| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202 | // 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.//// -----------------------------------------------------------------------------// File: uniform_real_distribution.h// -----------------------------------------------------------------------------//// This header defines a class for representing a uniform floating-point// distribution over a half-open interval [a,b). You use this distribution in// combination with an Abseil random bit generator to produce random values// according to the rules of the distribution.//// `absl::uniform_real_distribution` is a drop-in replacement for the C++11// `std::uniform_real_distribution` [rand.dist.uni.real] but is considerably// faster than the libstdc++ implementation.//// Note: the standard-library version may occasionally return `1.0` when// default-initialized. See https://bugs.llvm.org//show_bug.cgi?id=18767// `absl::uniform_real_distribution` does not exhibit this behavior.#ifndef ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_#define ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_#include <cassert>#include <cmath>#include <cstdint>#include <istream>#include <limits>#include <type_traits>#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::uniform_real_distribution<T>//// This distribution produces random floating-point values uniformly distributed// over the half-open interval [a, b).//// Example:////   absl::BitGen gen;////   // Use the distribution to produce a value between 0.0 (inclusive)//   // and 1.0 (exclusive).//   double value = absl::uniform_real_distribution<double>(0, 1)(gen);//template <typename RealType = double>class uniform_real_distribution { public:  using result_type = RealType;  class param_type {   public:    using distribution_type = uniform_real_distribution;    explicit param_type(result_type lo = 0, result_type hi = 1)        : lo_(lo), hi_(hi), range_(hi - lo) {      // [rand.dist.uni.real] preconditions 2 & 3      assert(lo <= hi);      // NOTE: For integral types, we can promote the range to an unsigned type,      // which gives full width of the range. However for real (fp) types, this      // is not possible, so value generation cannot use the full range of the      // real type.      assert(range_ <= (std::numeric_limits<result_type>::max)());      assert(std::isfinite(range_));    }    result_type a() const { return lo_; }    result_type b() const { return hi_; }    friend bool operator==(const param_type& a, const param_type& b) {      return a.lo_ == b.lo_ && a.hi_ == b.hi_;    }    friend bool operator!=(const param_type& a, const param_type& b) {      return !(a == b);    }   private:    friend class uniform_real_distribution;    result_type lo_, hi_, range_;    static_assert(std::is_floating_point<RealType>::value,                  "Class-template absl::uniform_real_distribution<> must be "                  "parameterized using a floating-point type.");  };  uniform_real_distribution() : uniform_real_distribution(0) {}  explicit uniform_real_distribution(result_type lo, result_type hi = 1)      : param_(lo, hi) {}  explicit uniform_real_distribution(const param_type& param) : param_(param) {}  // uniform_real_distribution<T>::reset()  //  // Resets the uniform real distribution. Note that this function has no effect  // because the distribution already produces independent values.  void reset() {}  template <typename URBG>  result_type operator()(URBG& gen) {  // NOLINT(runtime/references)    return operator()(gen, param_);  }  template <typename URBG>  result_type operator()(URBG& gen,  // NOLINT(runtime/references)                         const param_type& p);  result_type a() const { return param_.a(); }  result_type b() const { return param_.b(); }  param_type param() const { return param_; }  void param(const param_type& params) { param_ = params; }  result_type(min)() const { return a(); }  result_type(max)() const { return b(); }  friend bool operator==(const uniform_real_distribution& a,                         const uniform_real_distribution& b) {    return a.param_ == b.param_;  }  friend bool operator!=(const uniform_real_distribution& a,                         const uniform_real_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 uniform_real_distribution<RealType>::result_typeuniform_real_distribution<RealType>::operator()(    URBG& gen, const param_type& p) {  // NOLINT(runtime/references)  using random_internal::GeneratePositiveTag;  using random_internal::GenerateRealFromBits;  using real_type =      absl::conditional_t<std::is_same<RealType, float>::value, float, double>;  while (true) {    const result_type sample =        GenerateRealFromBits<real_type, GeneratePositiveTag, true>(            fast_u64_(gen));    const result_type res = p.a() + (sample * p.range_);    if (res < p.b() || p.range_ <= 0 || !std::isfinite(p.range_)) {      return res;    }    // else sample rejected, try again.  }}template <typename CharT, typename Traits, typename RealType>std::basic_ostream<CharT, Traits>& operator<<(    std::basic_ostream<CharT, Traits>& os,  // NOLINT(runtime/references)    const uniform_real_distribution<RealType>& x) {  auto saver = random_internal::make_ostream_state_saver(os);  os.precision(random_internal::stream_precision_helper<RealType>::kPrecision);  os << x.a() << os.fill() << x.b();  return os;}template <typename CharT, typename Traits, typename RealType>std::basic_istream<CharT, Traits>& operator>>(    std::basic_istream<CharT, Traits>& is,     // NOLINT(runtime/references)    uniform_real_distribution<RealType>& x) {  // NOLINT(runtime/references)  using param_type = typename uniform_real_distribution<RealType>::param_type;  using result_type = typename uniform_real_distribution<RealType>::result_type;  auto saver = random_internal::make_istream_state_saver(is);  auto a = random_internal::read_floating_point<result_type>(is);  if (is.fail()) return is;  auto b = random_internal::read_floating_point<result_type>(is);  if (!is.fail()) {    x.param(param_type(a, b));  }  return is;}ABSL_NAMESPACE_END}  // namespace absl#endif  // ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
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