Class to calculate statistics using the so-called Chauvenet criterion. More...

#include <ChauvenetCriterionStatistics.h>

Public Member Functions
	ChauvenetCriterionStatistics ()=delete
	ChauvenetCriterionStatistics (Double zscore=-1, Int maxIterations=0)
	If zscore is not negative, use that value to discard outliers beyond zscore standard deviations from the mean, and compute statistics based on the remaining data.
	ChauvenetCriterionStatistics (const ChauvenetCriterionStatistics< CASA_STATP > &other)
virtual	~ChauvenetCriterionStatistics ()
ChauvenetCriterionStatistics< CASA_STATP > &	operator= (const ChauvenetCriterionStatistics< 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
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.
uInt	getNiter () const
	get the number of iterations
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 uInt64	getNPts ()
	scan the dataset(s) that have been added, and find the number of good points.
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.
virtual void	setStatsToCalculate (std::set< StatisticsData::STATS > &stats)
	Provide guidance to algorithms by specifying a priori which statistics the caller would like calculated.
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.

Private Member Functions
void	_setRange ()

Private Attributes
Double	_zscore
Int	_maxIterations
Bool	_rangeIsSet
uInt	_niter

Additional Inherited Members
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 StatsData< CASA_STATP >	_getStatistics ()
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
virtual StatsData< CASA_STATP >	_getInitialStats () const
virtual StatsData< CASA_STATP > &	_getStatsData ()
	Retrieve stats structure.
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.

Detailed Description

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

Class to calculate statistics using the so-called Chauvenet criterion.

This method iteratively calculates statistics by discarding outliers on the basis of Chauvenet's criterion, until the specified maximum number of iterations is reached, or the final iteration results in no additional points being discarded. Alternatively, one can specify a z-score which indicates the number of standard deviations beyond which to discard points, which is held fixed while iterating.

When instantiated, objects of this class use a ConstrainedRangeQuantileComputer object for computing quantile-like statistics. See class documentation for StatisticsAlgorithm for details of QuantileComputer classes.

Definition at line 55 of file ChauvenetCriterionStatistics.h.

Constructor & Destructor Documentation

◆ ChauvenetCriterionStatistics() [1/3]

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

casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::ChauvenetCriterionStatistics ( )

delete

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

◆ ChauvenetCriterionStatistics() [2/3]

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

casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::ChauvenetCriterionStatistics	(	Double	zscore = -1,
		Int	maxIterations = 0 )

If zscore is not negative, use that value to discard outliers beyond zscore standard deviations from the mean, and compute statistics based on the remaining data.

If zscore is negative, use Chauvenet's Criterion to determine which outliers to discard. maxIterations is the maximum number of iterations to use before stopping. If negative, continue iterating until the set zscore or Chauvenet's criterion is met (ie that there are no remaining outliers).

◆ ChauvenetCriterionStatistics() [3/3]

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

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

References ChauvenetCriterionStatistics().

◆ ~ChauvenetCriterionStatistics()

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

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

virtual

Member Function Documentation

◆ _setRange()

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

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

private

◆ algorithm()

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

virtual StatisticsData::ALGORITHM casacore::ChauvenetCriterionStatistics< 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 85 of file ChauvenetCriterionStatistics.h.

References casacore::StatisticsData::CHAUVENETCRITERION.

◆ clone()

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

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

virtual

Clone this instance.

Reimplemented from casacore::ClassicalStatistics< CASA_STATP >.

◆ getNiter()

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

uInt casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::getNiter ( ) const

inline

get the number of iterations

Definition at line 99 of file ChauvenetCriterionStatistics.h.

References _niter.

◆ operator=()

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

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

copy semantics

References ChauvenetCriterionStatistics().

◆ reset()

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

virtual void casacore::ChauvenetCriterionStatistics< 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 >.

◆ setCalculateAsAdded()

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

void casacore::ChauvenetCriterionStatistics< 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

◆ _maxIterations

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

Int casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_maxIterations

private

Definition at line 104 of file ChauvenetCriterionStatistics.h.

◆ _niter

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

uInt casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_niter

private

Definition at line 106 of file ChauvenetCriterionStatistics.h.

Referenced by getNiter().

◆ _rangeIsSet

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

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

private

Definition at line 105 of file ChauvenetCriterionStatistics.h.

◆ _zscore

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

Double casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::_zscore

private

Definition at line 103 of file ChauvenetCriterionStatistics.h.

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

scimath/StatsFramework/ChauvenetCriterionStatistics.h

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ ChauvenetCriterionStatistics() [1/3]

◆ ChauvenetCriterionStatistics() [2/3]

◆ ChauvenetCriterionStatistics() [3/3]

◆ ~ChauvenetCriterionStatistics()

Member Function Documentation

◆ _setRange()

◆ algorithm()

◆ clone()

◆ getNiter()

◆ operator=()

◆ reset()

◆ setCalculateAsAdded()

Member Data Documentation

◆ _maxIterations

◆ _niter

◆ _rangeIsSet

◆ _zscore