng);
	}

	TEST(RandomNumberGeneratorTest, BucketTestSignedInt) {
	Random prng(7297352569824ull);
	UniformBucketTest<signed int>(64, 640000, &prng);
	UniformBucketTest<signed int>(11, 440000, &prng);
	UniformBucketTest<signed int>(3, 270000, &prng);
	}

	TEST(RandomNumberGeneratorTest, BucketTestUnsignedInt) {
	Random prng(7297352569824ull);
	UniformBucketTest<unsigned int>(64, 640000, &prng);
	UniformBucketTest<unsigned int>(11, 440000, &prng);
	UniformBucketTest<unsigned int>(3, 270000, &prng);
	}

	// The range of the random numbers is divided into bucket_count intervals
	// of consecutive numbers. Check that approximately equally many numbers
	// from each inteval are generated.
	void BucketTestSignedInterval(unsigned int bucket_count,
	unsigned int samples,
	int32_t low,
	int32_t high,
	int sigma_level,
	Random* prng) {
	std::vector<unsigned int> buckets(bucket_count, 0);

	ASSERT_GE(high, low);
	ASSERT_GE(bucket_count, 2u);
	uint32_t interval = webrtc_impl::unsigned_difference<int32_t>(high, low) + 1;
	uint32_t numbers_per_bucket;
	if (interval == 0) {
	// The computation high - low + 1 should be 2^32 but overflowed
	// Hence, bucket_count must be a power of 2
	ASSERT_EQ(bucket_count & (bucket_count - 1), 0u);
	numbers_per_bucket = (0x80000000u / bucket_count) * 2;
	} else {
	ASSERT_EQ(interval % bucket_count, 0u);
	numbers_per_bucket = interval / bucket_count;
	}

	for (unsigned int i = 0; i < samples; i++) {
	int32_t sample = prng->Rand(low, high);
	EXPECT_LE(low, sample);
	EXPECT_GE(high, sample);
	buckets[webrtc_impl::unsigned_difference<int32_t>(sample, low) /
	numbers_per_bucket]++;
	}

	for (unsigned int i = 0; i < bucket_count; i++) {
	// Expect the result to be within 3 standard deviations of the mean,
	// or more generally, within sigma_level standard deviations of the mean.
	double mean = static_cast<double>(samples) / bucket_count;
	EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
	}
	}

	// The range of the random numbers is divided into bucket_count intervals
	// of consecutive numbers. Check that approximately equally many numbers
	// from each inteval are generated.
	void BucketTestUnsignedInterval(unsigned int bucket_count,
	unsigned int samples,
	uint32_t low,
	uint32_t high,
	int sigma_level,
	Random* prng) {
	std::vector<unsigned int> buckets(bucket_count, 0);

	ASSERT_GE(high, low);
	ASSERT_GE(bucket_count, 2u);
	uint32_t interval = high - low + 1;
	uint32_t numbers_per_bucket;
	if (interval == 0) {
	// The computation high - low + 1 should be 2^32 but overflowed
	// Hence, bucket_count must be a power of 2
	ASSERT_EQ(bucket_count & (bucket_count - 1), 0u);
	numbers_per_bucket = (0x80000000u / bucket_count) * 2;
	} else {
	ASSERT_EQ(interval % bucket_count, 0u);
	numbers_per_bucket = interval / bucket_count;
	}

	for (unsigned int i = 0; i < samples; i++) {
	uint32_t sample = prng->Rand(low, high);
	EXPECT_LE(low, sample);
	EXPECT_GE(high, sample);
	buckets[(sample - low) / numbers_per_bucket]++;
	}

	for (unsigned int i = 0; i < bucket_count; i++) {
	// Expect the result to be within 3 standard deviations of the mean,
	// or more generally, within sigma_level standard deviations of the mean.
	double mean = static_cast<double>(samples) / bucket_count;
	EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
	}
	}

	TEST(RandomNumberGeneratorTest, UniformUnsignedInterval) {
	Random prng(299792458ull);
	BucketTestUnsignedInterval(2, 100000, 0, 1, 3, &prng);
	BucketTestUnsignedInterval(7, 100000, 1, 14, 3, &prng);
	BucketTestUnsignedInterval(11, 100000, 1000, 1010, 3, &prng);
	BucketTestUnsignedInterval(100, 100000, 0, 99, 3, &prng);
	BucketTestUnsignedInterval(2, 100000, 0, 4294967295, 3, &prng);
	BucketTestUnsignedInterval(17, 100000, 455, 2147484110, 3, &prng);
	// 99.7% of all samples will be within 3 standard deviations of the mean,
	// but since we test 1000 buckets we allow an interval of 4 sigma.
	BucketTestUnsignedInterval(1000, 1000000, 0, 2147483999, 4, &prng);
	}

	TEST(RandomNumberGeneratorTest, UniformSignedInterval) {
	Random prng(66260695729ull);
	BucketTestSignedInterval(2, 100000, 0, 1, 3, &prng);
	BucketTestSignedInterval(7, 100000, -2, 4, 3, &prng);
	BucketTestSignedInterval(11, 100000, 1000, 1010, 3, &prng);
	BucketTestSignedInterval(100, 100000, 0, 99, 3, &prng);
	BucketTestSignedInterval(2, 100000, std::numeric_limits<int32_t>::min(),
	std::numeric_limits<int32_t>::max(), 3, &prng);
	BucketTestSignedInterval(17, 100000, -1073741826, 1073741829, 3, &prng);
	// 99.7% of all samples will be within 3 standard deviations of the mean,
	// but since we test 1000 buckets we allow an interval of 4 sigma.
	BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
	}

	// The range of the random numbers is divided into bucket_count intervals
	// of consecutive numbers. Check that approximately equally many numbers
	// from each inteval are generated.
	void BucketTestFloat(unsigned int bucket_count,
	unsigned int samples,
	int sigma_level,
	Random* prng) {
	ASSERT_GE(bucket_count, 2u);
	std::vector<unsigned int> buckets(bucket_count, 0);

	for (unsigned int i = 0; i < samples; i++) {
	uint32_t sample = bucket_count * prng->Rand<float>();
	EXPECT_LE(0u, sample);
	EXPECT_GE(bucket_count - 1, sample);
	buckets[sample]++;
	}

	for (unsigned int i = 0; i < bucket_count; i++) {
	// Expect the result to be within 3 standard deviations of the mean,
	// or more generally, within sigma_level standard deviations of the mean.
	double mean = static_cast<double>(samples) / bucket_count;
	EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
	}
	}

	TEST(RandomNumberGeneratorTest, UniformFloatInterval) {
	Random prng(1380648813ull);
	BucketTestFloat(100, 100000, 3, &prng);
	// 99.7% of all samples will be within 3 standard deviations of the mean,
	// but since we test 1000 buckets we allow an interval of 4 sigma.
	// BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
	}

	TEST(RandomNumberGeneratorTest, SignedHasSameBitPattern) {
	Random prng_signed(66738480ull), prng_unsigned(66738480ull);

	for (int i = 0; i < 1000; i++) {
	signed int s = prng_signed.Rand<signed int>();
	unsigned int u = prng_unsigned.Rand<unsigned int>();
	EXPECT_EQ(u, static_cast<unsigned int>(s));
	}

	for (int i = 0; i < 1000; i++) {
	int16_t s = prng_signed.Rand<int16_t>();
	uint16_t u = prng_unsigned.Rand<uint16_t>();
	EXPECT_EQ(u, static_cast<uint16_t>(s));
	}

	for (int i = 0; i < 1000; i++) {
	signed char s = prng_signed.Rand<signed char>();
	unsigned char u = prng_unsigned.Rand<unsigned char>();
	EXPECT_EQ(u, static_cast<unsigned char>(s));
	}
	}

	TEST(RandomNumberGeneratorTest, Gaussian) {
	const int kN = 100000;
	const int kBuckets = 100;
	const double kMean = 49;
	const double kStddev = 10;

	Random prng(1256637061);

	std::vector<unsigned int> buckets(kBuckets, 0);
	for (int i = 0; i < kN; i++) {
	int index = prng.Gaussian(kMean, kStddev) + 0.5;
	if (index >= 0 && index < kBuckets) {
	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) {
	// Use Simpsons rule to estimate the probability that a random gaussian
	// 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);
	double f_mid = kScale * exp((n - kMean) * (n - kMean) / kDiv);
	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
	// (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