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Diffstat (limited to 'third_party/abseil_cpp/absl/random/uniform_real_distribution_test.cc')
| -rw-r--r-- | third_party/abseil_cpp/absl/random/uniform_real_distribution_test.cc | 343 |
1 files changed, 0 insertions, 343 deletions
diff --git a/third_party/abseil_cpp/absl/random/uniform_real_distribution_test.cc b/third_party/abseil_cpp/absl/random/uniform_real_distribution_test.cc deleted file mode 100644 index be107cdde4..0000000000 --- a/third_party/abseil_cpp/absl/random/uniform_real_distribution_test.cc +++ /dev/null @@ -1,343 +0,0 @@ -// 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_real_distribution.h" - -#include <cmath> -#include <cstdint> -#include <iterator> -#include <random> -#include <sstream> -#include <string> -#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/pcg_engine.h" -#include "absl/random/internal/sequence_urbg.h" -#include "absl/random/random.h" -#include "absl/strings/str_cat.h" - -// NOTES: -// * Some documentation on generating random real values suggests that -// it is possible to use std::nextafter(b, DBL_MAX) to generate a value on -// the closed range [a, b]. Unfortunately, that technique is not universally -// reliable due to floating point quantization. -// -// * absl::uniform_real_distribution<float> generates between 2^28 and 2^29 -// distinct floating point values in the range [0, 1). -// -// * absl::uniform_real_distribution<float> generates at least 2^23 distinct -// floating point values in the range [1, 2). This should be the same as -// any other range covered by a single exponent in IEEE 754. -// -// * absl::uniform_real_distribution<double> generates more than 2^52 distinct -// values in the range [0, 1), and should generate at least 2^52 distinct -// values in the range of [1, 2). -// - -namespace { - -template <typename RealType> -class UniformRealDistributionTest : public ::testing::Test {}; - -#if defined(__EMSCRIPTEN__) -using RealTypes = ::testing::Types<float, double>; -#else -using RealTypes = ::testing::Types<float, double, long double>; -#endif // defined(__EMSCRIPTEN__) - -TYPED_TEST_SUITE(UniformRealDistributionTest, RealTypes); - -TYPED_TEST(UniformRealDistributionTest, ParamSerializeTest) { - using param_type = - typename absl::uniform_real_distribution<TypeParam>::param_type; - - constexpr const TypeParam a{1152921504606846976}; - - constexpr int kCount = 1000; - absl::InsecureBitGen gen; - for (const auto& param : { - param_type(), - param_type(TypeParam(2.0), TypeParam(2.0)), // Same - param_type(TypeParam(-0.1), TypeParam(0.1)), - param_type(TypeParam(0.05), TypeParam(0.12)), - param_type(TypeParam(-0.05), TypeParam(0.13)), - param_type(TypeParam(-0.05), TypeParam(-0.02)), - // double range = 0 - // 2^60 , 2^60 + 2^6 - param_type(a, TypeParam(1152921504606847040)), - // 2^60 , 2^60 + 2^7 - param_type(a, TypeParam(1152921504606847104)), - // double range = 2^8 - // 2^60 , 2^60 + 2^8 - param_type(a, TypeParam(1152921504606847232)), - // float range = 0 - // 2^60 , 2^60 + 2^36 - param_type(a, TypeParam(1152921573326323712)), - // 2^60 , 2^60 + 2^37 - param_type(a, TypeParam(1152921642045800448)), - // float range = 2^38 - // 2^60 , 2^60 + 2^38 - param_type(a, TypeParam(1152921779484753920)), - // Limits - param_type(0, std::numeric_limits<TypeParam>::max()), - param_type(std::numeric_limits<TypeParam>::lowest(), 0), - param_type(0, std::numeric_limits<TypeParam>::epsilon()), - param_type(-std::numeric_limits<TypeParam>::epsilon(), - std::numeric_limits<TypeParam>::epsilon()), - param_type(std::numeric_limits<TypeParam>::epsilon(), - 2 * std::numeric_limits<TypeParam>::epsilon()), - }) { - // Validate parameters. - const auto a = param.a(); - const auto b = param.b(); - absl::uniform_real_distribution<TypeParam> before(a, b); - EXPECT_EQ(before.a(), param.a()); - EXPECT_EQ(before.b(), param.b()); - - { - absl::uniform_real_distribution<TypeParam> via_param(param); - EXPECT_EQ(via_param, before); - } - - std::stringstream ss; - ss << before; - absl::uniform_real_distribution<TypeParam> after(TypeParam(1.0), - TypeParam(3.1)); - - 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); - // Failure here indicates a bug in uniform_real_distribution::operator(), - // or bad parameters--range too large, etc. - if (after.min() == after.max()) { - EXPECT_EQ(sample, after.min()); - } else { - EXPECT_GE(sample, after.min()); - EXPECT_LT(sample, after.max()); - } - if (sample > sample_max) { - sample_max = sample; - } - if (sample < sample_min) { - sample_min = sample; - } - } - - if (!std::is_same<TypeParam, long double>::value) { - // static_cast<double>(long double) can overflow. - std::string msg = absl::StrCat("Range: ", static_cast<double>(sample_min), - ", ", static_cast<double>(sample_max)); - ABSL_RAW_LOG(INFO, "%s", msg.c_str()); - } - } -} - -#ifdef _MSC_VER -#pragma warning(push) -#pragma warning(disable:4756) // Constant arithmetic overflow. -#endif -TYPED_TEST(UniformRealDistributionTest, ViolatesPreconditionsDeathTest) { -#if GTEST_HAS_DEATH_TEST - // Hi < Lo - EXPECT_DEBUG_DEATH( - { absl::uniform_real_distribution<TypeParam> dist(10.0, 1.0); }, ""); - - // Hi - Lo > numeric_limits<>::max() - EXPECT_DEBUG_DEATH( - { - absl::uniform_real_distribution<TypeParam> dist( - std::numeric_limits<TypeParam>::lowest(), - std::numeric_limits<TypeParam>::max()); - }, - ""); -#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_real_distribution<TypeParam> dist(10.0, 1.0); - auto x = dist(gen); - EXPECT_FALSE(std::isnan(x)) << x; - } - { - absl::uniform_real_distribution<TypeParam> dist( - std::numeric_limits<TypeParam>::lowest(), - std::numeric_limits<TypeParam>::max()); - auto x = dist(gen); - // Infinite result. - EXPECT_FALSE(std::isfinite(x)) << x; - } -#endif // NDEBUG -} -#ifdef _MSC_VER -#pragma warning(pop) // warning(disable:4756) -#endif - -TYPED_TEST(UniformRealDistributionTest, TestMoments) { - constexpr int kSize = 1000000; - std::vector<double> values(kSize); - - // We use a fixed bit generator for distribution accuracy tests. This allows - // these tests to be deterministic, while still testing the qualify of the - // implementation. - absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6}; - - absl::uniform_real_distribution<TypeParam> dist; - for (int i = 0; i < kSize; i++) { - values[i] = dist(rng); - } - - const auto moments = - absl::random_internal::ComputeDistributionMoments(values); - EXPECT_NEAR(0.5, moments.mean, 0.01); - EXPECT_NEAR(1 / 12.0, moments.variance, 0.015); - EXPECT_NEAR(0.0, moments.skewness, 0.02); - EXPECT_NEAR(9 / 5.0, moments.kurtosis, 0.015); -} - -TYPED_TEST(UniformRealDistributionTest, ChiSquaredTest50) { - using absl::random_internal::kChiSquared; - using param_type = - typename absl::uniform_real_distribution<TypeParam>::param_type; - - constexpr size_t kTrials = 100000; - constexpr int kBuckets = 50; - constexpr double kExpected = - static_cast<double>(kTrials) / static_cast<double>(kBuckets); - - // 1-in-100000 threshold, but remember, there are about 8 tests - // in this file. And the test could fail for other reasons. - // Empirically validated with --runs_per_test=10000. - const int kThreshold = - absl::random_internal::ChiSquareValue(kBuckets - 1, 0.999999); - - // We use a fixed bit generator for distribution accuracy tests. This allows - // these tests to be deterministic, while still testing the qualify of the - // implementation. - absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6}; - - for (const auto& param : {param_type(0, 1), param_type(5, 12), - param_type(-5, 13), param_type(-5, -2)}) { - const double min_val = param.a(); - const double max_val = param.b(); - const double factor = kBuckets / (max_val - min_val); - - std::vector<int32_t> counts(kBuckets, 0); - absl::uniform_real_distribution<TypeParam> dist(param); - for (size_t i = 0; i < kTrials; i++) { - auto x = dist(rng); - auto bucket = static_cast<size_t>((x - min_val) * factor); - counts[bucket]++; - } - - 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; - } - } -} - -TYPED_TEST(UniformRealDistributionTest, StabilityTest) { - // absl::uniform_real_distribution stability relies only on - // random_internal::RandU64ToDouble and random_internal::RandU64ToFloat. - 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_real_distribution<TypeParam> dist; - std::generate(std::begin(output), std::end(output), [&] { - return static_cast<int>(TypeParam(1000000) * dist(urbg)); - }); - - EXPECT_THAT( - output, // - testing::ElementsAre(59, 999246, 762494, 395876, 167716, 82545, 925251, - 77341, 12527, 708791, 834451, 932808)); -} - -TEST(UniformRealDistributionTest, AlgorithmBounds) { - absl::uniform_real_distribution<double> dist; - - { - // This returns the smallest value >0 from absl::uniform_real_distribution. - absl::random_internal::sequence_urbg urbg({0x0000000000000001ull}); - double a = dist(urbg); - EXPECT_EQ(a, 5.42101086242752217004e-20); - } - - { - // This returns a value very near 0.5 from absl::uniform_real_distribution. - absl::random_internal::sequence_urbg urbg({0x7fffffffffffffefull}); - double a = dist(urbg); - EXPECT_EQ(a, 0.499999999999999944489); - } - { - // This returns a value very near 0.5 from absl::uniform_real_distribution. - absl::random_internal::sequence_urbg urbg({0x8000000000000000ull}); - double a = dist(urbg); - EXPECT_EQ(a, 0.5); - } - - { - // This returns the largest value <1 from absl::uniform_real_distribution. - absl::random_internal::sequence_urbg urbg({0xFFFFFFFFFFFFFFEFull}); - double a = dist(urbg); - EXPECT_EQ(a, 0.999999999999999888978); - } - { - // This *ALSO* returns the largest value <1. - absl::random_internal::sequence_urbg urbg({0xFFFFFFFFFFFFFFFFull}); - double a = dist(urbg); - EXPECT_EQ(a, 0.999999999999999888978); - } -} - -} // namespace |