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88 lines
2.7 KiB
C++
88 lines
2.7 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2021 PX4 Development Team. All rights reserved.
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*
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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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*
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* 1. 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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* 2. 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
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* distribution.
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* 3. Neither the name PX4 nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* 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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****************************************************************************/
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/**
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* @file WelfordMean.hpp
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*
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* Welford's online algorithm for computing mean and variance.
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*/
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#pragma once
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namespace math
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{
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template<typename T>
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class WelfordMean
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{
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public:
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// For a new value, compute the new count, new mean, the new M2.
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void update(const T &new_value)
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{
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if (_count == 0) {
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_mean = new_value;
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}
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_count++;
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// mean accumulates the mean of the entire dataset
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const T delta{new_value - _mean};
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_mean += delta / _count;
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// M2 aggregates the squared distance from the mean
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// count aggregates the number of samples seen so far
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_M2 += delta.emult(new_value - _mean);
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}
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bool valid() const { return _count > 2; }
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unsigned count() const { return _count; }
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void reset()
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{
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_count = 0;
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_mean = {};
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_M2 = {};
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}
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// Retrieve the mean, variance and sample variance
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T mean() const { return _mean; }
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T variance() const { return _M2 / _count; }
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T sample_variance() const { return _M2 / (_count - 1); }
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private:
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T _mean{};
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T _M2{};
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unsigned _count{0};
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};
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} // namespace math
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