casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > Class Template Reference

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

#include <FitToHalfStatistics.h>

Inheritance diagram for casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >:

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
virtual	~FitToHalfStatistics ()
FitToHalfStatistics< CASA_STATP > &	operator= (const FitToHalfStatistics< CASA_STATP > &other)
	copy semantics
virtual StatisticsData::ALGORITHM	algorithm () const
	get the algorithm that this object uses for computing stats
AccumType	getMedian (CountedPtr< uInt64 > knownNpts=NULL, CountedPtr< AccumType > knownMin=NULL, CountedPtr< AccumType > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt64 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, CountedPtr< uInt64 > knownNpts=NULL, CountedPtr< AccumType > knownMin=NULL, CountedPtr< AccumType > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt64 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 (CountedPtr< uInt64 > knownNpts=NULL, CountedPtr< AccumType > knownMin=NULL, CountedPtr< AccumType > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt64 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, CountedPtr< uInt64 > knownNpts=NULL, CountedPtr< AccumType > knownMin=NULL, CountedPtr< AccumType > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt64 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.
Static Public Attributes
static const AccumType	TWO
Protected Member Functions
virtual void	_clearData ()
virtual StatsData< AccumType >	_getInitialStats () const
StatsData< AccumType >	_getStatistics ()
StatsData< AccumType > &	_getStatsData ()
	retreive stats structure.
const StatsData< AccumType > &	_getStatsData () const
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, Int64 nr, uInt dataStride)
	no weights, no mask, no ranges
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude)
	no weights, no mask
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride)
void	_unweightedStats (StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, Int64 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, Int64 nr, uInt dataStride)
	has weights, but no mask, no ranges
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude)
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride)
void	_weightedStats (StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude)
Private Member Functions
void	_getRealMinMax (CountedPtr< AccumType > &realMin, CountedPtr< AccumType > &realMax, CountedPtr< AccumType > knownMin, CountedPtr< AccumType > knownMax)
void	_setRange ()
Private Attributes
FitToHalfStatisticsData::CENTER	_centerType
Bool	_useLower
AccumType	_centerValue
StatsData< AccumType >	_statsData
Bool	_doMedAbsDevMed
Bool	_rangeIsSet
CountedPtr< AccumType >	_realMax
	these are the max and min for the real portion of the dataset
CountedPtr< AccumType >	_realMin

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.

Definition at line 47 of file FitToHalfStatistics.h.

Constructor & Destructor Documentation

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

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

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

Member Function Documentation

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

virtual void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_clearData ( ) [protected, virtual]

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

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

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

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

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

void casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getRealMinMax	(	CountedPtr< AccumType > &	realMin,
		CountedPtr< AccumType > &	realMax,
		CountedPtr< AccumType >	knownMin,
		CountedPtr< AccumType >	knownMax
	)			`[private]`

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

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

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

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

const StatsData<AccumType>& casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getStatsData ( ) const [inline, protected, virtual]

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 164 of file FitToHalfStatistics.h.

References casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_statsData.

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

StatsData<AccumType>& casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getStatsData ( ) [inline, protected, virtual]

retreive stats structure.

Allows derived classes to maintain their own StatsData structs.

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 162 of file FitToHalfStatistics.h.

References casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_statsData.

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

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

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,
		Int64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride,
		const DataRanges &	ranges,
		Bool	isInclude
	)			`[protected]`

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,
		Int64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride
	)			`[protected]`

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,
		Int64	nr,
		uInt	dataStride,
		const DataRanges &	ranges,
		Bool	isInclude
	)			`[protected]`

no weights, no mask

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,
		Int64	nr,
		uInt	dataStride
	)			`[protected]`

no weights, no mask, no ranges

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]

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,
		Int64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride,
		const DataRanges &	ranges,
		Bool	isInclude
	)			`[protected]`

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,
		Int64	nr,
		uInt	dataStride,
		const MaskIterator &	maskBegin,
		uInt	maskStride
	)			`[protected]`

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,
		Int64	nr,
		uInt	dataStride,
		const DataRanges &	ranges,
		Bool	isInclude
	)			`[protected]`

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,
		Int64	nr,
		uInt	dataStride
	)			`[protected]`

has weights, but no mask, no ranges

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

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

get the algorithm that this object uses for computing stats

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 68 of file FitToHalfStatistics.h.

References casacore::StatisticsData::FITTOHALF.

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

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

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

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

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

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

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,
		CountedPtr< uInt64 >	knownNpts = `NULL`,
		CountedPtr< AccumType >	knownMin = `NULL`,
		CountedPtr< AccumType >	knownMax = `NULL`,
		uInt	binningThreshholdSizeBytes = `4096 *4096`,
		Bool	persistSortedArray = `False`,
		uInt64	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 used (although passing them in 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 exactly 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.

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.

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 >.

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,
		CountedPtr< uInt64 >	knownNpts = `NULL`,
		CountedPtr< AccumType >	knownMin = `NULL`,
		CountedPtr< AccumType >	knownMax = `NULL`,
		uInt	binningThreshholdSizeBytes = `4096 *4096`,
		Bool	persistSortedArray = `False`,
		uInt64	nBins = `10000`
	)

Get the specified quantiles.

fractions must be between 0 and 1, noninclusive.

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

Reimplemented from casacore::ConstrainedRangeStatistics< CASA_STATP >.

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 fence factor (_f), which was set at object construction.

Reimplemented from casacore::ConstrainedRangeStatistics< CASA_STATP >.

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 >.

Member Data Documentation

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 228 of file FitToHalfStatistics.h.

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

AccumType casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_centerValue [private]

Definition at line 230 of file FitToHalfStatistics.h.

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

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

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 232 of file FitToHalfStatistics.h.

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

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

Definition at line 232 of file FitToHalfStatistics.h.

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

CountedPtr<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 234 of file FitToHalfStatistics.h.

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

CountedPtr<AccumType> casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_realMin [private]

Definition at line 234 of file FitToHalfStatistics.h.

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

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

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

Definition at line 231 of file FitToHalfStatistics.h.

Referenced by casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_getStatsData().

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

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

Definition at line 229 of file FitToHalfStatistics.h.

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 51 of file FitToHalfStatistics.h.

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

casacore/scimath/Mathematics/FitToHalfStatistics.h

casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > Class Template Reference

Public Member Functions

Static Public Attributes

Protected Member Functions

Private Member Functions

Private Attributes

Detailed Description

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

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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