OpenMS  3.0.0
EmgGradientDescent.h
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32 // $Authors: Douglas McCloskey, Pasquale Domenico Colaianni $
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34 
35 #pragma once
36 
37 #include <OpenMS/config.h> // OPENMS_DLLAPI
41 
42 namespace OpenMS
43 {
64  class OPENMS_DLLAPI EmgGradientDescent :
65  public DefaultParamHandler
66  {
67 public:
71  ~EmgGradientDescent() override = default;
72 
73  void getDefaultParameters(Param& params);
74 
77 
111  template <typename PeakContainerT>
112  void fitEMGPeakModel(
113  const PeakContainerT& input_peak,
114  PeakContainerT& output_peak,
115  const double left_pos = 0.0,
116  const double right_pos = 0.0
117  ) const;
118 
131  UInt estimateEmgParameters(
132  const std::vector<double>& xs,
133  const std::vector<double>& ys,
134  double& best_h,
135  double& best_mu,
136  double& best_sigma,
137  double& best_tau
138  ) const;
139 
154  void applyEstimatedParameters(
155  const std::vector<double>& xs,
156  const double h,
157  const double mu,
158  const double sigma,
159  const double tau,
160  std::vector<double>& out_xs,
161  std::vector<double>& out_ys
162  ) const;
163 
164 protected:
165  void updateMembers_() override;
166 
189  void extractTrainingSet(
190  const std::vector<double>& xs,
191  const std::vector<double>& ys,
192  std::vector<double>& TrX,
193  std::vector<double>& TrY
194  ) const;
195 
208  double computeMuMaxDistance(const std::vector<double>& xs) const;
209 
223  double computeInitialMean(
224  const std::vector<double>& xs,
225  const std::vector<double>& ys
226  ) const;
227 
228 private:
246  void iRpropPlus(
247  const double prev_diff_E_param,
248  double& diff_E_param,
249  double& param_lr,
250  double& param_update,
251  double& param,
252  const double current_E,
253  const double previous_E
254  ) const;
255 
271  double Loss_function(
272  const std::vector<double>& xs,
273  const std::vector<double>& ys,
274  const double h,
275  const double mu,
276  const double sigma,
277  const double tau
278  ) const;
279 
295  double E_wrt_h(
296  const std::vector<double>& xs,
297  const std::vector<double>& ys,
298  const double h,
299  const double mu,
300  const double sigma,
301  const double tau
302  ) const;
303 
319  double E_wrt_mu(
320  const std::vector<double>& xs,
321  const std::vector<double>& ys,
322  const double h,
323  const double mu,
324  const double sigma,
325  const double tau
326  ) const;
327 
343  double E_wrt_sigma(
344  const std::vector<double>& xs,
345  const std::vector<double>& ys,
346  const double h,
347  const double mu,
348  const double sigma,
349  const double tau
350  ) const;
351 
367  double E_wrt_tau(
368  const std::vector<double>& xs,
369  const std::vector<double>& ys,
370  const double h,
371  const double mu,
372  const double sigma,
373  const double tau
374  ) const;
375 
396  double compute_z(
397  const double x,
398  const double mu,
399  const double sigma,
400  const double tau
401  ) const;
402 
414  double emg_point(
415  const double x,
416  const double h,
417  const double mu,
418  const double sigma,
419  const double tau
420  ) const;
421 
423  const double PI = OpenMS::Constants::PI;
424 
431 
434 
440  };
441 
443  {
444 public:
445  EmgGradientDescent_friend() = default;
446  ~EmgGradientDescent_friend() = default;
447 
449  const std::vector<double>& xs,
450  const std::vector<double>& ys,
451  const double h,
452  const double mu,
453  const double sigma,
454  const double tau
455  ) const
456  {
457  return emg_gd_.Loss_function(xs, ys, h, mu, sigma, tau);
458  }
459 
460  double computeMuMaxDistance(const std::vector<double>& xs) const
461  {
462  return emg_gd_.computeMuMaxDistance(xs);
463  }
464 
466  const std::vector<double>& xs,
467  const std::vector<double>& ys,
468  std::vector<double>& TrX,
469  std::vector<double>& TrY
470  ) const
471  {
472  emg_gd_.extractTrainingSet(xs, ys, TrX, TrY);
473  }
474 
476  const std::vector<double>& xs,
477  const std::vector<double>& ys
478  ) const
479  {
480  return emg_gd_.computeInitialMean(xs, ys);
481  }
482 
484  const double prev_diff_E_param,
485  double& diff_E_param,
486  double& param_lr,
487  double& param_update,
488  double& param,
489  const double current_E,
490  const double previous_E
491  ) const
492  {
494  prev_diff_E_param, diff_E_param, param_lr,
495  param_update, param, current_E, previous_E
496  );
497  }
498 
499  double compute_z(
500  const double x,
501  const double mu,
502  const double sigma,
503  const double tau
504  ) const
505  {
506  return emg_gd_.compute_z(x, mu, sigma, tau);
507  }
508 
510  const std::vector<double>& xs,
511  const double h,
512  const double mu,
513  const double sigma,
514  const double tau,
515  std::vector<double>& out_xs,
516  std::vector<double>& out_ys
517  ) const
518  {
519  emg_gd_.applyEstimatedParameters(xs, h, mu, sigma, tau, out_xs, out_ys);
520  }
521 
522  double emg_point(
523  const double x,
524  const double h,
525  const double mu,
526  const double sigma,
527  const double tau
528  ) const
529  {
530  return emg_gd_.emg_point(x, h, mu, sigma, tau);
531  }
532 
534  };
535 }
OpenMS::EmgGradientDescent::print_debug_
UInt print_debug_
Definition: EmgGradientDescent.h:430
OpenMS::EmgGradientDescent_friend::~EmgGradientDescent_friend
~EmgGradientDescent_friend()=default
DefaultParamHandler.h
OpenMS::EmgGradientDescent::applyEstimatedParameters
void applyEstimatedParameters(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
Compute the EMG function on a set of points.
OpenMS::EmgGradientDescent::extractTrainingSet
void extractTrainingSet(const std::vector< double > &xs, const std::vector< double > &ys, std::vector< double > &TrX, std::vector< double > &TrY) const
Given a peak, extract a training set to be used with the gradient descent algorithm.
OpenMS::EmgGradientDescent::compute_additional_points_
bool compute_additional_points_
Definition: EmgGradientDescent.h:439
OpenMS::EmgGradientDescent::emg_point
double emg_point(const double x, const double h, const double mu, const double sigma, const double tau) const
Compute the EMG function on a single point.
OpenMS::EmgGradientDescent_friend::iRpropPlus
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
Definition: EmgGradientDescent.h:483
OpenMS::EmgGradientDescent
Compute the area, background and shape metrics of a peak.
Definition: EmgGradientDescent.h:64
OpenMS::EmgGradientDescent::Loss_function
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
Compute the cost given by loss function E.
OpenMS::EmgGradientDescent_friend::computeMuMaxDistance
double computeMuMaxDistance(const std::vector< double > &xs) const
Definition: EmgGradientDescent.h:460
OpenMS::DefaultParamHandler
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:92
OpenMS::EmgGradientDescent::computeInitialMean
double computeInitialMean(const std::vector< double > &xs, const std::vector< double > &ys) const
Compute an estimation of the mean of a peak.
OpenMS
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:47
OpenMS::EmgGradientDescent_friend::emg_point
double emg_point(const double x, const double h, const double mu, const double sigma, const double tau) const
Definition: EmgGradientDescent.h:522
OpenMS::EmgGradientDescent_friend::EmgGradientDescent_friend
EmgGradientDescent_friend()=default
OpenMS::EmgGradientDescent::compute_z
double compute_z(const double x, const double mu, const double sigma, const double tau) const
Compute EMG's z parameter.
OpenMS::EmgGradientDescent_friend::extractTrainingSet
void extractTrainingSet(const std::vector< double > &xs, const std::vector< double > &ys, std::vector< double > &TrX, std::vector< double > &TrY) const
Definition: EmgGradientDescent.h:465
OpenMS::EmgGradientDescent_friend::compute_z
double compute_z(const double x, const double mu, const double sigma, const double tau) const
Definition: EmgGradientDescent.h:499
OpenMS::EmgGradientDescent_friend
Definition: EmgGradientDescent.h:442
OpenMS::EmgGradientDescent_friend::emg_gd_
EmgGradientDescent emg_gd_
Definition: EmgGradientDescent.h:533
OpenMS::EmgGradientDescent_friend::applyEstimatedParameters
void applyEstimatedParameters(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
Definition: EmgGradientDescent.h:509
OpenMS::UInt
unsigned int UInt
Unsigned integer type.
Definition: Types.h:94
OpenMS::Constants::PI
const double PI
PI.
Definition: Constants.h:75
OpenMS::EmgGradientDescent_friend::computeInitialMean
double computeInitialMean(const std::vector< double > &xs, const std::vector< double > &ys) const
Definition: EmgGradientDescent.h:475
OpenMS::Constants::h
const double h
Definition: Constants.h:162
OpenMS::EmgGradientDescent::computeMuMaxDistance
double computeMuMaxDistance(const std::vector< double > &xs) const
Compute the boundary for the mean (`mu`) parameter in gradient descent.
MSChromatogram.h
OpenMS::Param
Management and storage of parameters / INI files.
Definition: Param.h:69
OpenMS::EmgGradientDescent_friend::Loss_function
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
Definition: EmgGradientDescent.h:448
OpenMS::EmgGradientDescent::iRpropPlus
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
Apply the iRprop+ algorithm for gradient descent.
OpenMS::EmgGradientDescent::max_gd_iter_
UInt max_gd_iter_
Maximum number of gradient descent iterations in `fitEMGPeakModel()`.
Definition: EmgGradientDescent.h:433
MSSpectrum.h