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Diffstat (limited to 'absl/random/exponential_distribution.h')
-rw-r--r-- | absl/random/exponential_distribution.h | 159 |
1 files changed, 159 insertions, 0 deletions
diff --git a/absl/random/exponential_distribution.h b/absl/random/exponential_distribution.h new file mode 100644 index 00000000..ed5551ae --- /dev/null +++ b/absl/random/exponential_distribution.h @@ -0,0 +1,159 @@ +// 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. + +#ifndef ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_ +#define ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_ + +#include <cassert> +#include <cmath> +#include <istream> +#include <limits> +#include <type_traits> + +#include "absl/random/internal/distribution_impl.h" +#include "absl/random/internal/fast_uniform_bits.h" +#include "absl/random/internal/iostream_state_saver.h" + +namespace absl { +inline namespace lts_2019_08_08 { + +// absl::exponential_distribution: +// Generates a number conforming to an exponential distribution and is +// equivalent to the standard [rand.dist.pois.exp] distribution. +template <typename RealType = double> +class exponential_distribution { + public: + using result_type = RealType; + + class param_type { + public: + using distribution_type = exponential_distribution; + + explicit param_type(result_type lambda = 1) : lambda_(lambda) { + assert(lambda > 0); + neg_inv_lambda_ = -result_type(1) / lambda_; + } + + result_type lambda() const { return lambda_; } + + friend bool operator==(const param_type& a, const param_type& b) { + return a.lambda_ == b.lambda_; + } + + friend bool operator!=(const param_type& a, const param_type& b) { + return !(a == b); + } + + private: + friend class exponential_distribution; + + result_type lambda_; + result_type neg_inv_lambda_; + + static_assert( + std::is_floating_point<RealType>::value, + "Class-template absl::exponential_distribution<> must be parameterized " + "using a floating-point type."); + }; + + exponential_distribution() : exponential_distribution(1) {} + + explicit exponential_distribution(result_type lambda) : param_(lambda) {} + + explicit exponential_distribution(const param_type& p) : param_(p) {} + + void reset() {} + + // Generating functions + template <typename URBG> + result_type operator()(URBG& g) { // NOLINT(runtime/references) + return (*this)(g, param_); + } + + template <typename URBG> + result_type operator()(URBG& g, // NOLINT(runtime/references) + const param_type& p); + + param_type param() const { return param_; } + void param(const param_type& p) { param_ = p; } + + result_type(min)() const { return 0; } + result_type(max)() const { + return std::numeric_limits<result_type>::infinity(); + } + + result_type lambda() const { return param_.lambda(); } + + friend bool operator==(const exponential_distribution& a, + const exponential_distribution& b) { + return a.param_ == b.param_; + } + friend bool operator!=(const exponential_distribution& a, + const exponential_distribution& b) { + return a.param_ != b.param_; + } + + private: + param_type param_; + random_internal::FastUniformBits<uint64_t> fast_u64_; +}; + +// -------------------------------------------------------------------------- +// Implementation details follow +// -------------------------------------------------------------------------- + +template <typename RealType> +template <typename URBG> +typename exponential_distribution<RealType>::result_type +exponential_distribution<RealType>::operator()( + URBG& g, // NOLINT(runtime/references) + const param_type& p) { + using random_internal::NegativeValueT; + const result_type u = random_internal::RandU64ToReal< + result_type>::template Value<NegativeValueT, false>(fast_u64_(g)); + // log1p(-x) is mathematically equivalent to log(1 - x) but has more + // accuracy for x near zero. + return p.neg_inv_lambda_ * std::log1p(u); +} + +template <typename CharT, typename Traits, typename RealType> +std::basic_ostream<CharT, Traits>& operator<<( + std::basic_ostream<CharT, Traits>& os, // NOLINT(runtime/references) + const exponential_distribution<RealType>& x) { + auto saver = random_internal::make_ostream_state_saver(os); + os.precision(random_internal::stream_precision_helper<RealType>::kPrecision); + os << x.lambda(); + return os; +} + +template <typename CharT, typename Traits, typename RealType> +std::basic_istream<CharT, Traits>& operator>>( + std::basic_istream<CharT, Traits>& is, // NOLINT(runtime/references) + exponential_distribution<RealType>& x) { // NOLINT(runtime/references) + using result_type = typename exponential_distribution<RealType>::result_type; + using param_type = typename exponential_distribution<RealType>::param_type; + result_type lambda; + + auto saver = random_internal::make_istream_state_saver(is); + lambda = random_internal::read_floating_point<result_type>(is); + if (!is.fail()) { + x.param(param_type(lambda)); + } + return is; +} + +} // inline namespace lts_2019_08_08 +} // namespace absl + +#endif // ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_ |