From e9324d926a9189e222741fce6e676f0944661a72 Mon Sep 17 00:00:00 2001 From: Abseil Team Date: Fri, 21 Jun 2019 13:11:42 -0700 Subject: Export of internal Abseil changes. -- 7a6ff16a85beb730c172d5d25cf1b5e1be885c56 by Laramie Leavitt : Internal change. PiperOrigin-RevId: 254454546 -- ff8f9bafaefc26d451f576ea4a06d150aed63f6f by Andy Soffer : Internal changes PiperOrigin-RevId: 254451562 -- deefc5b651b479ce36f0b4ef203e119c0c8936f2 by CJ Johnson : Account for subtracting unsigned values from the size of InlinedVector PiperOrigin-RevId: 254450625 -- 3c677316a27bcadc17e41957c809ca472d5fef14 by Andy Soffer : Add C++17's std::make_from_tuple to absl/utility/utility.h PiperOrigin-RevId: 254411573 -- 4ee3536a918830eeec402a28fc31a62c7c90b940 by CJ Johnson : Adds benchmark for the rest of the InlinedVector public API PiperOrigin-RevId: 254408378 -- e5a21a00700ee83498ff1efbf649169756463ee4 by CJ Johnson : Updates the definition of InlinedVector::shrink_to_fit() to be exception safe and adds exception safety tests for it. PiperOrigin-RevId: 254401387 -- 2ea82e72b86d82d78b4e4712a63a55981b53c64b by Laramie Leavitt : Use absl::InsecureBitGen in place of std::mt19937 in tests absl/random/...distribution_test.cc PiperOrigin-RevId: 254289444 -- fa099e02c413a7ffda732415e8105cad26a90337 by Andy Soffer : Internal changes PiperOrigin-RevId: 254286334 -- ce34b7f36933b30cfa35b9c9a5697a792b5666e4 by Andy Soffer : Internal changes PiperOrigin-RevId: 254273059 -- 6f9c473da7c2090c2e85a37c5f00622e8a912a89 by Jorg Brown : Change absl::container_internal::CompressedTuple to instantiate its internal Storage class with the name of the type it's holding, rather than the name of the Tuple. This is not an externally-visible change, other than less compiler memory is used and less debug information is generated. PiperOrigin-RevId: 254269285 -- 8bd3c186bf2fc0c55d8a2dd6f28a5327502c9fba by Andy Soffer : Adding short-hand IntervalClosed for IntervalClosedClosed and IntervalOpen for IntervalOpenOpen. PiperOrigin-RevId: 254252419 -- ea957f99b6a04fccd42aa05605605f3b44b1ecfd by Abseil Team : Do not directly use __SIZEOF_INT128__. In order to avoid linker errors when building with clang-cl (__fixunsdfti, __udivti3 and __fixunssfti are undefined), this CL uses ABSL_HAVE_INTRINSIC_INT128 which is not defined for clang-cl. PiperOrigin-RevId: 254250739 -- 89ab385cd26b34d64130bce856253aaba96d2345 by Andy Soffer : Internal changes PiperOrigin-RevId: 254242321 -- cffc793d93eca6d6bdf7de733847b6ab4a255ae9 by CJ Johnson : Adds benchmark for InlinedVector::reserve(size_type) PiperOrigin-RevId: 254199226 -- c90c7a9fa3c8f0c9d5114036979548b055ea2f2a by Gennadiy Rozental : Import of CCTZ from GitHub. PiperOrigin-RevId: 254072387 -- c4c388beae016c9570ab54ffa1d52660e4a85b7b by Laramie Leavitt : Internal cleanup. PiperOrigin-RevId: 254062381 -- d3c992e221cc74e5372d0c8fa410170b6a43c062 by Tom Manshreck : Update distributions.h to Abseil standards PiperOrigin-RevId: 254054946 -- d15ad0035c34ef11b14fadc5a4a2d3ec415f5518 by CJ Johnson : Removes functions with only one caller from the implementation details of InlinedVector by manually inlining the definitions PiperOrigin-RevId: 254005427 -- 2f37e807efc3a8ef1f4b539bdd379917d4151520 by Andy Soffer : Initial release of Abseil Random PiperOrigin-RevId: 253999861 -- 24ed1694b6430791d781ed533a8f8ccf6cac5856 by CJ Johnson : Updates the definition of InlinedVector::assign(...)/InlinedVector::operator=(...) to new, exception-safe implementations with exception safety tests to boot PiperOrigin-RevId: 253993691 -- 5613d95f5a7e34a535cfaeadce801441e990843e by CJ Johnson : Adds benchmarks for InlinedVector::shrink_to_fit() PiperOrigin-RevId: 253989647 -- 2a96ddfdac40bbb8cb6a7f1aeab90917067c6e63 by Abseil Team : Initial release of Abseil Random PiperOrigin-RevId: 253927497 -- bf1aff8fc9ffa921ad74643e9525ecf25b0d8dc1 by Andy Soffer : Initial release of Abseil Random PiperOrigin-RevId: 253920512 -- bfc03f4a3dcda3cf3a4b84bdb84cda24e3394f41 by Laramie Leavitt : Internal change. PiperOrigin-RevId: 253886486 -- 05036cfcc078ca7c5f581a00dfb0daed568cbb69 by Eric Fiselier : Don't include `winsock2.h` because it drags in `windows.h` and friends, and they define awful macros like OPAQUE, ERROR, and more. This has the potential to break abseil users. Instead we only forward declare `timeval` and require Windows users include `winsock2.h` themselves. This is both inconsistent and poor QoI, but so including 'windows.h' is bad too. PiperOrigin-RevId: 253852615 GitOrigin-RevId: 7a6ff16a85beb730c172d5d25cf1b5e1be885c56 Change-Id: Icd6aff87da26f29ec8915da856f051129987cef6 --- absl/random/uniform_real_distribution_test.cc | 322 ++++++++++++++++++++++++++ 1 file changed, 322 insertions(+) create mode 100644 absl/random/uniform_real_distribution_test.cc (limited to 'absl/random/uniform_real_distribution_test.cc') diff --git a/absl/random/uniform_real_distribution_test.cc b/absl/random/uniform_real_distribution_test.cc new file mode 100644 index 00000000..597f0ee5 --- /dev/null +++ b/absl/random/uniform_real_distribution_test.cc @@ -0,0 +1,322 @@ +// 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 +#include +#include +#include +#include +#include +#include + +#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" + +// 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 generates between 2^28 and 2^29 +// distinct floating point values in the range [0, 1). +// +// * absl::uniform_real_distribution 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 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 +class UniformRealDistributionTest : public ::testing::Test {}; + +using RealTypes = ::testing::Types; +TYPED_TEST_SUITE(UniformRealDistributionTest, RealTypes); + +TYPED_TEST(UniformRealDistributionTest, ParamSerializeTest) { + using param_type = + typename absl::uniform_real_distribution::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::max()), + param_type(std::numeric_limits::lowest(), 0), + param_type(0, std::numeric_limits::epsilon()), + param_type(-std::numeric_limits::epsilon(), + std::numeric_limits::epsilon()), + param_type(std::numeric_limits::epsilon(), + 2 * std::numeric_limits::epsilon()), + }) { + // Validate parameters. + const auto a = param.a(); + const auto b = param.b(); + absl::uniform_real_distribution before(a, b); + EXPECT_EQ(before.a(), param.a()); + EXPECT_EQ(before.b(), param.b()); + + { + absl::uniform_real_distribution via_param(param); + EXPECT_EQ(via_param, before); + } + + std::stringstream ss; + ss << before; + absl::uniform_real_distribution 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::value) { + // static_cast(long double) can overflow. + std::string msg = absl::StrCat("Range: ", static_cast(sample_min), + ", ", static_cast(sample_max)); + ABSL_RAW_LOG(INFO, "%s", msg.c_str()); + } + } +} + +TYPED_TEST(UniformRealDistributionTest, ViolatesPreconditionsDeathTest) { +#if GTEST_HAS_DEATH_TEST + // Hi < Lo + EXPECT_DEBUG_DEATH( + { absl::uniform_real_distribution dist(10.0, 1.0); }, ""); + + // Hi - Lo > numeric_limits<>::max() + EXPECT_DEBUG_DEATH( + { + absl::uniform_real_distribution dist( + std::numeric_limits::lowest(), + std::numeric_limits::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 dist(10.0, 1.0); + auto x = dist(gen); + EXPECT_FALSE(std::isnan(x)) << x; + } + { + absl::uniform_real_distribution dist( + std::numeric_limits::lowest(), + std::numeric_limits::max()); + auto x = dist(gen); + // Infinite result. + EXPECT_FALSE(std::isfinite(x)) << x; + } +#endif // NDEBUG +} + +TYPED_TEST(UniformRealDistributionTest, TestMoments) { + constexpr int kSize = 1000000; + std::vector values(kSize); + + absl::InsecureBitGen rng; + absl::uniform_real_distribution 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::param_type; + + constexpr size_t kTrials = 100000; + constexpr int kBuckets = 50; + constexpr double kExpected = + static_cast(kTrials) / static_cast(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); + + absl::InsecureBitGen rng; + 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 counts(kBuckets, 0); + absl::uniform_real_distribution dist(param); + for (size_t i = 0; i < kTrials; i++) { + auto x = dist(rng); + auto bucket = static_cast((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 output(12); + + absl::uniform_real_distribution dist; + std::generate(std::begin(output), std::end(output), [&] { + return static_cast(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 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 -- cgit v1.2.3