SignalToNoiseEstimatorMeanIterative< Container > Class Template Reference

Estimates the signal/noise (S/N) ratio of each data point in a scan based on an iterative scheme which discards high intensities. More...

#include <OpenMS/PROCESSING/NOISEESTIMATION/SignalToNoiseEstimatorMeanIterative.h>

Inheritance diagram for SignalToNoiseEstimatorMeanIterative< Container >:

Collaboration diagram for SignalToNoiseEstimatorMeanIterative< Container >:

Public Types
enum	IntensityThresholdCalculation { MANUAL = -1 , AUTOMAXBYSTDEV = 0 , AUTOMAXBYPERCENT = 1 }
	method to use for estimating the maximal intensity that is used for histogram calculation More...
typedef SignalToNoiseEstimator< Container >::PeakIterator	PeakIterator
typedef SignalToNoiseEstimator< Container >::PeakType	PeakType
typedef SignalToNoiseEstimator< Container >::GaussianEstimate	GaussianEstimate
Public Types inherited from SignalToNoiseEstimator< Container >
typedef Container::const_iterator	PeakIterator
typedef PeakIterator::value_type	PeakType
Public Types inherited from ProgressLogger
enum	LogType { CMD , GUI , NONE }
	Possible log types. More...

Public Member Functions
	SignalToNoiseEstimatorMeanIterative ()
	default constructor
	SignalToNoiseEstimatorMeanIterative (const SignalToNoiseEstimatorMeanIterative &source)
	Copy Constructor.
Public Member Functions inherited from SignalToNoiseEstimator< Container >
	SignalToNoiseEstimator ()
	Constructor.
	SignalToNoiseEstimator (const SignalToNoiseEstimator &source)
	Copy constructor.
SignalToNoiseEstimator &	operator= (const SignalToNoiseEstimator &source)
	Assignment operator.
	~SignalToNoiseEstimator () override
	Destructor.
virtual void	init (const Container &c)
	Set the start and endpoint of the raw data interval, for which signal to noise ratios will be estimated immediately.
virtual double	getSignalToNoise (const Size index) const
Public Member Functions inherited from DefaultParamHandler
	DefaultParamHandler (const String &name)
	Constructor with name that is displayed in error messages.
	DefaultParamHandler (const DefaultParamHandler &rhs)
	Copy constructor.
virtual	~DefaultParamHandler ()
	Destructor.
DefaultParamHandler &	operator= (const DefaultParamHandler &rhs)
	Assignment operator.
virtual bool	operator== (const DefaultParamHandler &rhs) const
	Equality operator.
void	setParameters (const Param &param)
	Sets the parameters.
const Param &	getParameters () const
	Non-mutable access to the parameters.
const Param &	getDefaults () const
	Non-mutable access to the default parameters.
const String &	getName () const
	Non-mutable access to the name.
void	setName (const String &name)
	Mutable access to the name.
const std::vector< String > &	getSubsections () const
	Non-mutable access to the registered subsections.
Public Member Functions inherited from ProgressLogger
	ProgressLogger ()
	Constructor.
virtual	~ProgressLogger ()
	Destructor.
	ProgressLogger (const ProgressLogger &other)
	Copy constructor.
ProgressLogger &	operator= (const ProgressLogger &other)
	Assignment Operator.
void	setLogType (LogType type) const
	Sets the progress log that should be used. The default type is NONE!
LogType	getLogType () const
	Returns the type of progress log being used.
void	setLogger (ProgressLoggerImpl *logger)
	Sets the logger to be used for progress logging.
void	startProgress (SignedSize begin, SignedSize end, const String &label) const
	Initializes the progress display.
void	setProgress (SignedSize value) const
	Sets the current progress.
void	endProgress (UInt64 bytes_processed=0) const
void	nextProgress () const
	increment progress by 1 (according to range begin-end)

Assignment
double	max_intensity_
	maximal intensity considered during binning (values above get discarded)
double	auto_max_stdev_Factor_
	parameter for initial automatic estimation of "max_intensity_": a stdev multiplier
double	auto_max_percentile_
	parameter for initial automatic estimation of "max_intensity_" percentile or a stdev
int	auto_mode_
	determines which method shall be used for estimating "max_intensity_". valid are MANUAL=-1, AUTOMAXBYSTDEV=0 or AUTOMAXBYPERCENT=1
double	win_len_
	range of data points which belong to a window in Thomson
int	bin_count_
	number of bins in the histogram
double	stdev_
	multiplier for the stdev of intensities
int	min_required_elements_
	minimal number of elements a window needs to cover to be used
double	noise_for_empty_window_
SignalToNoiseEstimatorMeanIterative &	operator= (const SignalToNoiseEstimatorMeanIterative &source)
	~SignalToNoiseEstimatorMeanIterative () override
	Destructor.
void	computeSTN_ (const Container &c) override
void	updateMembers_ () override
	overridden function from DefaultParamHandler to keep members up to date, when a parameter is changed

Additional Inherited Members
Static Public Member Functions inherited from DefaultParamHandler
static void	writeParametersToMetaValues (const Param &write_this, MetaInfoInterface &write_here, const String &key_prefix="")
	Writes all parameters to meta values.
Protected Member Functions inherited from SignalToNoiseEstimator< Container >
GaussianEstimate	estimate_ (const PeakIterator &scan_first_, const PeakIterator &scan_last_) const
	calculate mean & stdev of intensities of a spectrum
Protected Member Functions inherited from DefaultParamHandler
void	defaultsToParam_ ()
	Updates the parameters after the defaults have been set in the constructor.
Protected Attributes inherited from SignalToNoiseEstimator< Container >
std::vector< double >	stn_estimates_
	stores the noise estimate for each peak
Protected Attributes inherited from DefaultParamHandler
Param	param_
	Container for current parameters.
Param	defaults_
	Container for default parameters. This member should be filled in the constructor of derived classes!
std::vector< String >	subsections_
	Container for registered subsections. This member should be filled in the constructor of derived classes!
String	error_name_
	Name that is displayed in error messages during the parameter checking.
bool	check_defaults_
	If this member is set to false no checking if parameters in done;.
bool	warn_empty_defaults_
	If this member is set to false no warning is emitted when defaults are empty;.
Protected Attributes inherited from ProgressLogger
LogType	type_
time_t	last_invoke_
ProgressLoggerImpl *	current_logger_
Static Protected Attributes inherited from ProgressLogger
static int	recursion_depth_

Detailed Description

template<typename Container = MSSpectrum>
class OpenMS::SignalToNoiseEstimatorMeanIterative< Container >

Estimates the signal/noise (S/N) ratio of each data point in a scan based on an iterative scheme which discards high intensities.

For each datapoint in the given scan, we collect a range of data points around it (param: win_len). The noise for a datapoint is estimated iteratively by discarding peaks which are more than (stdev_mp * StDev) above the mean value. After three iterations, the mean value is considered to be the noise level. If the number of elements in the current window is not sufficient (param: min_required_elements), the noise level is set to a default value (param: noise_for_empty_window).

The whole computation is histogram based, so the user will need to supply a number of bins (param: bin_count), which determines the level of error and runtime. The maximal intensity for a datapoint to be included in the histogram can be either determined automatically (param: auto_mode) by two different methods or can be set directly by the user (param: max_intensity).

Changing any of the parameters will invalidate the S/N values (which will invoke a recomputation on the next request).

Note

If more than 20 percent of windows have less than min_required_elements of elements, a warning is issued to stderr and noise estimates in those windows are set to the constant noise_for_empty_window.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
max_intensity	int	-1	min: -1	maximal intensity considered for histogram construction. By default, it will be calculated automatically (see auto_mode). Only provide this parameter if you know what you are doing (and change 'auto_mode' to '-1')! All intensities EQUAL/ABOVE 'max_intensity' will not be added to the histogram. If you choose 'max_intensity' too small, the noise estimate might be too small as well. If chosen too big, the bins become quite large (which you could counter by increasing 'bin_count', which increases runtime).
auto_max_stdev_factor	float	3.0	min: 0.0 max: 999.0	parameter for 'max_intensity' estimation (if 'auto_mode' == 0): mean + 'auto_max_stdev_factor' * stdev
auto_max_percentile	int	95	min: 0 max: 100	parameter for 'max_intensity' estimation (if 'auto_mode' == 1): auto_max_percentile th percentile
auto_mode	int	0	min: -1 max: 1	method to use to determine maximal intensity: -1 --> use 'max_intensity'; 0 --> 'auto_max_stdev_factor' method (default); 1 --> 'auto_max_percentile' method
win_len	float	200.0	min: 1.0	window length in Thomson
bin_count	int	30	min: 3	number of bins for intensity values
stdev_mp	float	3.0	min: 0.01 max: 999.0	multiplier for stdev
min_required_elements	int	10	min: 1	minimum number of elements required in a window (otherwise it is considered sparse)
noise_for_empty_window	float	1.0e20		noise value used for sparse windows

Note:

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

Member Typedef Documentation

GaussianEstimate

template<typename Container = MSSpectrum>

typedef SignalToNoiseEstimator<Container>::GaussianEstimate GaussianEstimate

PeakIterator

template<typename Container = MSSpectrum>

typedef SignalToNoiseEstimator<Container>::PeakIterator PeakIterator

PeakType

template<typename Container = MSSpectrum>

typedef SignalToNoiseEstimator<Container>::PeakType PeakType

Member Enumeration Documentation

IntensityThresholdCalculation

template<typename Container = MSSpectrum>

enum IntensityThresholdCalculation

method to use for estimating the maximal intensity that is used for histogram calculation

Enumerator
MANUAL
AUTOMAXBYSTDEV
AUTOMAXBYPERCENT

Constructor & Destructor Documentation

SignalToNoiseEstimatorMeanIterative() [1/2]

template<typename Container = MSSpectrum>

SignalToNoiseEstimatorMeanIterative ( )

inline

default constructor

References DefaultParamHandler::defaults_, DefaultParamHandler::defaultsToParam_(), Param::setMaxFloat(), Param::setMaxInt(), Param::setMinFloat(), Param::setMinInt(), DefaultParamHandler::setName(), and Param::setValue().

SignalToNoiseEstimatorMeanIterative() [2/2]

template<typename Container = MSSpectrum>

SignalToNoiseEstimatorMeanIterative ( const SignalToNoiseEstimatorMeanIterative< Container > &  source )

inline

Copy Constructor.

References SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

~SignalToNoiseEstimatorMeanIterative()

template<typename Container = MSSpectrum>

~SignalToNoiseEstimatorMeanIterative ( )

inlineoverride

Destructor.

Member Function Documentation

computeSTN_()

template<typename Container = MSSpectrum>

void computeSTN_ ( const Container &  c )

inlineoverrideprotectedvirtual

calculate StN values for all datapoints given, by using a sliding window approach

Parameters

[in]

c

raw data

Exceptions

Throws

Exception::InvalidValue

start progress estimation

Implements SignalToNoiseEstimator< Container >.

References SignalToNoiseEstimatorMeanIterative< Container >::auto_max_percentile_, SignalToNoiseEstimatorMeanIterative< Container >::auto_max_stdev_Factor_, SignalToNoiseEstimatorMeanIterative< Container >::auto_mode_, SignalToNoiseEstimatorMeanIterative< Container >::AUTOMAXBYPERCENT, SignalToNoiseEstimatorMeanIterative< Container >::AUTOMAXBYSTDEV, SignalToNoiseEstimatorMeanIterative< Container >::bin_count_, ProgressLogger::endProgress(), SignalToNoiseEstimator< Container >::estimate_(), SignalToNoiseEstimatorMeanIterative< Container >::max_intensity_, SignalToNoiseEstimator< Container >::GaussianEstimate::mean, SignalToNoiseEstimatorMeanIterative< Container >::min_required_elements_, SignalToNoiseEstimatorMeanIterative< Container >::noise_for_empty_window_, ProgressLogger::setProgress(), ProgressLogger::startProgress(), SignalToNoiseEstimatorMeanIterative< Container >::stdev_, SignalToNoiseEstimator< Container >::stn_estimates_, SignalToNoiseEstimator< Container >::GaussianEstimate::variance, and SignalToNoiseEstimatorMeanIterative< Container >::win_len_.

operator=()

template<typename Container = MSSpectrum>

SignalToNoiseEstimatorMeanIterative & operator= ( const SignalToNoiseEstimatorMeanIterative< Container > &  source )

inline

References SignalToNoiseEstimator< Container >::operator=(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

updateMembers_()

template<typename Container = MSSpectrum>

void updateMembers_ ( )

inlineoverrideprotectedvirtual

overridden function from DefaultParamHandler to keep members up to date, when a parameter is changed

Reimplemented from DefaultParamHandler.

References SignalToNoiseEstimatorMeanIterative< Container >::auto_max_percentile_, SignalToNoiseEstimatorMeanIterative< Container >::auto_max_stdev_Factor_, SignalToNoiseEstimatorMeanIterative< Container >::auto_mode_, SignalToNoiseEstimatorMeanIterative< Container >::bin_count_, Param::getValue(), SignalToNoiseEstimatorMeanIterative< Container >::max_intensity_, SignalToNoiseEstimatorMeanIterative< Container >::min_required_elements_, SignalToNoiseEstimatorMeanIterative< Container >::noise_for_empty_window_, DefaultParamHandler::param_, SignalToNoiseEstimatorMeanIterative< Container >::stdev_, SignalToNoiseEstimator< Container >::stn_estimates_, and SignalToNoiseEstimatorMeanIterative< Container >::win_len_.

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::operator=(), and SignalToNoiseEstimatorMeanIterative< Container >::SignalToNoiseEstimatorMeanIterative().

Member Data Documentation

auto_max_percentile_

template<typename Container = MSSpectrum>

double auto_max_percentile_

protected

parameter for initial automatic estimation of "max_intensity_" percentile or a stdev

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

auto_max_stdev_Factor_

template<typename Container = MSSpectrum>

double auto_max_stdev_Factor_

protected

parameter for initial automatic estimation of "max_intensity_": a stdev multiplier

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

auto_mode_

template<typename Container = MSSpectrum>

int auto_mode_

protected

determines which method shall be used for estimating "max_intensity_". valid are MANUAL=-1, AUTOMAXBYSTDEV=0 or AUTOMAXBYPERCENT=1

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

bin_count_

template<typename Container = MSSpectrum>

int bin_count_

protected

number of bins in the histogram

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

max_intensity_

template<typename Container = MSSpectrum>

double max_intensity_

protected

maximal intensity considered during binning (values above get discarded)

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

min_required_elements_

template<typename Container = MSSpectrum>

int min_required_elements_

protected

minimal number of elements a window needs to cover to be used

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

noise_for_empty_window_

template<typename Container = MSSpectrum>

double noise_for_empty_window_

protected

used as noise value for windows which cover less than "min_required_elements_" use a very high value if you want to get a low S/N result

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

stdev_

template<typename Container = MSSpectrum>

double stdev_

protected

multiplier for the stdev of intensities

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().

win_len_

template<typename Container = MSSpectrum>

double win_len_

protected

range of data points which belong to a window in Thomson

Referenced by SignalToNoiseEstimatorMeanIterative< Container >::computeSTN_(), and SignalToNoiseEstimatorMeanIterative< Container >::updateMembers_().