a877af1f29
-- ea0cfebeb69b25bec343652bbe1a203f5476c51a by Mark Barolak <mbar@google.com>: Change "std::string" to "string" in places where a "std::" qualification was incorrectly inserted by automation. PiperOrigin-RevId: 300108520 GitOrigin-RevId: ea0cfebeb69b25bec343652bbe1a203f5476c51a Change-Id: Ie3621e63a6ebad67b9fe56a3ebe33e1d50dac602
250 lines
8.3 KiB
C++
250 lines
8.3 KiB
C++
// Copyright 2017 The Abseil Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "absl/random/uniform_int_distribution.h"
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#include <cmath>
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#include <cstdint>
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#include <iterator>
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#include <random>
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#include <sstream>
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#include <vector>
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#include "gmock/gmock.h"
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#include "gtest/gtest.h"
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#include "absl/base/internal/raw_logging.h"
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#include "absl/random/internal/chi_square.h"
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#include "absl/random/internal/distribution_test_util.h"
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#include "absl/random/internal/sequence_urbg.h"
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#include "absl/random/random.h"
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#include "absl/strings/str_cat.h"
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namespace {
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template <typename IntType>
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class UniformIntDistributionTest : public ::testing::Test {};
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using IntTypes = ::testing::Types<int8_t, uint8_t, int16_t, uint16_t, int32_t,
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uint32_t, int64_t, uint64_t>;
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TYPED_TEST_SUITE(UniformIntDistributionTest, IntTypes);
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TYPED_TEST(UniformIntDistributionTest, ParamSerializeTest) {
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// This test essentially ensures that the parameters serialize,
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// not that the values generated cover the full range.
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using Limits = std::numeric_limits<TypeParam>;
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using param_type =
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typename absl::uniform_int_distribution<TypeParam>::param_type;
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const TypeParam kMin = std::is_unsigned<TypeParam>::value ? 37 : -105;
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const TypeParam kNegOneOrZero = std::is_unsigned<TypeParam>::value ? 0 : -1;
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constexpr int kCount = 1000;
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absl::InsecureBitGen gen;
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for (const auto& param : {
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param_type(),
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param_type(2, 2), // Same
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param_type(9, 32),
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param_type(kMin, 115),
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param_type(kNegOneOrZero, Limits::max()),
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param_type(Limits::min(), Limits::max()),
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param_type(Limits::lowest(), Limits::max()),
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param_type(Limits::min() + 1, Limits::max() - 1),
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}) {
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const auto a = param.a();
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const auto b = param.b();
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absl::uniform_int_distribution<TypeParam> before(a, b);
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EXPECT_EQ(before.a(), param.a());
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EXPECT_EQ(before.b(), param.b());
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{
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// Initialize via param_type
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absl::uniform_int_distribution<TypeParam> via_param(param);
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EXPECT_EQ(via_param, before);
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}
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// Initialize via iostreams
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std::stringstream ss;
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ss << before;
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absl::uniform_int_distribution<TypeParam> after(Limits::min() + 3,
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Limits::max() - 5);
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EXPECT_NE(before.a(), after.a());
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EXPECT_NE(before.b(), after.b());
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EXPECT_NE(before.param(), after.param());
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EXPECT_NE(before, after);
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ss >> after;
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EXPECT_EQ(before.a(), after.a());
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EXPECT_EQ(before.b(), after.b());
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EXPECT_EQ(before.param(), after.param());
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EXPECT_EQ(before, after);
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// Smoke test.
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auto sample_min = after.max();
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auto sample_max = after.min();
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for (int i = 0; i < kCount; i++) {
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auto sample = after(gen);
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EXPECT_GE(sample, after.min());
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EXPECT_LE(sample, after.max());
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if (sample > sample_max) {
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sample_max = sample;
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}
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if (sample < sample_min) {
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sample_min = sample;
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}
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}
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std::string msg = absl::StrCat("Range: ", +sample_min, ", ", +sample_max);
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ABSL_RAW_LOG(INFO, "%s", msg.c_str());
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}
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}
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TYPED_TEST(UniformIntDistributionTest, ViolatesPreconditionsDeathTest) {
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#if GTEST_HAS_DEATH_TEST
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// Hi < Lo
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EXPECT_DEBUG_DEATH({ absl::uniform_int_distribution<TypeParam> dist(10, 1); },
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"");
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#endif // GTEST_HAS_DEATH_TEST
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#if defined(NDEBUG)
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// opt-mode, for invalid parameters, will generate a garbage value,
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// but should not enter an infinite loop.
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absl::InsecureBitGen gen;
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absl::uniform_int_distribution<TypeParam> dist(10, 1);
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auto x = dist(gen);
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// Any value will generate a non-empty string.
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EXPECT_FALSE(absl::StrCat(+x).empty()) << x;
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#endif // NDEBUG
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}
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TYPED_TEST(UniformIntDistributionTest, TestMoments) {
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constexpr int kSize = 100000;
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using Limits = std::numeric_limits<TypeParam>;
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using param_type =
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typename absl::uniform_int_distribution<TypeParam>::param_type;
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absl::InsecureBitGen rng;
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std::vector<double> values(kSize);
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for (const auto& param :
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{param_type(0, Limits::max()), param_type(13, 127)}) {
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absl::uniform_int_distribution<TypeParam> dist(param);
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for (int i = 0; i < kSize; i++) {
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const auto sample = dist(rng);
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ASSERT_LE(dist.param().a(), sample);
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ASSERT_GE(dist.param().b(), sample);
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values[i] = sample;
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}
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auto moments = absl::random_internal::ComputeDistributionMoments(values);
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const double a = dist.param().a();
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const double b = dist.param().b();
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const double n = (b - a + 1);
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const double mean = (a + b) / 2;
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const double var = ((b - a + 1) * (b - a + 1) - 1) / 12;
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const double kurtosis = 3 - 6 * (n * n + 1) / (5 * (n * n - 1));
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// TODO(ahh): this is not the right bound
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// empirically validated with --runs_per_test=10000.
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EXPECT_NEAR(mean, moments.mean, 0.01 * var);
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EXPECT_NEAR(var, moments.variance, 0.015 * var);
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EXPECT_NEAR(0.0, moments.skewness, 0.025);
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EXPECT_NEAR(kurtosis, moments.kurtosis, 0.02 * kurtosis);
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}
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}
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TYPED_TEST(UniformIntDistributionTest, ChiSquaredTest50) {
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using absl::random_internal::kChiSquared;
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constexpr size_t kTrials = 1000;
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constexpr int kBuckets = 50; // inclusive, so actally +1
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constexpr double kExpected =
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static_cast<double>(kTrials) / static_cast<double>(kBuckets);
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// Empirically validated with --runs_per_test=10000.
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const int kThreshold =
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absl::random_internal::ChiSquareValue(kBuckets, 0.999999);
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const TypeParam min = std::is_unsigned<TypeParam>::value ? 37 : -37;
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const TypeParam max = min + kBuckets;
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absl::InsecureBitGen rng;
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absl::uniform_int_distribution<TypeParam> dist(min, max);
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std::vector<int32_t> counts(kBuckets + 1, 0);
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for (size_t i = 0; i < kTrials; i++) {
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auto x = dist(rng);
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counts[x - min]++;
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}
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double chi_square = absl::random_internal::ChiSquareWithExpected(
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std::begin(counts), std::end(counts), kExpected);
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if (chi_square > kThreshold) {
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double p_value =
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absl::random_internal::ChiSquarePValue(chi_square, kBuckets);
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// Chi-squared test failed. Output does not appear to be uniform.
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std::string msg;
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for (const auto& a : counts) {
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absl::StrAppend(&msg, a, "\n");
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}
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absl::StrAppend(&msg, kChiSquared, " p-value ", p_value, "\n");
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absl::StrAppend(&msg, "High ", kChiSquared, " value: ", chi_square, " > ",
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kThreshold);
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ABSL_RAW_LOG(INFO, "%s", msg.c_str());
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FAIL() << msg;
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}
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}
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TEST(UniformIntDistributionTest, StabilityTest) {
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// absl::uniform_int_distribution stability relies only on integer operations.
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absl::random_internal::sequence_urbg urbg(
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{0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull,
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0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull,
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0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull,
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0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull});
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std::vector<int> output(12);
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{
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absl::uniform_int_distribution<int32_t> dist(0, 4);
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for (auto& v : output) {
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v = dist(urbg);
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}
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}
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EXPECT_EQ(12, urbg.invocations());
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EXPECT_THAT(output, testing::ElementsAre(4, 4, 3, 2, 1, 0, 1, 4, 3, 1, 3, 1));
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{
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urbg.reset();
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absl::uniform_int_distribution<int32_t> dist(0, 100);
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for (auto& v : output) {
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v = dist(urbg);
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}
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}
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EXPECT_EQ(12, urbg.invocations());
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EXPECT_THAT(output, testing::ElementsAre(97, 86, 75, 41, 36, 16, 38, 92, 67,
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30, 80, 38));
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{
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urbg.reset();
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absl::uniform_int_distribution<int32_t> dist(0, 10000);
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for (auto& v : output) {
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v = dist(urbg);
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}
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}
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EXPECT_EQ(12, urbg.invocations());
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EXPECT_THAT(output, testing::ElementsAre(9648, 8562, 7439, 4089, 3571, 1602,
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3813, 9195, 6641, 2986, 7956, 3765));
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}
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} // namespace
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