1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
|
// 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/random/internal/distribution_impl.h"
#include "absl/random/internal/fast_uniform_bits.h"
#include "absl/random/internal/iostream_state_saver.h"
namespace absl {
// 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)());
}
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_type
uniform_real_distribution<RealType>::operator()(
URBG& gen, const param_type& p) { // NOLINT(runtime/references)
using random_internal::PositiveValueT;
while (true) {
const result_type sample = random_internal::RandU64ToReal<
result_type>::template Value<PositiveValueT, 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;
}
} // namespace absl
#endif // ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
|
