/*
 *  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_