OptimizePick.h

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// Copyright (c) 2002-2023, The OpenMS Team -- EKU Tuebingen, ETH Zurich, and FU Berlin
// SPDX-License-Identifier: BSD-3-Clause
//
// --------------------------------------------------------------------------
// $Maintainer: Timo Sachsenberg $
// $Authors: Eva Lange $
// --------------------------------------------------------------------------
 
#pragma once
 
#include <OpenMS/TRANSFORMATIONS/RAW2PEAK/PeakShape.h>
#include <OpenMS/KERNEL/Peak1D.h>
 
// forward decl
namespace Eigen
{
    template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
    class Matrix;
    using MatrixXd = Matrix<double, -1, -1, 0, -1, -1>;
    using VectorXd = Matrix<double, -1, 1, 0, -1, 1>;
}
 
#include <vector>
 
namespace OpenMS
{
  namespace OptimizationFunctions
  {
    typedef std::vector<Peak1D> RawDataVector;
    typedef RawDataVector::iterator PeakIterator;
 
    struct OPENMS_DLLAPI PenaltyFactors
    {
      PenaltyFactors() :
        pos(0), lWidth(0), rWidth(0) {}
      PenaltyFactors(const PenaltyFactors & p) :
        pos(p.pos), lWidth(p.lWidth), rWidth(p.rWidth) {}
      inline PenaltyFactors & operator=(const PenaltyFactors & p)
      {
        pos = p.pos;
        lWidth = p.lWidth;
        rWidth = p.rWidth;
 
        return *this;
      }
 
      ~PenaltyFactors(){}
 
      double pos;
      double lWidth;
      double rWidth;
    };
  }
 
 
  class OPENMS_DLLAPI OptimizePick
  {
public:
 
    struct Data
    {
      std::vector<double> positions;
      std::vector<double> signal;
      std::vector<PeakShape> peaks;
 
      OptimizationFunctions::PenaltyFactors penalties;
 
    };
 
    class OptPeakFunctor
    {
    public:
      int inputs() const { return m_inputs; }
      int values() const { return m_values; }
 
      OptPeakFunctor(unsigned dimensions, unsigned num_data_points, const OptimizePick::Data * data)
      : m_inputs(dimensions), m_values(num_data_points), m_data(data) {}
 
      int operator()(const Eigen::VectorXd &x, Eigen::VectorXd &fvec);
      // compute Jacobian matrix for the different parameters
      int df(const Eigen::VectorXd &x, Eigen::MatrixXd &J);
 
    private:
      const int m_inputs, m_values;
      const Data * m_data;
    };
 
    typedef std::vector<Peak1D> RawDataVector;
    typedef RawDataVector::iterator PeakIterator;
 
 
    OptimizePick() :
      max_iteration_(400)
    {}
 
    OptimizePick(const struct OptimizationFunctions::PenaltyFactors & penalties_,
                 const int max_iteration_);
 
    ~OptimizePick();
 
    inline const struct OptimizationFunctions::PenaltyFactors & getPenalties() const { return penalties_; }
    inline struct OptimizationFunctions::PenaltyFactors & getPenalties() { return penalties_; }
    inline void setPenalties(const struct OptimizationFunctions::PenaltyFactors & penalties) { penalties_ = penalties; }
 
    inline UInt getNumberIterations() const { return max_iteration_; }
    inline unsigned int & getNumberIterations() { return max_iteration_; }
    inline void setNumberIterations(const int max_iteration) { max_iteration_ = max_iteration; }
 
    void optimize(std::vector<PeakShape> & peaks, Data & data);
 
 
protected:
    struct OptimizationFunctions::PenaltyFactors penalties_;
 
    unsigned int max_iteration_;
  };
}