premiere-libtorrent/include/libtorrent/sliding_average.hpp

/*

Copyright (c) 2010-2016, Arvid Norberg
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#ifndef TORRENT_SLIDING_AVERAGE_HPP_INCLUDED
#define TORRENT_SLIDING_AVERAGE_HPP_INCLUDED

#include <cstdint>
#include <cstdlib> // for std::abs

namespace libtorrent
{

// an exponential moving average accumulator. Add samples to it and it keeps
// track of a moving mean value and an average deviation
template <int inverted_gain>
struct sliding_average
{
	sliding_average(): m_mean(0), m_average_deviation(0), m_num_samples(0) {}
	sliding_average(sliding_average const&) = default;
	sliding_average& operator=(sliding_average const&) = default;

	void add_sample(int s)
	{
		// fixed point
		s *= 64;
		int deviation = 0;

		if (m_num_samples > 0)
			deviation = std::abs(m_mean - s);

		if (m_num_samples < inverted_gain)
			++m_num_samples;

		m_mean += (s - m_mean) / m_num_samples;

		if (m_num_samples > 1) {
			// the the exact same thing for deviation off the mean except -1 on
			// the samples, because the number of deviation samples always lags
			// behind by 1 (you need to actual samples to have a single deviation
			// sample).
			m_average_deviation += (deviation - m_average_deviation) / (m_num_samples - 1);
		}
	}

	int mean() const { return m_num_samples > 0 ? (m_mean + 32) / 64 : 0; }
	int avg_deviation() const { return m_num_samples > 1 ? (m_average_deviation + 32) / 64 : 0; }
	int num_samples() const { return m_num_samples; }

private:
	// both of these are fixed point values (* 64)
	int m_mean = 0;
	int m_average_deviation = 0;
	// the number of samples we have received, but no more than inverted_gain
	// this is the effective inverted_gain
	int m_num_samples = 0;
};

struct average_accumulator
{
	average_accumulator() {}

	void add_sample(int s)
	{
		++m_num_samples;
		m_sample_sum += s;
	}

	int mean()
	{
		int ret;
		if (m_num_samples == 0) ret = 0;
		else ret = int(m_sample_sum / m_num_samples);
		// in case we don't get any more samples, at least
		// let the average roll over, but only be worth a
		// single sample
		m_num_samples = 1;
		m_sample_sum = ret;
		return ret;
	}

private:

	int m_num_samples = 0;
	std::uint64_t m_sample_sum = 0;
};

}

#endif