blob: 0a82b8d72d938e327f27ebacacb8f15f2935f1a7 [file] [log] [blame]
/*
* 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 "webrtc/test/random.h"
#include <math.h>
#include "webrtc/base/checks.h"
namespace webrtc {
namespace test {
Random::Random(uint32_t seed) : a_(0x531FDB97 ^ seed), b_(0x6420ECA8 + seed) {
}
uint32_t Random::Rand(uint32_t t) {
// If b / 2^32 is uniform on [0,1), then b / 2^32 * (t+1) is uniform on
// the interval [0,t+1), so the integer part is uniform on [0,t].
uint64_t result = b_ * (static_cast<uint64_t>(t) + 1);
result >>= 32;
a_ ^= b_;
b_ += a_;
return result;
}
uint32_t Random::Rand(uint32_t low, uint32_t high) {
RTC_DCHECK(low <= high);
return Rand(high - low) + low;
}
template <>
float Random::Rand<float>() {
const double kScale = 1.0f / (static_cast<uint64_t>(1) << 32);
double result = kScale * b_;
a_ ^= b_;
b_ += a_;
return static_cast<float>(result);
}
template <>
bool Random::Rand<bool>() {
return Rand(0, 1) == 1;
}
int Random::Gaussian(int mean, int 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], hence the mask+add below.
const double kPi = 3.14159265358979323846;
const double kScale = 1.0 / 0x80000000ul;
double u1 = kScale * ((a_ & 0x7ffffffful) + 1);
double u2 = kScale * ((b_ & 0x7ffffffful) + 1);
a_ ^= b_;
b_ += a_;
return static_cast<int>(
mean + standard_deviation * sqrt(-2 * log(u1)) * cos(2 * kPi * u2));
}
int Random::Exponential(float lambda) {
float uniform = Rand<float>();
return static_cast<int>(-log(uniform) / lambda);
}
} // namespace test
} // namespace webrtc