Train SVM models that are used by SvmTheoreticalSpectrumGenerator. More...

#include <OpenMS/CHEMISTRY/SvmTheoreticalSpectrumGeneratorTrainer.h>

Inheritance diagram for SvmTheoreticalSpectrumGeneratorTrainer:

Collaboration diagram for SvmTheoreticalSpectrumGeneratorTrainer:

Private Types
typedef SvmTheoreticalSpectrumGenerator::IonType	IonType

typedef SvmTheoreticalSpectrumGenerator::DescriptorSet	DescriptorSet

typedef std::map< std::pair< IonType, Size >, std::vector< double > >	ObservedIntensMap

Private Member Functions
void	countIntensities_ (const PeakSpectrum &spectrum, const AASequence &annotation, IonType type, std::map< std::pair< IonType, Size >, std::vector< double > > &observed_intensities, double tolerance, Size number_of_regions)
	stores the observed intensities for each sector-type combination in a vector More...

void	trainSecondaryTypes_ (TextFile &info_outfile, Size number_of_regions, Size number_of_intensity_levels, ObservedIntensMap &observed_intensities, const std::vector< IonType > &ion_types, const std::vector< bool > &is_primary)
	trains the Bayesian secondary peak types models More...

Constructors and Destructors
	SvmTheoreticalSpectrumGeneratorTrainer ()
	Default constructor. More...

	SvmTheoreticalSpectrumGeneratorTrainer (const SvmTheoreticalSpectrumGeneratorTrainer &source)
	Copy constructor. More...

	~SvmTheoreticalSpectrumGeneratorTrainer () override
	Destructor. More...

SvmTheoreticalSpectrumGeneratorTrainer &	operator= (const SvmTheoreticalSpectrumGeneratorTrainer &tsg)
	Assignment operator. More...

void	trainModel (const PeakMap &spectra, const std::vector< AASequence > &annotations, String filename, Int precursor_charge)
	trains an SVM for each ion_type and stores them in files <filename>_residue_loss_charge.svm More...

void	normalizeIntensity (PeakSpectrum &S) const
	Normalizes the intensity of the peaks in the input data. More...

void	writeTrainingFile_ (std::vector< DescriptorSet > &training_input, std::vector< double > &training_output, String filename)
	Write a training file that can be passed to libsvm command line tools. More...

Additional Inherited Members
Public Member Functions inherited from DefaultParamHandler
	DefaultParamHandler (const String &name)
	Constructor with name that is displayed in error messages. More...

	DefaultParamHandler (const DefaultParamHandler &rhs)
	Copy constructor. More...

virtual	~DefaultParamHandler ()
	Destructor. More...

virtual DefaultParamHandler &	operator= (const DefaultParamHandler &rhs)
	Assignment operator. More...

virtual bool	operator== (const DefaultParamHandler &rhs) const
	Equality operator. More...

void	setParameters (const Param &param)
	Sets the parameters. More...

const Param &	getParameters () const
	Non-mutable access to the parameters. More...

const Param &	getDefaults () const
	Non-mutable access to the default parameters. More...

const String &	getName () const
	Non-mutable access to the name. More...

void	setName (const String &name)
	Mutable access to the name. More...

const std::vector< String > &	getSubsections () const
	Non-mutable access to the registered subsections. More...

Static Public Member Functions inherited from DefaultParamHandler
static void	writeParametersToMetaValues (const Param &write_this, MetaInfoInterface &write_here, const String &prefix="")
	Writes all parameters to meta values. More...

Protected Member Functions inherited from DefaultParamHandler
virtual void	updateMembers_ ()
	This method is used to update extra member variables at the end of the setParameters() method. More...

void	defaultsToParam_ ()
	Updates the parameters after the defaults have been set in the constructor. More...

Protected Attributes inherited from DefaultParamHandler
Param	param_
	Container for current parameters. More...

Param	defaults_
	Container for default parameters. This member should be filled in the constructor of derived classes! More...

std::vector< String >	subsections_
	Container for registered subsections. This member should be filled in the constructor of derived classes! More...

String	error_name_
	Name that is displayed in error messages during the parameter checking. More...

bool	check_defaults_
	If this member is set to false no checking if parameters in done;. More...

bool	warn_empty_defaults_
	If this member is set to false no warning is emitted when defaults are empty;. More...

Detailed Description

Train SVM models that are used by SvmTheoreticalSpectrumGenerator.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
write_training_files	string	false	true, false	If set to true no models are trained but files (__training.dat) are produced for the selected primary ion types. They can be used as input for LibSVM command line tools
number_intensity_levels	int	7		The number of intensity bins (for secondary type models)
number_regions	int	3		The number of regions each spectrum is split to (for secondary type models)
parent_tolerance	float	2.5		The maximum difference between theoretical and experimental parent mass to accept training spectrum
peak_tolerance	float	0.5		The maximum mass error for a peak to the expected mass of some ion type
add_b_ions	string	true	true, false	Train simulator for b-ions
add_y_ions	string	true	true, false	Train simulator for y-ions
add_a_ions	string	false	true, false	Train simulator for a-ions
add_c_ions	string	false	true, false	Train simulator for c-ions
add_x_ions	string	false	true, false	Train simulator for x-ions
add_z_ions	string	false	true, false	Train simulator for z-ions
add_losses	string	false	true, false	Train simulator for neutral losses of H2O and NH3 for b-ions and y-ions
add_b2_ions	string	false	true, false	Train simulator for doubly charged b-ions
add_y2_ions	string	false	true, false	Train simulator for double charged y-ions
svm:svc_type	int	0	min: 0 max: 1	Type of the SVC: 0=C_SVC 1=NU_SVC
svm:svr_type	int	1	min: 0 max: 1	Type of the SVR: 0=EPSILON_SVR 1=NU_SVR
svm:scaling	string	true	true, false	Apply scaling of feature values
svm:scaling_lower	float	0.0		Lower bound for scaling
svm:scaling_upper	float	1.0		Upper bound for scaling
svm:n_fold	int	5	min: 1	n_fold cross validation is performed
svm:grid	string	false	true, false	Perform grid search
svm:additive_cv	string	false	true, false	Additive step size (if false multiplicative)
svm:svc:kernel_type	int	2	min: 0 max: 3	Type of the kernel: 0=LINEAR 1=POLY 2=RBF 3=SIGMOID
svm:svc:degree	int	3	min: 1	For POLY
svm:svc:gamma	float	0.0	min: 0.0	For POLY/RBF/SIGMOID
svm:svc:C	float	1.0		Cost of constraint violation
svm:svc:nu	float	0.5		For NU_SVC, ONE_CLASS and NU_SVR
svm:svc:balancing	string	true	true, false	Use class balanced SVC training
svm:svc:degree_start	int	1	min: 1	starting point of degree
svm:svc:degree_step_size	int	2		step size point of degree
svm:svc:degree_stop	int	4		stopping point of degree
svm:svc:gamma_start	float	1.0e-05	min: 0.0 max: 1.0	starting point of gamma
svm:svc:gamma_step_size	int	100		step size point of gamma
svm:svc:gamma_stop	float	0.1		stopping point of gamma
svm:svc:c_start	float	0.1		starting point of c
svm:svc:c_step_size	int	100		step size of c
svm:svc:c_stop	int	1000		stopping point of c
svm:svc:nu_start	float	0.3	min: 0.0 max: 1.0	starting point of nu
svm:svc:nu_step_size	int	2		step size of nu
svm:svc:nu_stop	float	0.6	min: 0.0 max: 1.0	stopping point of nu
svm:svr:kernel_type	int	2	min: 0 max: 3	Type of the kernel: 0=LINEAR 1=POLY 2=RBF 3=SIGMOID
svm:svr:degree	int	3	min: 1	For POLY
svm:svr:gamma	float	0.0	min: 0.0	For POLY/RBF/SIGMOID
svm:svr:C	float	1.0		Cost of constraint violation
svm:svr:p	float	0.1		The epsilon for the loss function in epsilon-SVR
svm:svr:nu	float	0.5		For NU_SVC, ONE_CLASS and NU_SVR
svm:svr:degree_start	int	1	min: 1	starting point of degree
svm:svr:degree_step_size	int	2		step size point of degree
svm:svr:degree_stop	int	4		stopping point of degree
svm:svr:gamma_start	float	1.0e-05	min: 0.0 max: 1.0	starting point of gamma
svm:svr:gamma_step_size	int	100		step size point of gamma
svm:svr:gamma_stop	float	0.1		stopping point of gamma
svm:svr:p_start	float	1.0e-05		starting point of p
svm:svr:p_step_size	int	100		step size point of p
svm:svr:p_stop	float	0.1		stopping point of p
svm:svr:c_start	float	0.1		starting point of c
svm:svr:c_step_size	int	100		step size of c
svm:svr:c_stop	int	1000		stopping point of c
svm:svr:nu_start	float	0.3	min: 0.0 max: 1.0	starting point of nu
svm:svr:nu_step_size	int	2		step size of nu
svm:svr:nu_stop	float	0.6	min: 0.0 max: 1.0	stopping point of nu

Note:

If a section name is documented, the documentation is displayed as tooltip.
Advanced parameter names are italic.

This class implements the algorithm used by the homonymous tool which can be used to train models for MS/MS spectrum simulation.
For the primary ion types (y, b) a SVM is trained using the libSVM library.
All important libSVM parameters are accessible as parameters.
Please refer to the libSVM manuals for detailed description of the parameters. Default values are chosen as in the svm-training tool delivered with libSVM.
For the secondary types (a, c, x, z, losses, b2, y2) a simple Bayesian model is used.

Member Typedef Documentation

◆ DescriptorSet

typedef SvmTheoreticalSpectrumGenerator::DescriptorSet DescriptorSet

private

◆ IonType

typedef SvmTheoreticalSpectrumGenerator::IonType IonType

private

◆ ObservedIntensMap

typedef std::map<std::pair<IonType, Size>, std::vector<double> > ObservedIntensMap

private

Constructor & Destructor Documentation

◆ SvmTheoreticalSpectrumGeneratorTrainer() [1/2]

SvmTheoreticalSpectrumGeneratorTrainer ( )

Default constructor.

◆ SvmTheoreticalSpectrumGeneratorTrainer() [2/2]

SvmTheoreticalSpectrumGeneratorTrainer ( const SvmTheoreticalSpectrumGeneratorTrainer & source )

Copy constructor.

◆ ~SvmTheoreticalSpectrumGeneratorTrainer()

~SvmTheoreticalSpectrumGeneratorTrainer ( )

override

Destructor.

Member Function Documentation

◆ countIntensities_()

void countIntensities_	(	const PeakSpectrum &	spectrum,
		const AASequence &	annotation,
		IonType	type,
		std::map< std::pair< IonType, Size >, std::vector< double > > &	observed_intensities,
		double	tolerance,
		Size	number_of_regions
	)

private

stores the observed intensities for each sector-type combination in a vector

◆ normalizeIntensity()

void normalizeIntensity ( PeakSpectrum & S ) const

Normalizes the intensity of the peaks in the input data.

◆ operator=()

SvmTheoreticalSpectrumGeneratorTrainer& operator= ( const SvmTheoreticalSpectrumGeneratorTrainer & tsg )

Assignment operator.

◆ trainModel()

void trainModel	(	const PeakMap &	spectra,
		const std::vector< AASequence > &	annotations,
		String	filename,
		Int	precursor_charge
	)

trains an SVM for each ion_type and stores them in files <filename>_residue_loss_charge.svm

◆ trainSecondaryTypes_()

void trainSecondaryTypes_	(	TextFile &	info_outfile,
		Size	number_of_regions,
		Size	number_of_intensity_levels,
		ObservedIntensMap &	observed_intensities,
		const std::vector< IonType > &	ion_types,
		const std::vector< bool > &	is_primary
	)

private

trains the Bayesian secondary peak types models

◆ writeTrainingFile_()

void writeTrainingFile_	(	std::vector< DescriptorSet > &	training_input,
		std::vector< double > &	training_output,
		String	filename
	)

protected

Write a training file that can be passed to libsvm command line tools.

Private Types

Private Member Functions

Constructors and Destructors

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ DescriptorSet

◆ IonType

◆ ObservedIntensMap

Constructor & Destructor Documentation

◆ SvmTheoreticalSpectrumGeneratorTrainer() [1/2]

◆ SvmTheoreticalSpectrumGeneratorTrainer() [2/2]

◆ ~SvmTheoreticalSpectrumGeneratorTrainer()

Member Function Documentation

◆ countIntensities_()

◆ normalizeIntensity()

◆ operator=()

◆ trainModel()

◆ trainSecondaryTypes_()

◆ writeTrainingFile_()