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/*
* Copyright (c) 2018 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.
*/
#ifndef RTC_TOOLS_FRAME_ANALYZER_LINEAR_LEAST_SQUARES_H_
#define RTC_TOOLS_FRAME_ANALYZER_LINEAR_LEAST_SQUARES_H_
#include <stdint.h>
#include <optional>
#include <valarray>
#include <vector>
namespace webrtc {
namespace test {
// This class is used for finding a matrix b that roughly solves the equation:
// y = x * b. This is generally impossible to do exactly, so the problem is
// rephrased as finding the matrix b that minimizes the difference:
// |y - x * b|^2. Calling multiple AddObservations() is equivalent to
// concatenating the observation vectors and calling AddObservations() once. The
// reason for doing it incrementally is that we can't store the raw YUV values
// for a whole video file in memory at once. This class has a constant memory
// footprint, regardless how may times AddObservations() is called.
class IncrementalLinearLeastSquares {
public:
IncrementalLinearLeastSquares();
~IncrementalLinearLeastSquares();
// Add a number of observations. The subvectors of x and y must have the same
// length.
void AddObservations(const std::vector<std::vector<uint8_t>>& x,
const std::vector<std::vector<uint8_t>>& y);
// Calculate and return the best linear solution, given the observations so
// far.
std::vector<std::vector<double>> GetBestSolution() const;
private:
// Running sum of x^T * x.
std::optional<std::valarray<std::valarray<uint64_t>>> sum_xx;
// Running sum of x^T * y.
std::optional<std::valarray<std::valarray<uint64_t>>> sum_xy;
};
} // namespace test
} // namespace webrtc
#endif // RTC_TOOLS_FRAME_ANALYZER_LINEAR_LEAST_SQUARES_H_
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