//===----------------------------------------------------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // REQUIRES: long_tests // // template // class uniform_int_distribution // template result_type operator()(_URNG& g); #include #include #include #include #include #include #include #include #include #include "test_macros.h" template T sqr(T x) { return x * x; } template void test_statistics(ResultType a, ResultType b) { ASSERT_SAME_TYPE(typename std::uniform_int_distribution::result_type, ResultType); EngineType g; std::uniform_int_distribution dist(a, b); assert(dist.a() == a); assert(dist.b() == b); std::vector u; for (int i = 0; i < 10000; ++i) { ResultType v = dist(g); assert(a <= v && v <= b); u.push_back(v); } // Quick check: The chance of getting *no* hits in any given tenth of the range // is (0.9)^10000, or "ultra-astronomically low." bool bottom_tenth = false; bool top_tenth = false; for (std::size_t i = 0; i < u.size(); ++i) { bottom_tenth = bottom_tenth || (u[i] <= (a + (b / 10) - (a / 10))); top_tenth = top_tenth || (u[i] >= (b - (b / 10) + (a / 10))); } assert(bottom_tenth); // ...is populated assert(top_tenth); // ...is populated // Now do some more involved statistical math. double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); double var = 0; double skew = 0; double kurtosis = 0; for (std::size_t i = 0; i < u.size(); ++i) { double dbl = (u[i] - mean); double d2 = dbl * dbl; var += d2; skew += dbl * d2; kurtosis += d2 * d2; } var /= u.size(); double dev = std::sqrt(var); skew /= u.size() * dev * var; kurtosis /= u.size() * var * var; double expected_mean = double(a) + double(b)/2 - double(a)/2; double expected_var = (sqr(double(b) - double(a) + 1) - 1) / 12; double range = double(b) - double(a) + 1.0; assert(range > range / 10); // i.e., it's not infinity assert(std::abs(mean - expected_mean) < range / 100); assert(std::abs(var - expected_var) < expected_var / 50); assert(-0.1 < skew && skew < 0.1); assert(1.6 < kurtosis && kurtosis < 2.0); } template void test_statistics() { test_statistics(0, std::numeric_limits::max()); } int main(int, char**) { test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(-6, 106); test_statistics(5, 100); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(); test_statistics(SHRT_MIN, SHRT_MAX); #if defined(_LIBCPP_VERSION) // extension test_statistics(); test_statistics(); #if !defined(TEST_HAS_NO_INT128) test_statistics<__int128_t, std::minstd_rand0>(); test_statistics<__uint128_t, std::minstd_rand0>(); test_statistics<__int128_t, std::minstd_rand0>(-100, 900); test_statistics<__int128_t, std::minstd_rand0>(0, UINT64_MAX); test_statistics<__int128_t, std::minstd_rand0>(std::numeric_limits<__int128_t>::min(), std::numeric_limits<__int128_t>::max()); test_statistics<__uint128_t, std::minstd_rand0>(0, UINT64_MAX); #endif #endif return 0; }