| // 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/distributions.h" |
| |
| #include <cfloat> |
| #include <cmath> |
| #include <cstdint> |
| #include <limits> |
| #include <type_traits> |
| #include <utility> |
| #include <vector> |
| |
| #include "gtest/gtest.h" |
| #include "absl/meta/type_traits.h" |
| #include "absl/numeric/int128.h" |
| #include "absl/random/internal/distribution_test_util.h" |
| #include "absl/random/random.h" |
| |
| namespace { |
| |
| constexpr int kSize = 400000; |
| |
| class RandomDistributionsTest : public testing::Test {}; |
| |
| struct Invalid {}; |
| |
| template <typename A, typename B> |
| auto InferredUniformReturnT(int) |
| -> decltype(absl::Uniform(std::declval<absl::InsecureBitGen&>(), |
| std::declval<A>(), std::declval<B>())); |
| |
| template <typename, typename> |
| Invalid InferredUniformReturnT(...); |
| |
| template <typename TagType, typename A, typename B> |
| auto InferredTaggedUniformReturnT(int) |
| -> decltype(absl::Uniform(std::declval<TagType>(), |
| std::declval<absl::InsecureBitGen&>(), |
| std::declval<A>(), std::declval<B>())); |
| |
| template <typename, typename, typename> |
| Invalid InferredTaggedUniformReturnT(...); |
| |
| // Given types <A, B, Expect>, CheckArgsInferType() verifies that |
| // |
| // absl::Uniform(gen, A{}, B{}) |
| // |
| // returns the type "Expect". |
| // |
| // This interface can also be used to assert that a given absl::Uniform() |
| // overload does not exist / will not compile. Given types <A, B>, the |
| // expression |
| // |
| // decltype(absl::Uniform(..., std::declval<A>(), std::declval<B>())) |
| // |
| // will not compile, leaving the definition of InferredUniformReturnT<A, B> to |
| // resolve (via SFINAE) to the overload which returns type "Invalid". This |
| // allows tests to assert that an invocation such as |
| // |
| // absl::Uniform(gen, 1.23f, std::numeric_limits<int>::max() - 1) |
| // |
| // should not compile, since neither type, float nor int, can precisely |
| // represent both endpoint-values. Writing: |
| // |
| // CheckArgsInferType<float, int, Invalid>() |
| // |
| // will assert that this overload does not exist. |
| template <typename A, typename B, typename Expect> |
| void CheckArgsInferType() { |
| static_assert( |
| absl::conjunction< |
| std::is_same<Expect, decltype(InferredUniformReturnT<A, B>(0))>, |
| std::is_same<Expect, |
| decltype(InferredUniformReturnT<B, A>(0))>>::value, |
| ""); |
| static_assert( |
| absl::conjunction< |
| std::is_same<Expect, decltype(InferredTaggedUniformReturnT< |
| absl::IntervalOpenOpenTag, A, B>(0))>, |
| std::is_same<Expect, |
| decltype(InferredTaggedUniformReturnT< |
| absl::IntervalOpenOpenTag, B, A>(0))>>::value, |
| ""); |
| } |
| |
| template <typename A, typename B, typename ExplicitRet> |
| auto ExplicitUniformReturnT(int) -> decltype(absl::Uniform<ExplicitRet>( |
| std::declval<absl::InsecureBitGen&>(), std::declval<A>(), |
| std::declval<B>())); |
| |
| template <typename, typename, typename ExplicitRet> |
| Invalid ExplicitUniformReturnT(...); |
| |
| template <typename TagType, typename A, typename B, typename ExplicitRet> |
| auto ExplicitTaggedUniformReturnT(int) -> decltype(absl::Uniform<ExplicitRet>( |
| std::declval<TagType>(), std::declval<absl::InsecureBitGen&>(), |
| std::declval<A>(), std::declval<B>())); |
| |
| template <typename, typename, typename, typename ExplicitRet> |
| Invalid ExplicitTaggedUniformReturnT(...); |
| |
| // Given types <A, B, Expect>, CheckArgsReturnExpectedType() verifies that |
| // |
| // absl::Uniform<Expect>(gen, A{}, B{}) |
| // |
| // returns the type "Expect", and that the function-overload has the signature |
| // |
| // Expect(URBG&, Expect, Expect) |
| template <typename A, typename B, typename Expect> |
| void CheckArgsReturnExpectedType() { |
| static_assert( |
| absl::conjunction< |
| std::is_same<Expect, |
| decltype(ExplicitUniformReturnT<A, B, Expect>(0))>, |
| std::is_same<Expect, decltype(ExplicitUniformReturnT<B, A, Expect>( |
| 0))>>::value, |
| ""); |
| static_assert( |
| absl::conjunction< |
| std::is_same<Expect, |
| decltype(ExplicitTaggedUniformReturnT< |
| absl::IntervalOpenOpenTag, A, B, Expect>(0))>, |
| std::is_same<Expect, decltype(ExplicitTaggedUniformReturnT< |
| absl::IntervalOpenOpenTag, B, A, |
| Expect>(0))>>::value, |
| ""); |
| } |
| |
| // Takes the type of `absl::Uniform<R>(gen)` if valid or `Invalid` otherwise. |
| template <typename R> |
| auto UniformNoBoundsReturnT(int) |
| -> decltype(absl::Uniform<R>(std::declval<absl::InsecureBitGen&>())); |
| |
| template <typename> |
| Invalid UniformNoBoundsReturnT(...); |
| |
| TEST_F(RandomDistributionsTest, UniformTypeInference) { |
| // Infers common types. |
| CheckArgsInferType<uint16_t, uint16_t, uint16_t>(); |
| CheckArgsInferType<uint32_t, uint32_t, uint32_t>(); |
| CheckArgsInferType<uint64_t, uint64_t, uint64_t>(); |
| CheckArgsInferType<int16_t, int16_t, int16_t>(); |
| CheckArgsInferType<int32_t, int32_t, int32_t>(); |
| CheckArgsInferType<int64_t, int64_t, int64_t>(); |
| CheckArgsInferType<float, float, float>(); |
| CheckArgsInferType<double, double, double>(); |
| |
| // Explicitly-specified return-values override inferences. |
| CheckArgsReturnExpectedType<int16_t, int16_t, int32_t>(); |
| CheckArgsReturnExpectedType<uint16_t, uint16_t, int32_t>(); |
| CheckArgsReturnExpectedType<int16_t, int16_t, int64_t>(); |
| CheckArgsReturnExpectedType<int16_t, int32_t, int64_t>(); |
| CheckArgsReturnExpectedType<int16_t, int32_t, double>(); |
| CheckArgsReturnExpectedType<float, float, double>(); |
| CheckArgsReturnExpectedType<int, int, int16_t>(); |
| |
| // Properly promotes uint16_t. |
| CheckArgsInferType<uint16_t, uint32_t, uint32_t>(); |
| CheckArgsInferType<uint16_t, uint64_t, uint64_t>(); |
| CheckArgsInferType<uint16_t, int32_t, int32_t>(); |
| CheckArgsInferType<uint16_t, int64_t, int64_t>(); |
| CheckArgsInferType<uint16_t, float, float>(); |
| CheckArgsInferType<uint16_t, double, double>(); |
| |
| // Properly promotes int16_t. |
| CheckArgsInferType<int16_t, int32_t, int32_t>(); |
| CheckArgsInferType<int16_t, int64_t, int64_t>(); |
| CheckArgsInferType<int16_t, float, float>(); |
| CheckArgsInferType<int16_t, double, double>(); |
| |
| // Invalid (u)int16_t-pairings do not compile. |
| // See "CheckArgsInferType" comments above, for how this is achieved. |
| CheckArgsInferType<uint16_t, int16_t, Invalid>(); |
| CheckArgsInferType<int16_t, uint32_t, Invalid>(); |
| CheckArgsInferType<int16_t, uint64_t, Invalid>(); |
| |
| // Properly promotes uint32_t. |
| CheckArgsInferType<uint32_t, uint64_t, uint64_t>(); |
| CheckArgsInferType<uint32_t, int64_t, int64_t>(); |
| CheckArgsInferType<uint32_t, double, double>(); |
| |
| // Properly promotes int32_t. |
| CheckArgsInferType<int32_t, int64_t, int64_t>(); |
| CheckArgsInferType<int32_t, double, double>(); |
| |
| // Invalid (u)int32_t-pairings do not compile. |
| CheckArgsInferType<uint32_t, int32_t, Invalid>(); |
| CheckArgsInferType<int32_t, uint64_t, Invalid>(); |
| CheckArgsInferType<int32_t, float, Invalid>(); |
| CheckArgsInferType<uint32_t, float, Invalid>(); |
| |
| // Invalid (u)int64_t-pairings do not compile. |
| CheckArgsInferType<uint64_t, int64_t, Invalid>(); |
| CheckArgsInferType<int64_t, float, Invalid>(); |
| CheckArgsInferType<int64_t, double, Invalid>(); |
| |
| // Properly promotes float. |
| CheckArgsInferType<float, double, double>(); |
| } |
| |
| TEST_F(RandomDistributionsTest, UniformExamples) { |
| // Examples. |
| absl::InsecureBitGen gen; |
| EXPECT_NE(1, absl::Uniform(gen, static_cast<uint16_t>(0), 1.0f)); |
| EXPECT_NE(1, absl::Uniform(gen, 0, 1.0)); |
| EXPECT_NE(1, absl::Uniform(absl::IntervalOpenOpen, gen, |
| static_cast<uint16_t>(0), 1.0f)); |
| EXPECT_NE(1, absl::Uniform(absl::IntervalOpenOpen, gen, 0, 1.0)); |
| EXPECT_NE(1, absl::Uniform(absl::IntervalOpenOpen, gen, -1, 1.0)); |
| EXPECT_NE(1, absl::Uniform<double>(absl::IntervalOpenOpen, gen, -1, 1)); |
| EXPECT_NE(1, absl::Uniform<float>(absl::IntervalOpenOpen, gen, 0, 1)); |
| EXPECT_NE(1, absl::Uniform<float>(gen, 0, 1)); |
| } |
| |
| TEST_F(RandomDistributionsTest, UniformNoBounds) { |
| absl::InsecureBitGen gen; |
| |
| absl::Uniform<uint8_t>(gen); |
| absl::Uniform<uint16_t>(gen); |
| absl::Uniform<uint32_t>(gen); |
| absl::Uniform<uint64_t>(gen); |
| absl::Uniform<absl::uint128>(gen); |
| |
| // Compile-time validity tests. |
| |
| // Allows unsigned ints. |
| testing::StaticAssertTypeEq<uint8_t, |
| decltype(UniformNoBoundsReturnT<uint8_t>(0))>(); |
| testing::StaticAssertTypeEq<uint16_t, |
| decltype(UniformNoBoundsReturnT<uint16_t>(0))>(); |
| testing::StaticAssertTypeEq<uint32_t, |
| decltype(UniformNoBoundsReturnT<uint32_t>(0))>(); |
| testing::StaticAssertTypeEq<uint64_t, |
| decltype(UniformNoBoundsReturnT<uint64_t>(0))>(); |
| testing::StaticAssertTypeEq< |
| absl::uint128, decltype(UniformNoBoundsReturnT<absl::uint128>(0))>(); |
| |
| // Disallows signed ints. |
| testing::StaticAssertTypeEq<Invalid, |
| decltype(UniformNoBoundsReturnT<int8_t>(0))>(); |
| testing::StaticAssertTypeEq<Invalid, |
| decltype(UniformNoBoundsReturnT<int16_t>(0))>(); |
| testing::StaticAssertTypeEq<Invalid, |
| decltype(UniformNoBoundsReturnT<int32_t>(0))>(); |
| testing::StaticAssertTypeEq<Invalid, |
| decltype(UniformNoBoundsReturnT<int64_t>(0))>(); |
| testing::StaticAssertTypeEq< |
| Invalid, decltype(UniformNoBoundsReturnT<absl::int128>(0))>(); |
| |
| // Disallows float types. |
| testing::StaticAssertTypeEq<Invalid, |
| decltype(UniformNoBoundsReturnT<float>(0))>(); |
| testing::StaticAssertTypeEq<Invalid, |
| decltype(UniformNoBoundsReturnT<double>(0))>(); |
| } |
| |
| TEST_F(RandomDistributionsTest, UniformNonsenseRanges) { |
| // The ranges used in this test are undefined behavior. |
| // The results are arbitrary and subject to future changes. |
| |
| #if (defined(__i386__) || defined(_M_IX86)) && FLT_EVAL_METHOD != 0 |
| // We're using an x87-compatible FPU, and intermediate operations can be |
| // performed with 80-bit floats. This produces slightly different results from |
| // what we expect below. |
| GTEST_SKIP() |
| << "Skipping the test because we detected x87 floating-point semantics"; |
| #endif |
| |
| absl::InsecureBitGen gen; |
| |
| // <uint> |
| EXPECT_EQ(0, absl::Uniform<uint64_t>(gen, 0, 0)); |
| EXPECT_EQ(1, absl::Uniform<uint64_t>(gen, 1, 0)); |
| EXPECT_EQ(0, absl::Uniform<uint64_t>(absl::IntervalOpenOpen, gen, 0, 0)); |
| EXPECT_EQ(1, absl::Uniform<uint64_t>(absl::IntervalOpenOpen, gen, 1, 0)); |
| |
| constexpr auto m = (std::numeric_limits<uint64_t>::max)(); |
| |
| EXPECT_EQ(m, absl::Uniform(gen, m, m)); |
| EXPECT_EQ(m, absl::Uniform(gen, m, m - 1)); |
| EXPECT_EQ(m - 1, absl::Uniform(gen, m - 1, m)); |
| EXPECT_EQ(m, absl::Uniform(absl::IntervalOpenOpen, gen, m, m)); |
| EXPECT_EQ(m, absl::Uniform(absl::IntervalOpenOpen, gen, m, m - 1)); |
| EXPECT_EQ(m - 1, absl::Uniform(absl::IntervalOpenOpen, gen, m - 1, m)); |
| |
| // <int> |
| EXPECT_EQ(0, absl::Uniform<int64_t>(gen, 0, 0)); |
| EXPECT_EQ(1, absl::Uniform<int64_t>(gen, 1, 0)); |
| EXPECT_EQ(0, absl::Uniform<int64_t>(absl::IntervalOpenOpen, gen, 0, 0)); |
| EXPECT_EQ(1, absl::Uniform<int64_t>(absl::IntervalOpenOpen, gen, 1, 0)); |
| |
| constexpr auto l = (std::numeric_limits<int64_t>::min)(); |
| constexpr auto r = (std::numeric_limits<int64_t>::max)(); |
| |
| EXPECT_EQ(l, absl::Uniform(gen, l, l)); |
| EXPECT_EQ(r, absl::Uniform(gen, r, r)); |
| EXPECT_EQ(r, absl::Uniform(gen, r, r - 1)); |
| EXPECT_EQ(r - 1, absl::Uniform(gen, r - 1, r)); |
| EXPECT_EQ(l, absl::Uniform(absl::IntervalOpenOpen, gen, l, l)); |
| EXPECT_EQ(r, absl::Uniform(absl::IntervalOpenOpen, gen, r, r)); |
| EXPECT_EQ(r, absl::Uniform(absl::IntervalOpenOpen, gen, r, r - 1)); |
| EXPECT_EQ(r - 1, absl::Uniform(absl::IntervalOpenOpen, gen, r - 1, r)); |
| |
| // <double> |
| const double e = std::nextafter(1.0, 2.0); // 1 + epsilon |
| const double f = std::nextafter(1.0, 0.0); // 1 - epsilon |
| const double g = std::numeric_limits<double>::denorm_min(); |
| |
| EXPECT_EQ(1.0, absl::Uniform(gen, 1.0, e)); |
| EXPECT_EQ(1.0, absl::Uniform(gen, 1.0, f)); |
| EXPECT_EQ(0.0, absl::Uniform(gen, 0.0, g)); |
| |
| EXPECT_EQ(e, absl::Uniform(absl::IntervalOpenOpen, gen, 1.0, e)); |
| EXPECT_EQ(f, absl::Uniform(absl::IntervalOpenOpen, gen, 1.0, f)); |
| EXPECT_EQ(g, absl::Uniform(absl::IntervalOpenOpen, gen, 0.0, g)); |
| } |
| |
| // TODO(lar): Validate properties of non-default interval-semantics. |
| TEST_F(RandomDistributionsTest, UniformReal) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Uniform(gen, 0, 1.0); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(0.5, moments.mean, 0.02); |
| EXPECT_NEAR(1 / 12.0, moments.variance, 0.02); |
| EXPECT_NEAR(0.0, moments.skewness, 0.02); |
| EXPECT_NEAR(9 / 5.0, moments.kurtosis, 0.02); |
| } |
| |
| TEST_F(RandomDistributionsTest, UniformInt) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| const int64_t kMax = 1000000000000ll; |
| int64_t j = absl::Uniform(absl::IntervalClosedClosed, gen, 0, kMax); |
| // convert to double. |
| values[i] = static_cast<double>(j) / static_cast<double>(kMax); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(0.5, moments.mean, 0.02); |
| EXPECT_NEAR(1 / 12.0, moments.variance, 0.02); |
| EXPECT_NEAR(0.0, moments.skewness, 0.02); |
| EXPECT_NEAR(9 / 5.0, moments.kurtosis, 0.02); |
| |
| /* |
| // NOTE: These are not supported by absl::Uniform, which is specialized |
| // on integer and real valued types. |
| |
| enum E { E0, E1 }; // enum |
| enum S : int { S0, S1 }; // signed enum |
| enum U : unsigned int { U0, U1 }; // unsigned enum |
| |
| absl::Uniform(gen, E0, E1); |
| absl::Uniform(gen, S0, S1); |
| absl::Uniform(gen, U0, U1); |
| */ |
| } |
| |
| TEST_F(RandomDistributionsTest, Exponential) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Exponential<double>(gen); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(1.0, moments.mean, 0.02); |
| EXPECT_NEAR(1.0, moments.variance, 0.025); |
| EXPECT_NEAR(2.0, moments.skewness, 0.1); |
| EXPECT_LT(5.0, moments.kurtosis); |
| } |
| |
| TEST_F(RandomDistributionsTest, PoissonDefault) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Poisson<int64_t>(gen); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(1.0, moments.mean, 0.02); |
| EXPECT_NEAR(1.0, moments.variance, 0.02); |
| EXPECT_NEAR(1.0, moments.skewness, 0.025); |
| EXPECT_LT(2.0, moments.kurtosis); |
| } |
| |
| TEST_F(RandomDistributionsTest, PoissonLarge) { |
| constexpr double kMean = 100000000.0; |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Poisson<int64_t>(gen, kMean); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(kMean, moments.mean, kMean * 0.015); |
| EXPECT_NEAR(kMean, moments.variance, kMean * 0.015); |
| EXPECT_NEAR(std::sqrt(kMean), moments.skewness, kMean * 0.02); |
| EXPECT_LT(2.0, moments.kurtosis); |
| } |
| |
| TEST_F(RandomDistributionsTest, Bernoulli) { |
| constexpr double kP = 0.5151515151; |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Bernoulli(gen, kP); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(kP, moments.mean, 0.01); |
| } |
| |
| TEST_F(RandomDistributionsTest, Beta) { |
| constexpr double kAlpha = 2.0; |
| constexpr double kBeta = 3.0; |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Beta(gen, kAlpha, kBeta); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(0.4, moments.mean, 0.01); |
| } |
| |
| TEST_F(RandomDistributionsTest, Zipf) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Zipf<int64_t>(gen, 100); |
| } |
| |
| // The mean of a zipf distribution is: H(N, s-1) / H(N,s). |
| // Given the parameter v = 1, this gives the following function: |
| // (Hn(100, 1) - Hn(1,1)) / (Hn(100,2) - Hn(1,2)) = 6.5944 |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(6.5944, moments.mean, 2000) << moments; |
| } |
| |
| TEST_F(RandomDistributionsTest, ZipfWithZeroMax) { |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < 100; ++i) { |
| EXPECT_EQ(0, absl::Zipf(gen, 0)); |
| } |
| } |
| |
| TEST_F(RandomDistributionsTest, Gaussian) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::Gaussian<double>(gen); |
| } |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(0.0, moments.mean, 0.02); |
| EXPECT_NEAR(1.0, moments.variance, 0.04); |
| EXPECT_NEAR(0, moments.skewness, 0.2); |
| EXPECT_NEAR(3.0, moments.kurtosis, 0.5); |
| } |
| |
| TEST_F(RandomDistributionsTest, LogUniform) { |
| std::vector<double> values(kSize); |
| |
| absl::InsecureBitGen gen; |
| for (int i = 0; i < kSize; i++) { |
| values[i] = absl::LogUniform<int64_t>(gen, 0, (1 << 10) - 1); |
| } |
| |
| // The mean is the sum of the fractional means of the uniform distributions: |
| // [0..0][1..1][2..3][4..7][8..15][16..31][32..63] |
| // [64..127][128..255][256..511][512..1023] |
| const double mean = (0 + 1 + 1 + 2 + 3 + 4 + 7 + 8 + 15 + 16 + 31 + 32 + 63 + |
| 64 + 127 + 128 + 255 + 256 + 511 + 512 + 1023) / |
| (2.0 * 11.0); |
| |
| const auto moments = |
| absl::random_internal::ComputeDistributionMoments(values); |
| EXPECT_NEAR(mean, moments.mean, 2) << moments; |
| } |
| |
| } // namespace |