502efe6d78
-- 8e04df6fcbd062e5eaf179a6ec9b0a26f8aa8a39 by Abseil Team <absl-team@google.com>: Use a floating point type for the example usage of absl::uniform_real_distribution. PiperOrigin-RevId: 271167776 -- 5f8f1dfea50bc16a9d9af3e50c4636500a938b29 by Abseil Team <absl-team@google.com>: the llvm wasm backend does not support this data symbol in text section, so remove it from the test. PiperOrigin-RevId: 271138100 -- 2874542cb212962ac3093fd78fd5e1eb85c126c0 by Xiaoyi Zhang <zhangxy@google.com>: Work around MSVC 2019 compiler bug related to constexpr in optional_test. The change in optional_test is necessary to avoid another bug on MSVC complaining about accessing invalid member of union, and also makes the test more reasonale by checking the value of a non-static member. Filed a bug against MSVC https://developercommunity.visualstudio.com/content/problem/743998/internal-compiler-error-related-to-constexpr-and-u.html. PiperOrigin-RevId: 271129805 -- 3a5d56f0c3362aabf68938fb95c4e2d3eca59538 by Abseil Team <absl-team@google.com>: Improve precision of absl::GetCurrentTimeNanos() by adjusting cycle time sooner. PiperOrigin-RevId: 271007945 -- 1e044a6dec7c0ca150fff1aee52dbdb16aa43ed7 by Abseil Team <absl-team@google.com>: Internal change. PiperOrigin-RevId: 270962690 GitOrigin-RevId: 8e04df6fcbd062e5eaf179a6ec9b0a26f8aa8a39 Change-Id: Icb05423a7e93ebdae16baadd59a60b75b5cfa249
193 lines
6.9 KiB
C++
193 lines
6.9 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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//
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// -----------------------------------------------------------------------------
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// File: uniform_real_distribution.h
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// -----------------------------------------------------------------------------
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//
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// This header defines a class for representing a uniform floating-point
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// distribution over a half-open interval [a,b). You use this distribution in
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// combination with an Abseil random bit generator to produce random values
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// according to the rules of the distribution.
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//
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// `absl::uniform_real_distribution` is a drop-in replacement for the C++11
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// `std::uniform_real_distribution` [rand.dist.uni.real] but is considerably
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// faster than the libstdc++ implementation.
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//
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// Note: the standard-library version may occasionally return `1.0` when
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// default-initialized. See https://bugs.llvm.org//show_bug.cgi?id=18767
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// `absl::uniform_real_distribution` does not exhibit this behavior.
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#ifndef ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
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#define ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
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#include <cassert>
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#include <cmath>
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#include <cstdint>
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#include <istream>
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#include <limits>
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#include <type_traits>
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#include "absl/random/internal/distribution_impl.h"
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#include "absl/random/internal/fast_uniform_bits.h"
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#include "absl/random/internal/iostream_state_saver.h"
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namespace absl {
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// absl::uniform_real_distribution<T>
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//
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// This distribution produces random floating-point values uniformly distributed
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// over the half-open interval [a, b).
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//
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// Example:
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//
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// absl::BitGen gen;
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//
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// // Use the distribution to produce a value between 0.0 (inclusive)
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// // and 1.0 (exclusive).
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// double value = absl::uniform_real_distribution<double>(0, 1)(gen);
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//
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template <typename RealType = double>
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class uniform_real_distribution {
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public:
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using result_type = RealType;
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class param_type {
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public:
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using distribution_type = uniform_real_distribution;
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explicit param_type(result_type lo = 0, result_type hi = 1)
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: lo_(lo), hi_(hi), range_(hi - lo) {
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// [rand.dist.uni.real] preconditions 2 & 3
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assert(lo <= hi);
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// NOTE: For integral types, we can promote the range to an unsigned type,
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// which gives full width of the range. However for real (fp) types, this
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// is not possible, so value generation cannot use the full range of the
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// real type.
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assert(range_ <= (std::numeric_limits<result_type>::max)());
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}
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result_type a() const { return lo_; }
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result_type b() const { return hi_; }
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friend bool operator==(const param_type& a, const param_type& b) {
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return a.lo_ == b.lo_ && a.hi_ == b.hi_;
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}
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friend bool operator!=(const param_type& a, const param_type& b) {
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return !(a == b);
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}
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private:
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friend class uniform_real_distribution;
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result_type lo_, hi_, range_;
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static_assert(std::is_floating_point<RealType>::value,
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"Class-template absl::uniform_real_distribution<> must be "
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"parameterized using a floating-point type.");
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};
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uniform_real_distribution() : uniform_real_distribution(0) {}
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explicit uniform_real_distribution(result_type lo, result_type hi = 1)
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: param_(lo, hi) {}
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explicit uniform_real_distribution(const param_type& param) : param_(param) {}
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// uniform_real_distribution<T>::reset()
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//
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// Resets the uniform real distribution. Note that this function has no effect
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// because the distribution already produces independent values.
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void reset() {}
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template <typename URBG>
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result_type operator()(URBG& gen) { // NOLINT(runtime/references)
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return operator()(gen, param_);
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}
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template <typename URBG>
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result_type operator()(URBG& gen, // NOLINT(runtime/references)
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const param_type& p);
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result_type a() const { return param_.a(); }
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result_type b() const { return param_.b(); }
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param_type param() const { return param_; }
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void param(const param_type& params) { param_ = params; }
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result_type(min)() const { return a(); }
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result_type(max)() const { return b(); }
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friend bool operator==(const uniform_real_distribution& a,
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const uniform_real_distribution& b) {
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return a.param_ == b.param_;
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}
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friend bool operator!=(const uniform_real_distribution& a,
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const uniform_real_distribution& b) {
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return a.param_ != b.param_;
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}
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private:
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param_type param_;
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random_internal::FastUniformBits<uint64_t> fast_u64_;
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};
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// -----------------------------------------------------------------------------
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// Implementation details follow
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// -----------------------------------------------------------------------------
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template <typename RealType>
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template <typename URBG>
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typename uniform_real_distribution<RealType>::result_type
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uniform_real_distribution<RealType>::operator()(
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URBG& gen, const param_type& p) { // NOLINT(runtime/references)
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using random_internal::PositiveValueT;
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while (true) {
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const result_type sample = random_internal::RandU64ToReal<
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result_type>::template Value<PositiveValueT, true>(fast_u64_(gen));
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const result_type res = p.a() + (sample * p.range_);
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if (res < p.b() || p.range_ <= 0 || !std::isfinite(p.range_)) {
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return res;
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}
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// else sample rejected, try again.
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}
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}
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template <typename CharT, typename Traits, typename RealType>
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std::basic_ostream<CharT, Traits>& operator<<(
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std::basic_ostream<CharT, Traits>& os, // NOLINT(runtime/references)
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const uniform_real_distribution<RealType>& x) {
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auto saver = random_internal::make_ostream_state_saver(os);
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os.precision(random_internal::stream_precision_helper<RealType>::kPrecision);
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os << x.a() << os.fill() << x.b();
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return os;
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}
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template <typename CharT, typename Traits, typename RealType>
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std::basic_istream<CharT, Traits>& operator>>(
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std::basic_istream<CharT, Traits>& is, // NOLINT(runtime/references)
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uniform_real_distribution<RealType>& x) { // NOLINT(runtime/references)
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using param_type = typename uniform_real_distribution<RealType>::param_type;
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using result_type = typename uniform_real_distribution<RealType>::result_type;
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auto saver = random_internal::make_istream_state_saver(is);
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auto a = random_internal::read_floating_point<result_type>(is);
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if (is.fail()) return is;
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auto b = random_internal::read_floating_point<result_type>(is);
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if (!is.fail()) {
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x.param(param_type(a, b));
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}
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return is;
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}
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} // namespace absl
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#endif // ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
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