forked from premiere/premiere-libtorrent
120 lines
3.5 KiB
C++
120 lines
3.5 KiB
C++
/*
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Copyright (c) 2010-2016, Arvid Norberg
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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* Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in
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the documentation and/or other materials provided with the distribution.
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* Neither the name of the author nor the names of its
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contributors may be used to endorse or promote products derived
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from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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POSSIBILITY OF SUCH DAMAGE.
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*/
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#ifndef TORRENT_SLIDING_AVERAGE_HPP_INCLUDED
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#define TORRENT_SLIDING_AVERAGE_HPP_INCLUDED
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#include <cstdint>
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#include <cstdlib> // for std::abs
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namespace libtorrent
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{
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// an exponential moving average accumulator. Add samples to it and it keeps
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// track of a moving mean value and an average deviation
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template <int inverted_gain>
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struct sliding_average
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{
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sliding_average(): m_mean(0), m_average_deviation(0), m_num_samples(0) {}
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sliding_average(sliding_average const&) = default;
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sliding_average& operator=(sliding_average const&) = default;
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void add_sample(int s)
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{
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// fixed point
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s *= 64;
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int deviation = 0;
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if (m_num_samples > 0)
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deviation = std::abs(m_mean - s);
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if (m_num_samples < inverted_gain)
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++m_num_samples;
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m_mean += (s - m_mean) / m_num_samples;
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if (m_num_samples > 1) {
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// the the exact same thing for deviation off the mean except -1 on
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// the samples, because the number of deviation samples always lags
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// behind by 1 (you need to actual samples to have a single deviation
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// sample).
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m_average_deviation += (deviation - m_average_deviation) / (m_num_samples - 1);
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}
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}
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int mean() const { return m_num_samples > 0 ? (m_mean + 32) / 64 : 0; }
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int avg_deviation() const { return m_num_samples > 1 ? (m_average_deviation + 32) / 64 : 0; }
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int num_samples() const { return m_num_samples; }
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private:
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// both of these are fixed point values (* 64)
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int m_mean = 0;
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int m_average_deviation = 0;
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// the number of samples we have received, but no more than inverted_gain
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// this is the effective inverted_gain
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int m_num_samples = 0;
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};
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struct average_accumulator
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{
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average_accumulator() {}
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void add_sample(int s)
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{
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++m_num_samples;
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m_sample_sum += s;
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}
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int mean()
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{
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int ret;
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if (m_num_samples == 0) ret = 0;
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else ret = int(m_sample_sum / m_num_samples);
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// in case we don't get any more samples, at least
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// let the average roll over, but only be worth a
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// single sample
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m_num_samples = 1;
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m_sample_sum = ret;
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return ret;
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}
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private:
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int m_num_samples = 0;
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std::uint64_t m_sample_sum = 0;
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};
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}
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#endif
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