| /* |
| * Copyright (c) 2015 The WebRTC project authors. All Rights Reserved. |
| * |
| * Use of this source code is governed by a BSD-style license |
| * that can be found in the LICENSE file in the root of the source |
| * tree. An additional intellectual property rights grant can be found |
| * in the file PATENTS. All contributing project authors may |
| * be found in the AUTHORS file in the root of the source tree. |
| */ |
| #include "rtc_base/random.h" |
| |
| #include <math.h> |
| |
| #include "rtc_base/checks.h" |
| #include "rtc_base/numerics/safe_conversions.h" |
| |
| namespace webrtc { |
| |
| Random::Random(uint64_t seed) { |
| RTC_DCHECK(seed != 0x0ull); |
| state_ = seed; |
| } |
| |
| uint32_t Random::Rand(uint32_t t) { |
| // Casting the output to 32 bits will give an almost uniform number. |
| // Pr[x=0] = (2^32-1) / (2^64-1) |
| // Pr[x=k] = 2^32 / (2^64-1) for k!=0 |
| // Uniform would be Pr[x=k] = 2^32 / 2^64 for all 32-bit integers k. |
| uint32_t x = NextOutput(); |
| // If x / 2^32 is uniform on [0,1), then x / 2^32 * (t+1) is uniform on |
| // the interval [0,t+1), so the integer part is uniform on [0,t]. |
| uint64_t result = x * (static_cast<uint64_t>(t) + 1); |
| result >>= 32; |
| return result; |
| } |
| |
| uint32_t Random::Rand(uint32_t low, uint32_t high) { |
| RTC_DCHECK(low <= high); |
| return Rand(high - low) + low; |
| } |
| |
| int32_t Random::Rand(int32_t low, int32_t high) { |
| RTC_DCHECK(low <= high); |
| const int64_t low_i64{low}; |
| return rtc::dchecked_cast<int32_t>( |
| Rand(rtc::dchecked_cast<uint32_t>(high - low_i64)) + low_i64); |
| } |
| |
| template <> |
| float Random::Rand<float>() { |
| double result = NextOutput() - 1; |
| result = result / 0xFFFFFFFFFFFFFFFEull; |
| return static_cast<float>(result); |
| } |
| |
| template <> |
| double Random::Rand<double>() { |
| double result = NextOutput() - 1; |
| result = result / 0xFFFFFFFFFFFFFFFEull; |
| return result; |
| } |
| |
| template <> |
| bool Random::Rand<bool>() { |
| return Rand(0, 1) == 1; |
| } |
| |
| double Random::Gaussian(double mean, double standard_deviation) { |
| // Creating a Normal distribution variable from two independent uniform |
| // variables based on the Box-Muller transform, which is defined on the |
| // interval (0, 1]. Note that we rely on NextOutput to generate integers |
| // in the range [1, 2^64-1]. Normally this behavior is a bit frustrating, |
| // but here it is exactly what we need. |
| const double kPi = 3.14159265358979323846; |
| double u1 = static_cast<double>(NextOutput()) / 0xFFFFFFFFFFFFFFFFull; |
| double u2 = static_cast<double>(NextOutput()) / 0xFFFFFFFFFFFFFFFFull; |
| return mean + standard_deviation * sqrt(-2 * log(u1)) * cos(2 * kPi * u2); |
| } |
| |
| double Random::Exponential(double lambda) { |
| double uniform = Rand<double>(); |
| return -log(uniform) / lambda; |
| } |
| |
| } // namespace webrtc |