blob: 3868031dd8333c56b6a858e9e7e2be9cf0adab89 [file] [log] [blame]
/*
* libjingle
* Copyright 2011, Google Inc.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* 3. The name of the author may not be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
* MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
* EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
* WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
* OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
* ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef TALK_BASE_ROLLINGACCUMULATOR_H_
#define TALK_BASE_ROLLINGACCUMULATOR_H_
#include <vector>
#include "talk/base/common.h"
namespace talk_base {
// RollingAccumulator stores and reports statistics
// over N most recent samples.
//
// T is assumed to be an int, long, double or float.
template<typename T>
class RollingAccumulator {
public:
explicit RollingAccumulator(size_t max_count)
: count_(0),
next_index_(0),
sum_(0.0),
sum_2_(0.0),
samples_(max_count) {
}
~RollingAccumulator() {
}
int max_count() const {
return samples_.size();
}
int count() const {
return count_;
}
void AddSample(T sample) {
if (count_ == max_count()) {
// Remove oldest sample.
T sample_to_remove = samples_[next_index_];
sum_ -= sample_to_remove;
sum_2_ -= sample_to_remove * sample_to_remove;
} else {
// Increase count of samples.
++count_;
}
// Add new sample.
samples_[next_index_] = sample;
sum_ += sample;
sum_2_ += sample * sample;
// Update next_index_.
next_index_ = (next_index_ + 1) % max_count();
}
T ComputeSum() const {
return static_cast<T>(sum_);
}
T ComputeMean() const {
if (count_ == 0) {
return static_cast<T>(0);
}
return static_cast<T>(sum_ / count_);
}
// Compute estimated variance. Estimation is more accurate
// as the number of samples grows.
T ComputeVariance() const {
if (count_ == 0) {
return static_cast<T>(0);
}
// Var = E[x^2] - (E[x])^2
double count_inv = 1.0 / count_;
double mean_2 = sum_2_ * count_inv;
double mean = sum_ * count_inv;
return static_cast<T>(mean_2 - (mean * mean));
}
private:
int count_;
int next_index_;
double sum_; // Sum(x)
double sum_2_; // Sum(x*x)
std::vector<T> samples_;
DISALLOW_COPY_AND_ASSIGN(RollingAccumulator);
};
} // namespace talk_base
#endif // TALK_BASE_ROLLINGACCUMULATOR_H_