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Diffstat (limited to 'absl/random/uniform_int_distribution_test.cc')
| -rw-r--r-- | absl/random/uniform_int_distribution_test.cc | 250 |
1 files changed, 250 insertions, 0 deletions
diff --git a/absl/random/uniform_int_distribution_test.cc b/absl/random/uniform_int_distribution_test.cc new file mode 100644 index 00000000..aacff88d --- /dev/null +++ b/absl/random/uniform_int_distribution_test.cc @@ -0,0 +1,250 @@ +// Copyright 2017 The Abseil Authors. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "absl/random/uniform_int_distribution.h" + +#include <cmath> +#include <cstdint> +#include <iterator> +#include <random> +#include <sstream> +#include <vector> + +#include "gmock/gmock.h" +#include "gtest/gtest.h" +#include "absl/base/internal/raw_logging.h" +#include "absl/random/internal/chi_square.h" +#include "absl/random/internal/distribution_test_util.h" +#include "absl/random/internal/sequence_urbg.h" +#include "absl/random/random.h" +#include "absl/strings/str_cat.h" + +namespace { + +template <typename IntType> +class UniformIntDistributionTest : public ::testing::Test {}; + +using IntTypes = ::testing::Types<int8_t, uint8_t, int16_t, uint16_t, int32_t, + uint32_t, int64_t, uint64_t>; +TYPED_TEST_SUITE(UniformIntDistributionTest, IntTypes); + +TYPED_TEST(UniformIntDistributionTest, ParamSerializeTest) { + // This test essentially ensures that the parameters serialize, + // not that the values generated cover the full range. + using Limits = std::numeric_limits<TypeParam>; + using param_type = + typename absl::uniform_int_distribution<TypeParam>::param_type; + const TypeParam kMin = std::is_unsigned<TypeParam>::value ? 37 : -105; + const TypeParam kNegOneOrZero = std::is_unsigned<TypeParam>::value ? 0 : -1; + + constexpr int kCount = 1000; + absl::InsecureBitGen gen; + for (const auto& param : { + param_type(), + param_type(2, 2), // Same + param_type(9, 32), + param_type(kMin, 115), + param_type(kNegOneOrZero, Limits::max()), + param_type(Limits::min(), Limits::max()), + param_type(Limits::lowest(), Limits::max()), + param_type(Limits::min() + 1, Limits::max() - 1), + }) { + const auto a = param.a(); + const auto b = param.b(); + absl::uniform_int_distribution<TypeParam> before(a, b); + EXPECT_EQ(before.a(), param.a()); + EXPECT_EQ(before.b(), param.b()); + + { + // Initialize via param_type + absl::uniform_int_distribution<TypeParam> via_param(param); + EXPECT_EQ(via_param, before); + } + + // Initialize via iostreams + std::stringstream ss; + ss << before; + + absl::uniform_int_distribution<TypeParam> after(Limits::min() + 3, + Limits::max() - 5); + + EXPECT_NE(before.a(), after.a()); + EXPECT_NE(before.b(), after.b()); + EXPECT_NE(before.param(), after.param()); + EXPECT_NE(before, after); + + ss >> after; + + EXPECT_EQ(before.a(), after.a()); + EXPECT_EQ(before.b(), after.b()); + EXPECT_EQ(before.param(), after.param()); + EXPECT_EQ(before, after); + + // Smoke test. + auto sample_min = after.max(); + auto sample_max = after.min(); + for (int i = 0; i < kCount; i++) { + auto sample = after(gen); + EXPECT_GE(sample, after.min()); + EXPECT_LE(sample, after.max()); + if (sample > sample_max) { + sample_max = sample; + } + if (sample < sample_min) { + sample_min = sample; + } + } + std::string msg = absl::StrCat("Range: ", +sample_min, ", ", +sample_max); + ABSL_RAW_LOG(INFO, "%s", msg.c_str()); + } +} + +TYPED_TEST(UniformIntDistributionTest, ViolatesPreconditionsDeathTest) { +#if GTEST_HAS_DEATH_TEST + // Hi < Lo + EXPECT_DEBUG_DEATH({ absl::uniform_int_distribution<TypeParam> dist(10, 1); }, + ""); +#endif // GTEST_HAS_DEATH_TEST +#if defined(NDEBUG) + // opt-mode, for invalid parameters, will generate a garbage value, + // but should not enter an infinite loop. + absl::InsecureBitGen gen; + absl::uniform_int_distribution<TypeParam> dist(10, 1); + auto x = dist(gen); + + // Any value will generate a non-empty std::string. + EXPECT_FALSE(absl::StrCat(+x).empty()) << x; +#endif // NDEBUG +} + +TYPED_TEST(UniformIntDistributionTest, TestMoments) { + constexpr int kSize = 100000; + using Limits = std::numeric_limits<TypeParam>; + using param_type = + typename absl::uniform_int_distribution<TypeParam>::param_type; + + absl::InsecureBitGen rng; + std::vector<double> values(kSize); + for (const auto& param : + {param_type(0, Limits::max()), param_type(13, 127)}) { + absl::uniform_int_distribution<TypeParam> dist(param); + for (int i = 0; i < kSize; i++) { + const auto sample = dist(rng); + ASSERT_LE(dist.param().a(), sample); + ASSERT_GE(dist.param().b(), sample); + values[i] = sample; + } + + auto moments = absl::random_internal::ComputeDistributionMoments(values); + const double a = dist.param().a(); + const double b = dist.param().b(); + const double n = (b - a + 1); + const double mean = (a + b) / 2; + const double var = ((b - a + 1) * (b - a + 1) - 1) / 12; + const double kurtosis = 3 - 6 * (n * n + 1) / (5 * (n * n - 1)); + + // TODO(ahh): this is not the right bound + // empirically validated with --runs_per_test=10000. + EXPECT_NEAR(mean, moments.mean, 0.01 * var); + EXPECT_NEAR(var, moments.variance, 0.015 * var); + EXPECT_NEAR(0.0, moments.skewness, 0.025); + EXPECT_NEAR(kurtosis, moments.kurtosis, 0.02 * kurtosis); + } +} + +TYPED_TEST(UniformIntDistributionTest, ChiSquaredTest50) { + using absl::random_internal::kChiSquared; + + constexpr size_t kTrials = 1000; + constexpr int kBuckets = 50; // inclusive, so actally +1 + constexpr double kExpected = + static_cast<double>(kTrials) / static_cast<double>(kBuckets); + + // Empirically validated with --runs_per_test=10000. + const int kThreshold = + absl::random_internal::ChiSquareValue(kBuckets, 0.999999); + + const TypeParam min = std::is_unsigned<TypeParam>::value ? 37 : -37; + const TypeParam max = min + kBuckets; + + absl::InsecureBitGen rng; + absl::uniform_int_distribution<TypeParam> dist(min, max); + + std::vector<int32_t> counts(kBuckets + 1, 0); + for (size_t i = 0; i < kTrials; i++) { + auto x = dist(rng); + counts[x - min]++; + } + double chi_square = absl::random_internal::ChiSquareWithExpected( + std::begin(counts), std::end(counts), kExpected); + if (chi_square > kThreshold) { + double p_value = + absl::random_internal::ChiSquarePValue(chi_square, kBuckets); + + // Chi-squared test failed. Output does not appear to be uniform. + std::string msg; + for (const auto& a : counts) { + absl::StrAppend(&msg, a, "\n"); + } + absl::StrAppend(&msg, kChiSquared, " p-value ", p_value, "\n"); + absl::StrAppend(&msg, "High ", kChiSquared, " value: ", chi_square, " > ", + kThreshold); + ABSL_RAW_LOG(INFO, "%s", msg.c_str()); + FAIL() << msg; + } +} + +TEST(UniformIntDistributionTest, StabilityTest) { + // absl::uniform_int_distribution stability relies only on integer operations. + absl::random_internal::sequence_urbg urbg( + {0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull, + 0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull, + 0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull, + 0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull}); + + std::vector<int> output(12); + + { + absl::uniform_int_distribution<int32_t> dist(0, 4); + for (auto& v : output) { + v = dist(urbg); + } + } + EXPECT_EQ(12, urbg.invocations()); + EXPECT_THAT(output, testing::ElementsAre(4, 4, 3, 2, 1, 0, 1, 4, 3, 1, 3, 1)); + + { + urbg.reset(); + absl::uniform_int_distribution<int32_t> dist(0, 100); + for (auto& v : output) { + v = dist(urbg); + } + } + EXPECT_EQ(12, urbg.invocations()); + EXPECT_THAT(output, testing::ElementsAre(97, 86, 75, 41, 36, 16, 38, 92, 67, + 30, 80, 38)); + + { + urbg.reset(); + absl::uniform_int_distribution<int32_t> dist(0, 10000); + for (auto& v : output) { + v = dist(urbg); + } + } + EXPECT_EQ(12, urbg.invocations()); + EXPECT_THAT(output, testing::ElementsAre(9648, 8562, 7439, 4089, 3571, 1602, + 3813, 9195, 6641, 2986, 7956, 3765)); +} + +} // namespace |