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terelius84e78f92015-12-10 01:50:55 -08001/*
2 * Copyright (c) 2015 The WebRTC project authors. All Rights Reserved.
3 *
4 * Use of this source code is governed by a BSD-style license
5 * that can be found in the LICENSE file in the root of the source
6 * tree. An additional intellectual property rights grant can be found
7 * in the file PATENTS. All contributing project authors may
8 * be found in the AUTHORS file in the root of the source tree.
9 */
10
11#include <math.h>
12
13#include <limits>
14#include <vector>
15
Karl Wiberg65c39222017-11-22 12:25:14 +010016#include "rtc_base/numerics/mathutils.h" // unsigned difference
Mirko Bonadei92ea95e2017-09-15 06:47:31 +020017#include "rtc_base/random.h"
18#include "test/gtest.h"
terelius84e78f92015-12-10 01:50:55 -080019
20namespace webrtc {
21
22namespace {
23// Computes the positive remainder of x/n.
24template <typename T>
25T fdiv_remainder(T x, T n) {
kwiberg352444f2016-11-28 15:58:53 -080026 RTC_CHECK_GE(n, 0);
terelius84e78f92015-12-10 01:50:55 -080027 T remainder = x % n;
28 if (remainder < 0)
29 remainder += n;
30 return remainder;
31}
32} // namespace
33
34// Sample a number of random integers of type T. Divide them into buckets
35// based on the remainder when dividing by bucket_count and check that each
36// bucket gets roughly the expected number of elements.
37template <typename T>
38void UniformBucketTest(T bucket_count, int samples, Random* prng) {
39 std::vector<int> buckets(bucket_count, 0);
40
41 uint64_t total_values = 1ull << (std::numeric_limits<T>::digits +
42 std::numeric_limits<T>::is_signed);
43 T upper_limit =
44 std::numeric_limits<T>::max() -
45 static_cast<T>(total_values % static_cast<uint64_t>(bucket_count));
46 ASSERT_GT(upper_limit, std::numeric_limits<T>::max() / 2);
47
48 for (int i = 0; i < samples; i++) {
49 T sample;
50 do {
51 // We exclude a few numbers from the range so that it is divisible by
52 // the number of buckets. If we are unlucky and hit one of the excluded
53 // numbers we just resample. Note that if the number of buckets is a
54 // power of 2, then we don't have to exclude anything.
55 sample = prng->Rand<T>();
56 } while (sample > upper_limit);
57 buckets[fdiv_remainder(sample, bucket_count)]++;
58 }
59
60 for (T i = 0; i < bucket_count; i++) {
61 // Expect the result to be within 3 standard deviations of the mean.
62 EXPECT_NEAR(buckets[i], samples / bucket_count,
63 3 * sqrt(samples / bucket_count));
64 }
65}
66
67TEST(RandomNumberGeneratorTest, BucketTestSignedChar) {
68 Random prng(7297352569824ull);
69 UniformBucketTest<signed char>(64, 640000, &prng);
70 UniformBucketTest<signed char>(11, 440000, &prng);
71 UniformBucketTest<signed char>(3, 270000, &prng);
72}
73
74TEST(RandomNumberGeneratorTest, BucketTestUnsignedChar) {
75 Random prng(7297352569824ull);
76 UniformBucketTest<unsigned char>(64, 640000, &prng);
77 UniformBucketTest<unsigned char>(11, 440000, &prng);
78 UniformBucketTest<unsigned char>(3, 270000, &prng);
79}
80
81TEST(RandomNumberGeneratorTest, BucketTestSignedShort) {
82 Random prng(7297352569824ull);
83 UniformBucketTest<int16_t>(64, 640000, &prng);
84 UniformBucketTest<int16_t>(11, 440000, &prng);
85 UniformBucketTest<int16_t>(3, 270000, &prng);
86}
87
88TEST(RandomNumberGeneratorTest, BucketTestUnsignedShort) {
89 Random prng(7297352569824ull);
90 UniformBucketTest<uint16_t>(64, 640000, &prng);
91 UniformBucketTest<uint16_t>(11, 440000, &prng);
92 UniformBucketTest<uint16_t>(3, 270000, &prng);
93}
94
95TEST(RandomNumberGeneratorTest, BucketTestSignedInt) {
96 Random prng(7297352569824ull);
97 UniformBucketTest<signed int>(64, 640000, &prng);
98 UniformBucketTest<signed int>(11, 440000, &prng);
99 UniformBucketTest<signed int>(3, 270000, &prng);
100}
101
102TEST(RandomNumberGeneratorTest, BucketTestUnsignedInt) {
103 Random prng(7297352569824ull);
104 UniformBucketTest<unsigned int>(64, 640000, &prng);
105 UniformBucketTest<unsigned int>(11, 440000, &prng);
106 UniformBucketTest<unsigned int>(3, 270000, &prng);
107}
108
109// The range of the random numbers is divided into bucket_count intervals
110// of consecutive numbers. Check that approximately equally many numbers
111// from each inteval are generated.
112void BucketTestSignedInterval(unsigned int bucket_count,
113 unsigned int samples,
114 int32_t low,
115 int32_t high,
116 int sigma_level,
117 Random* prng) {
118 std::vector<unsigned int> buckets(bucket_count, 0);
119
120 ASSERT_GE(high, low);
121 ASSERT_GE(bucket_count, 2u);
tereliusd802b5b2016-03-01 11:07:34 -0800122 uint32_t interval = unsigned_difference<int32_t>(high, low) + 1;
terelius84e78f92015-12-10 01:50:55 -0800123 uint32_t numbers_per_bucket;
124 if (interval == 0) {
125 // The computation high - low + 1 should be 2^32 but overflowed
126 // Hence, bucket_count must be a power of 2
127 ASSERT_EQ(bucket_count & (bucket_count - 1), 0u);
128 numbers_per_bucket = (0x80000000u / bucket_count) * 2;
129 } else {
130 ASSERT_EQ(interval % bucket_count, 0u);
131 numbers_per_bucket = interval / bucket_count;
132 }
133
134 for (unsigned int i = 0; i < samples; i++) {
135 int32_t sample = prng->Rand(low, high);
136 EXPECT_LE(low, sample);
137 EXPECT_GE(high, sample);
tereliusd802b5b2016-03-01 11:07:34 -0800138 buckets[unsigned_difference<int32_t>(sample, low) / numbers_per_bucket]++;
terelius84e78f92015-12-10 01:50:55 -0800139 }
140
141 for (unsigned int i = 0; i < bucket_count; i++) {
142 // Expect the result to be within 3 standard deviations of the mean,
143 // or more generally, within sigma_level standard deviations of the mean.
144 double mean = static_cast<double>(samples) / bucket_count;
145 EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
146 }
147}
148
149// The range of the random numbers is divided into bucket_count intervals
150// of consecutive numbers. Check that approximately equally many numbers
151// from each inteval are generated.
152void BucketTestUnsignedInterval(unsigned int bucket_count,
153 unsigned int samples,
154 uint32_t low,
155 uint32_t high,
156 int sigma_level,
157 Random* prng) {
158 std::vector<unsigned int> buckets(bucket_count, 0);
159
160 ASSERT_GE(high, low);
161 ASSERT_GE(bucket_count, 2u);
tereliusd802b5b2016-03-01 11:07:34 -0800162 uint32_t interval = high - low + 1;
terelius84e78f92015-12-10 01:50:55 -0800163 uint32_t numbers_per_bucket;
164 if (interval == 0) {
165 // The computation high - low + 1 should be 2^32 but overflowed
166 // Hence, bucket_count must be a power of 2
167 ASSERT_EQ(bucket_count & (bucket_count - 1), 0u);
168 numbers_per_bucket = (0x80000000u / bucket_count) * 2;
169 } else {
170 ASSERT_EQ(interval % bucket_count, 0u);
171 numbers_per_bucket = interval / bucket_count;
172 }
173
174 for (unsigned int i = 0; i < samples; i++) {
175 uint32_t sample = prng->Rand(low, high);
176 EXPECT_LE(low, sample);
177 EXPECT_GE(high, sample);
tereliusd802b5b2016-03-01 11:07:34 -0800178 buckets[(sample - low) / numbers_per_bucket]++;
terelius84e78f92015-12-10 01:50:55 -0800179 }
180
181 for (unsigned int i = 0; i < bucket_count; i++) {
182 // Expect the result to be within 3 standard deviations of the mean,
183 // or more generally, within sigma_level standard deviations of the mean.
184 double mean = static_cast<double>(samples) / bucket_count;
185 EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
186 }
187}
188
189TEST(RandomNumberGeneratorTest, UniformUnsignedInterval) {
190 Random prng(299792458ull);
191 BucketTestUnsignedInterval(2, 100000, 0, 1, 3, &prng);
192 BucketTestUnsignedInterval(7, 100000, 1, 14, 3, &prng);
193 BucketTestUnsignedInterval(11, 100000, 1000, 1010, 3, &prng);
194 BucketTestUnsignedInterval(100, 100000, 0, 99, 3, &prng);
195 BucketTestUnsignedInterval(2, 100000, 0, 4294967295, 3, &prng);
196 BucketTestUnsignedInterval(17, 100000, 455, 2147484110, 3, &prng);
197 // 99.7% of all samples will be within 3 standard deviations of the mean,
198 // but since we test 1000 buckets we allow an interval of 4 sigma.
199 BucketTestUnsignedInterval(1000, 1000000, 0, 2147483999, 4, &prng);
200}
201
oprypin8ad0e582017-09-05 03:00:37 -0700202TEST(RandomNumberGeneratorTest, UniformSignedInterval) {
terelius84e78f92015-12-10 01:50:55 -0800203 Random prng(66260695729ull);
204 BucketTestSignedInterval(2, 100000, 0, 1, 3, &prng);
205 BucketTestSignedInterval(7, 100000, -2, 4, 3, &prng);
206 BucketTestSignedInterval(11, 100000, 1000, 1010, 3, &prng);
207 BucketTestSignedInterval(100, 100000, 0, 99, 3, &prng);
208 BucketTestSignedInterval(2, 100000, std::numeric_limits<int32_t>::min(),
209 std::numeric_limits<int32_t>::max(), 3, &prng);
210 BucketTestSignedInterval(17, 100000, -1073741826, 1073741829, 3, &prng);
211 // 99.7% of all samples will be within 3 standard deviations of the mean,
212 // but since we test 1000 buckets we allow an interval of 4 sigma.
213 BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
214}
215
216// The range of the random numbers is divided into bucket_count intervals
217// of consecutive numbers. Check that approximately equally many numbers
218// from each inteval are generated.
219void BucketTestFloat(unsigned int bucket_count,
220 unsigned int samples,
221 int sigma_level,
222 Random* prng) {
223 ASSERT_GE(bucket_count, 2u);
224 std::vector<unsigned int> buckets(bucket_count, 0);
225
226 for (unsigned int i = 0; i < samples; i++) {
227 uint32_t sample = bucket_count * prng->Rand<float>();
228 EXPECT_LE(0u, sample);
229 EXPECT_GE(bucket_count - 1, sample);
230 buckets[sample]++;
231 }
232
233 for (unsigned int i = 0; i < bucket_count; i++) {
234 // Expect the result to be within 3 standard deviations of the mean,
235 // or more generally, within sigma_level standard deviations of the mean.
236 double mean = static_cast<double>(samples) / bucket_count;
237 EXPECT_NEAR(buckets[i], mean, sigma_level * sqrt(mean));
238 }
239}
240
241TEST(RandomNumberGeneratorTest, UniformFloatInterval) {
242 Random prng(1380648813ull);
243 BucketTestFloat(100, 100000, 3, &prng);
244 // 99.7% of all samples will be within 3 standard deviations of the mean,
245 // but since we test 1000 buckets we allow an interval of 4 sigma.
246 // BucketTestSignedInterval(1000, 1000000, -352, 2147483647, 4, &prng);
247}
248
249TEST(RandomNumberGeneratorTest, SignedHasSameBitPattern) {
250 Random prng_signed(66738480ull), prng_unsigned(66738480ull);
251
252 for (int i = 0; i < 1000; i++) {
253 signed int s = prng_signed.Rand<signed int>();
254 unsigned int u = prng_unsigned.Rand<unsigned int>();
255 EXPECT_EQ(u, static_cast<unsigned int>(s));
256 }
257
258 for (int i = 0; i < 1000; i++) {
259 int16_t s = prng_signed.Rand<int16_t>();
260 uint16_t u = prng_unsigned.Rand<uint16_t>();
261 EXPECT_EQ(u, static_cast<uint16_t>(s));
262 }
263
264 for (int i = 0; i < 1000; i++) {
265 signed char s = prng_signed.Rand<signed char>();
266 unsigned char u = prng_unsigned.Rand<unsigned char>();
267 EXPECT_EQ(u, static_cast<unsigned char>(s));
268 }
269}
270
271TEST(RandomNumberGeneratorTest, Gaussian) {
272 const int kN = 100000;
273 const int kBuckets = 100;
274 const double kMean = 49;
275 const double kStddev = 10;
276
277 Random prng(1256637061);
278
279 std::vector<unsigned int> buckets(kBuckets, 0);
280 for (int i = 0; i < kN; i++) {
281 int index = prng.Gaussian(kMean, kStddev) + 0.5;
282 if (index >= 0 && index < kBuckets) {
283 buckets[index]++;
284 }
285 }
286
287 const double kPi = 3.14159265358979323846;
288 const double kScale = 1 / (kStddev * sqrt(2.0 * kPi));
289 const double kDiv = -2.0 * kStddev * kStddev;
290 for (int n = 0; n < kBuckets; ++n) {
291 // Use Simpsons rule to estimate the probability that a random gaussian
292 // sample is in the interval [n-0.5, n+0.5].
293 double f_left = kScale * exp((n - kMean - 0.5) * (n - kMean - 0.5) / kDiv);
294 double f_mid = kScale * exp((n - kMean) * (n - kMean) / kDiv);
295 double f_right = kScale * exp((n - kMean + 0.5) * (n - kMean + 0.5) / kDiv);
296 double normal_dist = (f_left + 4 * f_mid + f_right) / 6;
297 // Expect the number of samples to be within 3 standard deviations
298 // (rounded up) of the expected number of samples in the bucket.
299 EXPECT_NEAR(buckets[n], kN * normal_dist, 3 * sqrt(kN * normal_dist) + 1);
300 }
301}
302
303} // namespace webrtc