EmgGradientDescent.h

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// --------------------------------------------------------------------------
//                   OpenMS -- Open-Source Mass Spectrometry
// --------------------------------------------------------------------------
// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2018.
//
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//    may be used to endorse or promote products derived from this software
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// $Maintainer: Douglas McCloskey, Pasquale Domenico Colaianni $
// $Authors: Douglas McCloskey, Pasquale Domenico Colaianni $
// --------------------------------------------------------------------------

#pragma once

#include <OpenMS/config.h> // OPENMS_DLLAPI
#include <OpenMS/DATASTRUCTURES/DefaultParamHandler.h>
#include <OpenMS/KERNEL/MSChromatogram.h>
#include <OpenMS/KERNEL/MSSpectrum.h>

namespace OpenMS
{
  class OPENMS_DLLAPI EmgGradientDescent :
    public DefaultParamHandler
  {
public:
    EmgGradientDescent();
    ~EmgGradientDescent() = default;

    void getDefaultParameters(Param& params);

    friend class EmgGradientDescent_friend;

    template <typename PeakContainerT>
    void fitEMGPeakModel(
      const PeakContainerT& input_peak,
      PeakContainerT& output_peak,
      const double left_pos = 0.0,
      const double right_pos = 0.0
    ) const;

protected:
    void updateMembers_();

    void extractTrainingSet(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      std::vector<double>& TrX,
      std::vector<double>& TrY
    ) const;

    double computeMuMaxDistance(const std::vector<double>& xs) const;

    double computeInitialMean(
      const std::vector<double>& xs,
      const std::vector<double>& ys
    ) const;

private:
    UInt emg_gradient_descent(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      double& best_h,
      double& best_mu,
      double& best_sigma,
      double& best_tau
    ) const;

    void iRpropPlus(
      const double prev_diff_E_param,
      double& diff_E_param,
      double& param_lr,
      double& param_update,
      double& param,
      const double current_E,
      const double previous_E
    ) const;

    double Loss_function(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    double E_wrt_h(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    double E_wrt_mu(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    double E_wrt_sigma(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    double E_wrt_tau(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    double compute_z(
      const double x,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    void emg_vector(
      const std::vector<double>& xs,
      const double h,
      const double mu,
      const double sigma,
      const double tau,
      std::vector<double>& out_xs,
      std::vector<double>& out_ys
    ) const;

    double emg_point(
      const double x,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const;

    const double PI = OpenMS::Constants::PI;

    UInt print_debug_;

    UInt max_gd_iter_;

    bool compute_additional_points_;
  };

  class EmgGradientDescent_friend
  {
public:
    EmgGradientDescent_friend() = default;
    ~EmgGradientDescent_friend() = default;

    double Loss_function(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const
    {
      return emg_gd_.Loss_function(xs, ys, h, mu, sigma, tau);
    }

    double computeMuMaxDistance(const std::vector<double>& xs) const
    {
      return emg_gd_.computeMuMaxDistance(xs);
    }

    void extractTrainingSet(
      const std::vector<double>& xs,
      const std::vector<double>& ys,
      std::vector<double>& TrX,
      std::vector<double>& TrY
    ) const
    {
      emg_gd_.extractTrainingSet(xs, ys, TrX, TrY);
    }

    double computeInitialMean(
      const std::vector<double>& xs,
      const std::vector<double>& ys
    ) const
    {
      return emg_gd_.computeInitialMean(xs, ys);
    }

    void iRpropPlus(
      const double prev_diff_E_param,
      double& diff_E_param,
      double& param_lr,
      double& param_update,
      double& param,
      const double current_E,
      const double previous_E
    ) const
    {
      emg_gd_.iRpropPlus(
        prev_diff_E_param, diff_E_param, param_lr,
        param_update, param, current_E, previous_E
      );
    }

    double compute_z(
      const double x,
      const double mu,
      const double sigma,
      const double tau
    ) const
    {
      return emg_gd_.compute_z(x, mu, sigma, tau);
    }

    void emg_vector(
      const std::vector<double>& xs,
      const double h,
      const double mu,
      const double sigma,
      const double tau,
      std::vector<double>& out_xs,
      std::vector<double>& out_ys
    ) const
    {
      emg_gd_.emg_vector(xs, h, mu, sigma, tau, out_xs, out_ys);
    }

    double emg_point(
      const double x,
      const double h,
      const double mu,
      const double sigma,
      const double tau
    ) const
    {
      return emg_gd_.emg_point(x, h, mu, sigma, tau);
    }

    EmgGradientDescent emg_gd_;
  };
}