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// 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 #include #include #include #include #include "absl/base/config.h" #include "absl/meta/type_traits.h" #include "absl/random/internal/fast_uniform_bits.h" #include "absl/random/internal/generate_real.h" #include "absl/random/internal/iostream_state_saver.h" namespace absl { ABSL_NAMESPACE_BEGIN // absl::exponential_distribution: // Generates a number conforming to an exponential distribution and is // equivalent to the standard [rand.dist.pois.exp] distribution. template 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::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 result_type operator()(URBG& g) { // NOLINT(runtime/references) return (*this)(g, param_); } template 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::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 fast_u64_; }; // -------------------------------------------------------------------------- // Implementation details follow // -------------------------------------------------------------------------- template template typename exponential_distribution::result_type exponential_distribution::operator()( URBG& g, // NOLINT(runtime/references) const param_type& p) { using random_internal::GenerateNegativeTag; using random_internal::GenerateRealFromBits; using real_type = absl::conditional_t::value, float, double>; const result_type u = GenerateRealFromBits(fast_u64_(g)); // U(-1, 0) // 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 std::basic_ostream& operator<<( std::basic_ostream& os, // NOLINT(runtime/references) const exponential_distribution& x) { auto saver = random_internal::make_ostream_state_saver(os); os.precision(random_internal::stream_precision_helper::kPrecision); os << x.lambda(); return os; } template std::basic_istream& operator>>( std::basic_istream& is, // NOLINT(runtime/references) exponential_distribution& x) { // NOLINT(runtime/references) using result_type = typename exponential_distribution::result_type; using param_type = typename exponential_distribution::param_type; result_type lambda; auto saver = random_internal::make_istream_state_saver(is); lambda = random_internal::read_floating_point(is); if (!is.fail()) { x.param(param_type(lambda)); } return is; } ABSL_NAMESPACE_END } // namespace absl #endif // ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_