uniform_int_distribution_test.cc (8903B)
1 // Copyright 2017 The Abseil Authors. 2 // 3 // Licensed under the Apache License, Version 2.0 (the "License"); 4 // you may not use this file except in compliance with the License. 5 // You may obtain a copy of the License at 6 // 7 // https://www.apache.org/licenses/LICENSE-2.0 8 // 9 // Unless required by applicable law or agreed to in writing, software 10 // distributed under the License is distributed on an "AS IS" BASIS, 11 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 // See the License for the specific language governing permissions and 13 // limitations under the License. 14 15 #include "absl/random/uniform_int_distribution.h" 16 17 #include <cmath> 18 #include <cstdint> 19 #include <iterator> 20 #include <random> 21 #include <sstream> 22 #include <string> 23 #include <vector> 24 25 #include "gmock/gmock.h" 26 #include "gtest/gtest.h" 27 #include "absl/log/log.h" 28 #include "absl/random/internal/chi_square.h" 29 #include "absl/random/internal/distribution_test_util.h" 30 #include "absl/random/internal/pcg_engine.h" 31 #include "absl/random/internal/sequence_urbg.h" 32 #include "absl/random/random.h" 33 #include "absl/strings/str_cat.h" 34 35 namespace { 36 37 template <typename IntType> 38 class UniformIntDistributionTest : public ::testing::Test {}; 39 40 using IntTypes = ::testing::Types<int8_t, uint8_t, int16_t, uint16_t, int32_t, 41 uint32_t, int64_t, uint64_t>; 42 TYPED_TEST_SUITE(UniformIntDistributionTest, IntTypes); 43 44 TYPED_TEST(UniformIntDistributionTest, ParamSerializeTest) { 45 // This test essentially ensures that the parameters serialize, 46 // not that the values generated cover the full range. 47 using Limits = std::numeric_limits<TypeParam>; 48 using param_type = 49 typename absl::uniform_int_distribution<TypeParam>::param_type; 50 const TypeParam kMin = std::is_unsigned<TypeParam>::value ? 37 : -105; 51 const TypeParam kNegOneOrZero = std::is_unsigned<TypeParam>::value ? 0 : -1; 52 53 constexpr int kCount = 1000; 54 absl::InsecureBitGen gen; 55 for (const auto& param : { 56 param_type(), 57 param_type(2, 2), // Same 58 param_type(9, 32), 59 param_type(kMin, 115), 60 param_type(kNegOneOrZero, Limits::max()), 61 param_type(Limits::min(), Limits::max()), 62 param_type(Limits::lowest(), Limits::max()), 63 param_type(Limits::min() + 1, Limits::max() - 1), 64 }) { 65 const auto a = param.a(); 66 const auto b = param.b(); 67 absl::uniform_int_distribution<TypeParam> before(a, b); 68 EXPECT_EQ(before.a(), param.a()); 69 EXPECT_EQ(before.b(), param.b()); 70 71 { 72 // Initialize via param_type 73 absl::uniform_int_distribution<TypeParam> via_param(param); 74 EXPECT_EQ(via_param, before); 75 } 76 77 // Initialize via iostreams 78 std::stringstream ss; 79 ss << before; 80 81 absl::uniform_int_distribution<TypeParam> after(Limits::min() + 3, 82 Limits::max() - 5); 83 84 EXPECT_NE(before.a(), after.a()); 85 EXPECT_NE(before.b(), after.b()); 86 EXPECT_NE(before.param(), after.param()); 87 EXPECT_NE(before, after); 88 89 ss >> after; 90 91 EXPECT_EQ(before.a(), after.a()); 92 EXPECT_EQ(before.b(), after.b()); 93 EXPECT_EQ(before.param(), after.param()); 94 EXPECT_EQ(before, after); 95 96 // Smoke test. 97 auto sample_min = after.max(); 98 auto sample_max = after.min(); 99 for (int i = 0; i < kCount; i++) { 100 auto sample = after(gen); 101 EXPECT_GE(sample, after.min()); 102 EXPECT_LE(sample, after.max()); 103 if (sample > sample_max) { 104 sample_max = sample; 105 } 106 if (sample < sample_min) { 107 sample_min = sample; 108 } 109 } 110 LOG(INFO) << "Range: " << sample_min << ", " << sample_max; 111 } 112 } 113 114 TYPED_TEST(UniformIntDistributionTest, ViolatesPreconditionsDeathTest) { 115 #if GTEST_HAS_DEATH_TEST 116 // Hi < Lo 117 EXPECT_DEBUG_DEATH( 118 { absl::uniform_int_distribution<TypeParam> dist(10, 1); }, ""); 119 #endif // GTEST_HAS_DEATH_TEST 120 #if defined(NDEBUG) 121 // opt-mode, for invalid parameters, will generate a garbage value, 122 // but should not enter an infinite loop. 123 absl::InsecureBitGen gen; 124 absl::uniform_int_distribution<TypeParam> dist(10, 1); 125 auto x = dist(gen); 126 127 // Any value will generate a non-empty string. 128 EXPECT_FALSE(absl::StrCat(+x).empty()) << x; 129 #endif // NDEBUG 130 } 131 132 TYPED_TEST(UniformIntDistributionTest, TestMoments) { 133 constexpr int kSize = 100000; 134 using Limits = std::numeric_limits<TypeParam>; 135 using param_type = 136 typename absl::uniform_int_distribution<TypeParam>::param_type; 137 138 // We use a fixed bit generator for distribution accuracy tests. This allows 139 // these tests to be deterministic, while still testing the quality of the 140 // implementation. 141 absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6}; 142 143 std::vector<double> values(kSize); 144 for (const auto& param : 145 {param_type(0, Limits::max()), param_type(13, 127)}) { 146 absl::uniform_int_distribution<TypeParam> dist(param); 147 for (int i = 0; i < kSize; i++) { 148 const auto sample = dist(rng); 149 ASSERT_LE(dist.param().a(), sample); 150 ASSERT_GE(dist.param().b(), sample); 151 values[i] = sample; 152 } 153 154 auto moments = absl::random_internal::ComputeDistributionMoments(values); 155 const double a = dist.param().a(); 156 const double b = dist.param().b(); 157 const double n = (b - a + 1); 158 const double mean = (a + b) / 2; 159 const double var = ((b - a + 1) * (b - a + 1) - 1) / 12; 160 const double kurtosis = 3 - 6 * (n * n + 1) / (5 * (n * n - 1)); 161 162 // TODO(ahh): this is not the right bound 163 // empirically validated with --runs_per_test=10000. 164 EXPECT_NEAR(mean, moments.mean, 0.01 * var); 165 EXPECT_NEAR(var, moments.variance, 0.015 * var); 166 EXPECT_NEAR(0.0, moments.skewness, 0.025); 167 EXPECT_NEAR(kurtosis, moments.kurtosis, 0.02 * kurtosis); 168 } 169 } 170 171 TYPED_TEST(UniformIntDistributionTest, ChiSquaredTest50) { 172 using absl::random_internal::kChiSquared; 173 174 constexpr size_t kTrials = 1000; 175 constexpr int kBuckets = 50; // inclusive, so actually +1 176 constexpr double kExpected = 177 static_cast<double>(kTrials) / static_cast<double>(kBuckets); 178 179 // Empirically validated with --runs_per_test=10000. 180 const int kThreshold = 181 absl::random_internal::ChiSquareValue(kBuckets, 0.999999); 182 183 const TypeParam min = std::is_unsigned<TypeParam>::value ? 37 : -37; 184 const TypeParam max = min + kBuckets; 185 186 // We use a fixed bit generator for distribution accuracy tests. This allows 187 // these tests to be deterministic, while still testing the quality of the 188 // implementation. 189 absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6}; 190 191 absl::uniform_int_distribution<TypeParam> dist(min, max); 192 193 std::vector<int32_t> counts(kBuckets + 1, 0); 194 for (size_t i = 0; i < kTrials; i++) { 195 auto x = dist(rng); 196 counts[x - min]++; 197 } 198 double chi_square = absl::random_internal::ChiSquareWithExpected( 199 std::begin(counts), std::end(counts), kExpected); 200 if (chi_square > kThreshold) { 201 double p_value = 202 absl::random_internal::ChiSquarePValue(chi_square, kBuckets); 203 204 // Chi-squared test failed. Output does not appear to be uniform. 205 std::string msg; 206 for (const auto& a : counts) { 207 absl::StrAppend(&msg, a, "\n"); 208 } 209 absl::StrAppend(&msg, kChiSquared, " p-value ", p_value, "\n"); 210 absl::StrAppend(&msg, "High ", kChiSquared, " value: ", chi_square, " > ", 211 kThreshold); 212 LOG(INFO) << msg; 213 FAIL() << msg; 214 } 215 } 216 217 TEST(UniformIntDistributionTest, StabilityTest) { 218 // absl::uniform_int_distribution stability relies only on integer operations. 219 absl::random_internal::sequence_urbg urbg( 220 {0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull, 221 0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull, 222 0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull, 223 0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull}); 224 225 std::vector<int> output(12); 226 227 { 228 absl::uniform_int_distribution<int32_t> dist(0, 4); 229 for (auto& v : output) { 230 v = dist(urbg); 231 } 232 } 233 EXPECT_EQ(12, urbg.invocations()); 234 EXPECT_THAT(output, testing::ElementsAre(4, 4, 3, 2, 1, 0, 1, 4, 3, 1, 3, 1)); 235 236 { 237 urbg.reset(); 238 absl::uniform_int_distribution<int32_t> dist(0, 100); 239 for (auto& v : output) { 240 v = dist(urbg); 241 } 242 } 243 EXPECT_EQ(12, urbg.invocations()); 244 EXPECT_THAT(output, testing::ElementsAre(97, 86, 75, 41, 36, 16, 38, 92, 67, 245 30, 80, 38)); 246 247 { 248 urbg.reset(); 249 absl::uniform_int_distribution<int32_t> dist(0, 10000); 250 for (auto& v : output) { 251 v = dist(urbg); 252 } 253 } 254 EXPECT_EQ(12, urbg.invocations()); 255 EXPECT_THAT(output, testing::ElementsAre(9648, 8562, 7439, 4089, 3571, 1602, 256 3813, 9195, 6641, 2986, 7956, 3765)); 257 } 258 259 } // namespace