Class to calculate statistics using the so-called fit to half algorithm. More...

#include <FitToHalfStatistics.h>

Public Member Functions
	FitToHalfStatistics (FitToHalfStatisticsData::CENTER center=FitToHalfStatisticsData::CMEAN, FitToHalfStatisticsData::USE_DATA useData=FitToHalfStatisticsData::LE_CENTER, AccumType value=0)
	value is only used if center=CVALUE
	FitToHalfStatistics (const FitToHalfStatistics< CASA_STATP > &other)
	copy semantics
virtual	~FitToHalfStatistics ()
FitToHalfStatistics< CASA_STATP > &	operator= (const FitToHalfStatistics< CASA_STATP > &other)
	copy semantics
virtual StatisticsAlgorithm< CASA_STATP > *	clone () const
	Clone this instance.
virtual StatisticsData::ALGORITHM	algorithm () const
	get the algorithm that this object uses for computing stats
AccumType	getMedian (std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< AccumType > knownMin=nullptr, std::shared_ptr< AccumType > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	The median is just the center value, so none of the parameters to this method are used.
AccumType	getMedianAndQuantiles (std::map< Double, AccumType > &quantiles, const std::set< Double > &fractions, std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< AccumType > knownMin=nullptr, std::shared_ptr< AccumType > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	In the following group of methods, if the size of the composite dataset is smaller than binningThreshholdSizeBytes, the composite dataset will be (perhaps partially) sorted and persisted in memory during the call.
AccumType	getMedianAbsDevMed (std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< AccumType > knownMin=nullptr, std::shared_ptr< AccumType > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	get the median of the absolute deviation about the median of the data.
std::map< Double, AccumType >	getQuantiles (const std::set< Double > &fractions, std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< AccumType > knownMin=nullptr, std::shared_ptr< AccumType > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	Get the specified quantiles.
virtual void	getMinMax (AccumType &mymin, AccumType &mymax)
	scan the dataset(s) that have been added, and find the min and max.
uInt64	getNPts ()
	scan the dataset(s) that have been added, and find the number of good points.
virtual void	reset ()
	reset object to initial state.
void	setCalculateAsAdded (Bool c)
	This class does not allow statistics to be calculated as datasets are added, so an exception will be thrown if c is True.
virtual void	setStatsToCalculate (std::set< StatisticsData::STATS > &stats)
	Override base class method by requiring mean to be computed in addition to what is added in stats if the requested center value is CMEAN.
Public Member Functions inherited from casacore::ConstrainedRangeStatistics< CASA_STATP >
	ConstrainedRangeStatistics ()=delete
virtual	~ConstrainedRangeStatistics ()
virtual CASA_STATP	getMedian (std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< CASA_STATP > knownMin=nullptr, std::shared_ptr< CASA_STATP > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	In the following group of methods, if the size of the composite dataset is smaller than binningThreshholdSizeBytes, the composite dataset will be (perhaps partially) sorted and persisted in memory during the call.
virtual CASA_STATP	getMedianAbsDevMed (std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< CASA_STATP > knownMin=nullptr, std::shared_ptr< CASA_STATP > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	get the median of the absolute deviation about the median of the data.
virtual CASA_STATP	getMedianAndQuantiles (std::map< Double, CASA_STATP > &quantileToValue, const std::set< Double > &quantiles, std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< CASA_STATP > knownMin=nullptr, std::shared_ptr< CASA_STATP > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	If one needs to compute both the median and quantile values, it is better to call getMedianAndQuantiles() rather than getMedian() and getQuantiles() separately, as the first will scan large data sets fewer times than calling the seperate methods.
virtual std::map< Double, CASA_STATP >	getQuantiles (const std::set< Double > &quantiles, std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< CASA_STATP > knownMin=nullptr, std::shared_ptr< CASA_STATP > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	Get the specified quantiles.
virtual void	getMinMax (CASA_STATP &mymin, CASA_STATP &mymax)
	get the min and max of the data set
virtual LocationType	getStatisticIndex (StatisticsData::STATS stat)
	see base class description
Public Member Functions inherited from casacore::ClassicalStatistics< CASA_STATP >
	ClassicalStatistics ()
virtual	~ClassicalStatistics ()
ClassicalStatistics &	operator= (const ClassicalStatistics &other)
	copy semantics
virtual void	getMinMaxNpts (uInt64 &npts, CASA_STATP &mymin, CASA_STATP &mymax)
virtual void	setDataProvider (StatsDataProvider< CASA_STATP > *dataProvider)
	An exception will be thrown if setCalculateAsAdded(True) has been called.
void	setQuantileComputer (std::shared_ptr< ClassicalQuantileComputer< CASA_STATP > > qc)
	Allow derived objects to set the quantile computer object.
Public Member Functions inherited from casacore::StatisticsAlgorithm< CASA_STATP >
virtual	~StatisticsAlgorithm ()
void	addData (const DataIterator &first, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False)
	Add a dataset to an existing set of datasets on which statistics are to be calculated.
CASA_STATP	getQuantile (Double quantile, std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< CASA_STATP > knownMin=nullptr, std::shared_ptr< CASA_STATP > knownMax=nullptr, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
	Purposefully not virtual.
CASA_STATP	getStatistic (StatisticsData::STATS stat)
	get the value of the specified statistic.
StatsData< CASA_STATP >	getStatistics ()
	Return statistics.
void	setData (const DataIterator &first, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False)
	setdata() clears any current datasets or data provider and then adds the specified data set as the first dataset in the (possibly new) set of data sets for which statistics are to be calculated.

Static Public Attributes
static const AccumType	TWO

Protected Member Functions
virtual StatsData< AccumType >	_getInitialStats () const
virtual StatsData< AccumType >	_getStatistics ()
StatsData< AccumType > &	_getStatsData ()
	Retrieve stats structure.
const StatsData< AccumType > &	_getStatsData () const
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride)
	no weights, no mask, no ranges
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude)
	no weights, no mask
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride)
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude)
void	_updateDataProviderMaxMin (const StatsData< AccumType > &threadStats)
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride)
	has weights, but no mask, no ranges
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude)
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride)
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude)
Protected Member Functions inherited from casacore::ConstrainedRangeStatistics< CASA_STATP >
ConstrainedRangeStatistics< CASA_STATP > &	operator= (const ConstrainedRangeStatistics< CASA_STATP > &other)
	copy semantics
virtual void	_accumNpts (uInt64 &npts, const DataIterator &dataStart, uInt64 nr, uInt dataStride) const
	scan through the data set to determine the number of good (unmasked, weight > 0, within range) points.
virtual CASA_STATP	_getStatistic (StatisticsData::STATS stat)
virtual void	_minMax (std::shared_ptr< CASA_STATP > &mymin, std::shared_ptr< CASA_STATP > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride) const
virtual void	_minMaxNpts (uInt64 &npts, std::shared_ptr< CASA_STATP > &mymin, std::shared_ptr< CASA_STATP > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride) const
	Sometimes we want the min, max, and npts all in one scan.
void	_setRange (std::shared_ptr< std::pair< CASA_STATP, CASA_STATP > > r)
	This method is purposefully non-virtual.
virtual void	_unweightedStats (StatsData< CASA_STATP > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride)
	no weights, no mask, no ranges
virtual void	_weightedStats (StatsData< CASA_STATP > &stats, LocationType &location, const DataIterator &dataBegin, const DataIterator &weightsBegin, uInt64 nr, uInt dataStride)
	has weights, but no mask, no ranges
Protected Member Functions inherited from casacore::ClassicalStatistics< CASA_STATP >
void	_accumulate (StatsData< CASA_STATP > &stats, const CASA_STATP &datum, const LocationType &location)
void	_addData ()
	Allows derived classes to do things after data is set or added.
void	_clearStats ()
Bool	_getDoMaxMin () const
std::shared_ptr< StatisticsAlgorithmQuantileComputer< CASA_STATP > >	_getQuantileComputer ()
virtual void	_updateDataProviderMaxMin (const StatsData< CASA_STATP > &threadStats)
Protected Member Functions inherited from casacore::StatisticsAlgorithm< CASA_STATP >
	StatisticsAlgorithm ()
StatisticsAlgorithm &	operator= (const StatisticsAlgorithm &other)
	use copy semantics, except for the data provider which uses reference semantics
const StatisticsDataset< CASA_STATP > &	_getDataset () const
	These methods are purposefully not virtual.
const std::set< StatisticsData::STATS >	_getStatsToCalculate () const
virtual const std::set< StatisticsData::STATS > &	_getUnsupportedStatistics () const
void	_setUnsupportedStatistics (const std::set< StatisticsData::STATS > &stats)
	Derived classes should normally call this in their constructors, if applicable.

Private Member Functions
void	_getMinMax (std::shared_ptr< AccumType > &realMin, std::shared_ptr< AccumType > &realMax, std::shared_ptr< AccumType > knownMin, std::shared_ptr< AccumType > knownMax)
	get the min max of the entire (real + virtual) data set.
void	_getRealMinMax (AccumType &realMin, AccumType &realMax)
	get the min/max of the real portion only of the dataset
void	_setRange ()

Private Attributes
FitToHalfStatisticsData::CENTER	_centerType
Bool	_useLower
AccumType	_centerValue
StatsData< AccumType >	_statsData
Bool	_doMedAbsDevMed
Bool	_rangeIsSet
std::shared_ptr< AccumType >	_realMax
	these are the max and min for the real portion of the dataset
std::shared_ptr< AccumType >	_realMin
Bool	_isNullSet
std::shared_ptr< std::pair< AccumType, AccumType > >	_range
	This is used for convenience and performance.

Detailed Description

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>
class casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >

Class to calculate statistics using the so-called fit to half algorithm.

In this algorithm, a center value is specified, and only points greater or equal or less or equal this value are included. Furthermore, each of the included points is reflected about the center value, and these virtual points are added to the included points and the union of sets of included real points and virtual points are used for computing statistics. The specified center point is therefore the mean and median of the resulting distribution, and the total number of points is exactly twice the number of real data points that are included.

This class uses a ConstrainedRangeQuantileComputer object for computing quantile-like statistics. See class documentation for StatisticsAlgorithm for details regarding QuantileComputer classes.

Definition at line 54 of file FitToHalfStatistics.h.

Constructor & Destructor Documentation

◆ FitToHalfStatistics() [1/2]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::FitToHalfStatistics	(	FitToHalfStatisticsData::CENTER	center = FitToHalfStatisticsData::CMEAN,
		FitToHalfStatisticsData::USE_DATA	useData = FitToHalfStatisticsData::LE_CENTER,
		AccumType	value = 0 )

value is only used if center=CVALUE

References casacore::FitToHalfStatisticsData::CMEAN, casacore::FitToHalfStatisticsData::LE_CENTER, and casacore::NewDelAllocator< T >::value.

Referenced by FitToHalfStatistics(), and operator=().

◆ FitToHalfStatistics() [2/2]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::FitToHalfStatistics ( const FitToHalfStatistics< CASA_STATP > & other )

copy semantics

References FitToHalfStatistics().

◆ ~FitToHalfStatistics()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::~FitToHalfStatistics ( )

virtual

Member Function Documentation

◆ _getInitialStats()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual StatsData< AccumType > casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getInitialStats ( ) const

protectedvirtual

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

◆ _getMinMax()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getMinMax	(	std::shared_ptr< AccumType > &	realMin,
		std::shared_ptr< AccumType > &	realMax,
		std::shared_ptr< AccumType >	knownMin,
		std::shared_ptr< AccumType >	knownMax )

private

get the min max of the entire (real + virtual) data set.

Only used for quantile computation

◆ _getRealMinMax()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getRealMinMax	(	AccumType &	realMin,
		AccumType &	realMax )

private

get the min/max of the real portion only of the dataset

◆ _getStatistics()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual StatsData< AccumType > casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getStatistics ( )

protectedvirtual

Reimplemented from casacore::ConstrainedRangeStatistics< CASA_STATP >.

◆ _getStatsData() [1/2]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

StatsData< AccumType > & casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getStatsData ( )

inlineprotectedvirtual

Retrieve stats structure.

Allows derived classes to maintain their own StatsData structs.

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 187 of file FitToHalfStatistics.h.

References _statsData.

◆ _getStatsData() [2/2]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

const StatsData< AccumType > & casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getStatsData ( ) const

inlineprotected

Definition at line 189 of file FitToHalfStatistics.h.

References _statsData.

◆ _setRange()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_setRange ( )

private

◆ _unweightedStats() [1/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_unweightedStats	(	StatsData< AccumType > &	stats,
		uInt64 &	ngood,
		LocationType &	location,
		const DataIterator &	dataBegin,
		uInt64	nr,
		uInt	dataStride )

protected

no weights, no mask, no ranges

◆ _unweightedStats() [2/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_unweightedStats	(	StatsData< AccumType > &	stats,
		uInt64 &	ngood,
		LocationType &	location,
		const DataIterator &	dataBegin,
		uInt64	nr,
		uInt	dataStride,
		const DataRanges &	ranges,
		Bool	isInclude )

protected

no weights, no mask

References DataRanges.

◆ _unweightedStats() [3/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_unweightedStats	(	StatsData< AccumType > &	stats,
		uInt64 &	ngood,
		LocationType &	location,
		const DataIterator &	dataBegin,
		uInt64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride )

protected

◆ _unweightedStats() [4/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_unweightedStats	(	StatsData< AccumType > &	stats,
		uInt64 &	ngood,
		LocationType &	location,
		const DataIterator &	dataBegin,
		uInt64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride,
		const DataRanges &	ranges,
		Bool	isInclude )

protected

References DataRanges.

◆ _updateDataProviderMaxMin()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_updateDataProviderMaxMin ( const StatsData< AccumType > & threadStats )

protected

◆ _weightedStats() [1/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_weightedStats	(	StatsData< AccumType > &	stats,
		LocationType &	location,
		const DataIterator &	dataBegin,
		const WeightsIterator &	weightBegin,
		uInt64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride )

protected

◆ _weightedStats() [2/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_weightedStats	(	StatsData< AccumType > &	stats,
		LocationType &	location,
		const DataIterator &	dataBegin,
		const WeightsIterator &	weightBegin,
		uInt64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride,
		const DataRanges &	ranges,
		Bool	isInclude )

protected

References DataRanges.

◆ _weightedStats() [3/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_weightedStats	(	StatsData< AccumType > &	stats,
		LocationType &	location,
		const DataIterator &	dataBegin,
		const WeightsIterator &	weightsBegin,
		uInt64	nr,
		uInt	dataStride )

protected

has weights, but no mask, no ranges

◆ _weightedStats() [4/4]

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_weightedStats	(	StatsData< AccumType > &	stats,
		LocationType &	location,
		const DataIterator &	dataBegin,
		const WeightsIterator &	weightsBegin,
		uInt64	nr,
		uInt	dataStride,
		const DataRanges &	ranges,
		Bool	isInclude )

protected

References DataRanges.

◆ algorithm()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual StatisticsData::ALGORITHM casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::algorithm ( ) const

inlinevirtual

get the algorithm that this object uses for computing stats

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 82 of file FitToHalfStatistics.h.

References casacore::StatisticsData::FITTOHALF.

◆ clone()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual StatisticsAlgorithm< CASA_STATP > * casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::clone ( ) const

virtual

Clone this instance.

Caller is responsible for deleting the returned pointer.

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

◆ getMedian()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

AccumType casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getMedian	(	std::shared_ptr< uInt64 >	knownNpts = nullptr,
		std::shared_ptr< AccumType >	knownMin = nullptr,
		std::shared_ptr< AccumType >	knownMax = nullptr,
		uInt	binningThreshholdSizeBytes = 4096 *4096,
		Bool	persistSortedArray = False,
		uInt	nBins = 10000 )

The median is just the center value, so none of the parameters to this method are used.

References casacore::False.

◆ getMedianAbsDevMed()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

AccumType casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getMedianAbsDevMed	(	std::shared_ptr< uInt64 >	knownNpts = nullptr,
		std::shared_ptr< AccumType >	knownMin = nullptr,
		std::shared_ptr< AccumType >	knownMax = nullptr,
		uInt	binningThreshholdSizeBytes = 4096 *4096,
		Bool	persistSortedArray = False,
		uInt	nBins = 10000 )

get the median of the absolute deviation about the median of the data.

References casacore::False.

◆ getMedianAndQuantiles()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

AccumType casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getMedianAndQuantiles	(	std::map< Double, AccumType > &	quantiles,
		const std::set< Double > &	fractions,
		std::shared_ptr< uInt64 >	knownNpts = nullptr,
		std::shared_ptr< AccumType >	knownMin = nullptr,
		std::shared_ptr< AccumType >	knownMax = nullptr,
		uInt	binningThreshholdSizeBytes = 4096 *4096,
		Bool	persistSortedArray = False,
		uInt	nBins = 10000 )

In the following group of methods, if the size of the composite dataset is smaller than binningThreshholdSizeBytes, the composite dataset will be (perhaps partially) sorted and persisted in memory during the call.

In that case, and if persistSortedArray is True, this sorted array will remain in memory after the call and will be used on subsequent calls of this method when binningThreshholdSizeBytes is greater than the size of the composite dataset. If persistSortedArray is False, the sorted array will not be stored after this call completes and so any subsequent calls for which the dataset size is less than binningThreshholdSizeBytes, the dataset will be sorted from scratch. Values which are not included due to non-unity strides, are not included in any specified ranges, are masked, or have associated weights of zero are not considered as dataset members for quantile computations. If one has a priori information regarding the number of points (npts) and/or the minimum and maximum values of the data set, these can be supplied to improve performance. Note however, that if these values are not correct, the resulting median and/or quantile values will also not be correct (although see the following notes regarding max/min). Note that if this object has already had getStatistics() called, and the min and max were calculated, there is no need to pass these values in as they have been stored internally and will be used (although passing them explicitly shouldn't hurt anything). If provided, npts, the number of points falling in the specified ranges which are not masked and have weights > 0, should be correct. min can be less than the true minimum, and max can be greater than the True maximum, but for best performance, these should be as close to the actual min and max as possible (and ideally the actual min/max values of the data set).

References casacore::False.

◆ getMinMax()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getMinMax	(	AccumType &	mymin,
		AccumType &	mymax )

virtual

scan the dataset(s) that have been added, and find the min and max.

This method may be called even if setStatsToCaclulate has been called and MAX and MIN has been excluded.

◆ getNPts()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

uInt64 casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getNPts ( )

virtual

scan the dataset(s) that have been added, and find the number of good points.

This method may be called even if setStatsToCaclulate has been called and NPTS has been excluded. If setCalculateAsAdded(True) has previously been called after this object has been (re)initialized, an exception will be thrown.

Reimplemented from casacore::ConstrainedRangeStatistics< CASA_STATP >.

◆ getQuantiles()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

std::map< Double, AccumType > casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getQuantiles	(	const std::set< Double > &	fractions,
		std::shared_ptr< uInt64 >	knownNpts = nullptr,
		std::shared_ptr< AccumType >	knownMin = nullptr,
		std::shared_ptr< AccumType >	knownMax = nullptr,
		uInt	binningThreshholdSizeBytes = 4096 *4096,
		Bool	persistSortedArray = False,
		uInt	nBins = 10000 )

Get the specified quantiles.

fractions must be between 0 and 1, noninclusive.

References casacore::False.

◆ operator=()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

FitToHalfStatistics< CASA_STATP > & casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::operator= ( const FitToHalfStatistics< CASA_STATP > & other )

copy semantics

References FitToHalfStatistics().

◆ reset()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::reset ( )

virtual

reset object to initial state.

Clears all private fields including data, accumulators, global range. It does not affect the center type, center value, or which "side" to use which were set at construction.

Reimplemented from casacore::ConstrainedRangeStatistics< CASA_STATP >.

◆ setCalculateAsAdded()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::setCalculateAsAdded ( Bool c )

virtual

This class does not allow statistics to be calculated as datasets are added, so an exception will be thrown if c is True.

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

◆ setStatsToCalculate()

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

virtual void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::setStatsToCalculate ( std::set< StatisticsData::STATS > & stats )

virtual

Override base class method by requiring mean to be computed in addition to what is added in stats if the requested center value is CMEAN.

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Member Data Documentation

◆ _centerType

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

FitToHalfStatisticsData::CENTER casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_centerType

private

Definition at line 253 of file FitToHalfStatistics.h.

◆ _centerValue

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

AccumType casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_centerValue

private

Definition at line 255 of file FitToHalfStatistics.h.

◆ _doMedAbsDevMed

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

Bool casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_doMedAbsDevMed

private

Definition at line 257 of file FitToHalfStatistics.h.

◆ _isNullSet

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

Bool casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_isNullSet

private

Definition at line 260 of file FitToHalfStatistics.h.

◆ _range

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

std::shared_ptr<std::pair<AccumType, AccumType> > casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_range

private

This is used for convenience and performance.

It should always be the same as the _range value used in the base ConstrainedRangeStatistics object

Definition at line 264 of file FitToHalfStatistics.h.

◆ _rangeIsSet

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

Bool casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_rangeIsSet

private

Definition at line 257 of file FitToHalfStatistics.h.

◆ _realMax

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

std::shared_ptr<AccumType> casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_realMax

private

these are the max and min for the real portion of the dataset

Definition at line 259 of file FitToHalfStatistics.h.

◆ _realMin

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

std::shared_ptr<AccumType> casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_realMin

private

Definition at line 259 of file FitToHalfStatistics.h.

◆ _statsData

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

StatsData<AccumType> casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_statsData

private

Definition at line 256 of file FitToHalfStatistics.h.

Referenced by _getStatsData(), and _getStatsData().

◆ _useLower

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

Bool casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_useLower

private

Definition at line 254 of file FitToHalfStatistics.h.

◆ TWO

template<class AccumType, class DataIterator, class MaskIterator = const Bool *, class WeightsIterator = DataIterator>

const AccumType casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::TWO

static

Definition at line 58 of file FitToHalfStatistics.h.

The documentation for this class was generated from the following file:

scimath/StatsFramework/FitToHalfStatistics.h

Public Member Functions

Static Public Attributes

Protected Member Functions

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ FitToHalfStatistics() [1/2]

◆ FitToHalfStatistics() [2/2]

◆ ~FitToHalfStatistics()

Member Function Documentation

◆ _getInitialStats()

◆ _getMinMax()

◆ _getRealMinMax()

◆ _getStatistics()

◆ _getStatsData() [1/2]

◆ _getStatsData() [2/2]

◆ _setRange()

◆ _unweightedStats() [1/4]

◆ _unweightedStats() [2/4]

◆ _unweightedStats() [3/4]

◆ _unweightedStats() [4/4]

◆ _updateDataProviderMaxMin()

◆ _weightedStats() [1/4]

◆ _weightedStats() [2/4]

◆ _weightedStats() [3/4]

◆ _weightedStats() [4/4]

◆ algorithm()

◆ clone()

◆ getMedian()

◆ getMedianAbsDevMed()

◆ getMedianAndQuantiles()

◆ getMinMax()

◆ getNPts()

◆ getQuantiles()

◆ operator=()

◆ reset()

◆ setCalculateAsAdded()

◆ setStatsToCalculate()

Member Data Documentation

◆ _centerType

◆ _centerValue

◆ _doMedAbsDevMed

◆ _isNullSet

◆ _range

◆ _rangeIsSet

◆ _realMax

◆ _realMin

◆ _statsData

◆ _useLower

◆ TWO