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ConstrainedRangeStatistics.h
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//# Copyright (C) 2000,2001
//# Associated Universities, Inc. Washington DC, USA.
//#
//# This library is free software; you can redistribute it and/or modify it
//# under the terms of the GNU Library General Public License as published by
//# the Free Software Foundation; either version 2 of the License, or (at your
//# option) any later version.
//#
//# This library is distributed in the hope that it will be useful, but WITHOUT
//# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
//# FITNESS FOR A PARTICULAR PURPOSE. See the GNU Library General Public
//# License for more details.
//#
//# You should have received a copy of the GNU Library General Public License
//# along with this library; if not, write to the Free Software Foundation,
//# Inc., 675 Massachusetts Ave, Cambridge, MA 02139, USA.
//#
//# Correspondence concerning AIPS++ should be addressed as follows:
//# Internet email: casa-feedback@nrao.edu.
//# Postal address: AIPS++ Project Office
//# National Radio Astronomy Observatory
//# 520 Edgemont Road
//# Charlottesville, VA 22903-2475 USA
//#
#ifndef SCIMATH_CONSTRAINEDRANGESTATISTICS_H
#define SCIMATH_CONSTRAINEDRANGESTATISTICS_H
#include <casacore/casa/aips.h>
#include <casacore/scimath/StatsFramework/ClassicalStatistics.h>
#include <casacore/scimath/StatsFramework/ConstrainedRangeQuantileComputer.h>
#include <set>
#include <vector>
#include <utility>
namespace casacore {
// Abstract base class for statistics algorithms which are characterized by
// a range of good values. The range is usually calculated dynamically based
// on the entire distribution. The specifics of such calculations are
// delegated to derived classes.
template <
class AccumType, class DataIterator, class MaskIterator=const Bool*,
class WeightsIterator=DataIterator
>
class ConstrainedRangeStatistics : public ClassicalStatistics<CASA_STATP> {
public:
ConstrainedRangeStatistics() = delete;
virtual ~ConstrainedRangeStatistics();
// <group>
// In the following group of methods, if the size of the composite dataset
// is smaller than
// <src>binningThreshholdSizeBytes</src>, the composite dataset
// will be (perhaps partially) sorted and persisted in memory during the
// call. In that case, and if <src>persistSortedArray</src> is True, this
// sorted array will remain in memory after the call and will be used on
// subsequent calls of this method when
// <src>binningThreshholdSizeBytes</src> is greater than the size of the
// composite dataset. If <src>persistSortedArray</src> 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
// <src>binningThreshholdSizeBytes</src>, 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. <src>min</src> can be less than the true minimum, and
// <src>max</src> can be greater than the True maximum, but for best
// performance, these should be as close to the actual min and max as
// possible. In order for quantile computations to occur over multiple
// datasets, all datasets must be available. This means that if
// setCalculateAsAdded() was previously called by passing in a value of
// True, these methods will throw an exception as the previous call
// indicates that there is no guarantee that all datasets will be available.
// If one uses a data provider (by having called setDataProvider()), then
// this should not be an issue.
// get the median of the distribution.
// For a dataset with an odd number of good points, the median is just the
// value at index int(N/2) in the equivalent sorted dataset, where N is the
// number of points. For a dataset with an even number of points, the median
// is the mean of the values at indices int(N/2)-1 and int(N/2) in the
// sorted dataset.
virtual 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
);
// get the median of the absolute deviation about the median of the data.
virtual 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
);
// 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 separate methods. The return value is the median;
// the quantiles are returned in the <src>quantileToValue</src> map.
virtual AccumType getMedianAndQuantiles(
std::map<Double, AccumType>& quantileToValue,
const std::set<Double>& quantiles,
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. <src>quantiles</src> must be between 0 and
// 1, noninclusive.
virtual std::map<Double, AccumType> getQuantiles(
const std::set<Double>& quantiles,
std::shared_ptr<uInt64> knownNpts=nullptr,
std::shared_ptr<AccumType> knownMin=nullptr,
std::shared_ptr<AccumType> knownMax=NULL,
uInt binningThreshholdSizeBytes=4096*4096,
Bool persistSortedArray=False, uInt nBins=10000
);
// </group>
// get the min and max of the data set
virtual void getMinMax(AccumType& mymin, AccumType& mymax);
// 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.
virtual uInt64 getNPts();
// see base class description
virtual LocationType getStatisticIndex(StatisticsData::STATS stat);
// reset object to initial state. Clears all private fields including data,
// accumulators, global range.
virtual void reset();
protected:
// Concrete derived classes are responsible for providing an appropriate
// QuantileComputer object to the constructor, which is ultimately passed
// up the instantiation hierarchy and stored at the StatisticsAlgorithm
// level.
ConstrainedRangeStatistics(
std::shared_ptr<ConstrainedRangeQuantileComputer<CASA_STATP>> qc
);
// copy semantics
ConstrainedRangeStatistics(
const ConstrainedRangeStatistics<CASA_STATP>& other
);
// copy semantics
ConstrainedRangeStatistics<CASA_STATP>& operator=(
const ConstrainedRangeStatistics<CASA_STATP>& other
);
// <group>
// scan through the data set to determine the number of good (unmasked,
// weight > 0, within range) points. The first with no mask, no ranges, and
// no weights is trivial with npts = nr in this class, but is implemented
// here so that derived classes may override it.
virtual void _accumNpts(
uInt64& npts, const DataIterator& dataStart, uInt64 nr, uInt dataStride
) const;
virtual void _accumNpts(
uInt64& npts,
const DataIterator& dataStart, uInt64 nr, uInt dataStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _accumNpts(
uInt64& npts, const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride
) const;
virtual void _accumNpts(
uInt64& npts,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _accumNpts(
uInt64& npts, const DataIterator& dataBegin,
const WeightsIterator& weightsBegin, uInt64 nr, uInt dataStride
) const;
virtual void _accumNpts(
uInt64& npts, const DataIterator& dataBegin,
const WeightsIterator& weightsBegin, uInt64 nr, uInt dataStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _accumNpts(
uInt64& npts, const DataIterator& dataBegin,
const WeightsIterator& weightsBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _accumNpts(
uInt64& npts, const DataIterator& dataBegin,
const WeightsIterator& weightBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride
) const;
// </group>
virtual AccumType _getStatistic(StatisticsData::STATS stat);
virtual StatsData<AccumType> _getStatistics();
// <group>
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, const WeightsIterator& weightsBegin,
uInt64 nr, uInt dataStride
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, const WeightsIterator& weightsBegin,
uInt64 nr, uInt dataStride, const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, const WeightsIterator& weightsBegin,
uInt64 nr, uInt dataStride, const MaskIterator& maskBegin,
uInt maskStride, const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMax(
std::shared_ptr<AccumType>& mymin, std::shared_ptr<AccumType>& mymax,
const DataIterator& dataBegin, const WeightsIterator& weightBegin,
uInt64 nr, uInt dataStride, const MaskIterator& maskBegin,
uInt maskStride
) const;
// </group>
// <group>
// Sometimes we want the min, max, and npts all in one scan.
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin, uInt64 nr,
uInt dataStride
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin, uInt64 nr,
uInt dataStride, const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin, uInt64 nr,
uInt dataStride, const MaskIterator& maskBegin, uInt maskStride
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin, uInt64 nr,
uInt dataStride, const MaskIterator& maskBegin, uInt maskStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin,
const WeightsIterator& weightsBegin, uInt64 nr, uInt dataStride
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin,
const WeightsIterator& weightsBegin, uInt64 nr, uInt dataStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin,
const WeightsIterator& weightsBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride,
const DataRanges& ranges, Bool isInclude
) const;
virtual void _minMaxNpts(
uInt64& npts, std::shared_ptr<AccumType>& mymin,
std::shared_ptr<AccumType>& mymax, const DataIterator& dataBegin,
const WeightsIterator& weightBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride
) const;
// </group>
// This method is purposefully non-virtual. Derived classes
// should implement the version with no parameters.
void _setRange(std::shared_ptr<std::pair<AccumType, AccumType>> r);
// derived classes need to implement how to set their respective range
virtual void _setRange() = 0;
// <group>
// no weights, no mask, no ranges
virtual void _unweightedStats(
StatsData<AccumType>& stats, uInt64& ngood, LocationType& location,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride
);
// no weights, no mask
virtual void _unweightedStats(
StatsData<AccumType>& stats, uInt64& ngood, LocationType& location,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const DataRanges& ranges, Bool isInclude
);
virtual void _unweightedStats(
StatsData<AccumType>& stats, uInt64& ngood, LocationType& location,
const DataIterator& dataBegin, uInt64 nr, uInt dataStride,
const MaskIterator& maskBegin, uInt maskStride
);
virtual 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
);
// </group>
// <group>
// has weights, but no mask, no ranges
virtual void _weightedStats(
StatsData<AccumType>& stats, LocationType& location,
const DataIterator& dataBegin, const WeightsIterator& weightsBegin,
uInt64 nr, uInt dataStride
);
virtual void _weightedStats(
StatsData<AccumType>& stats, LocationType& location,
const DataIterator& dataBegin, const WeightsIterator& weightsBegin,
uInt64 nr, uInt dataStride, const DataRanges& ranges, Bool isInclude
);
virtual void _weightedStats(
StatsData<AccumType>& stats, LocationType& location,
const DataIterator& dataBegin, const WeightsIterator& weightBegin,
uInt64 nr, uInt dataStride, const MaskIterator& maskBegin,
uInt maskStride
);
virtual 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
);
// </group>
private:
std::shared_ptr<std::pair<AccumType, AccumType>> _range{};
};
}
#ifndef CASACORE_NO_AUTO_TEMPLATES
#include <casacore/scimath/StatsFramework/ConstrainedRangeStatistics.tcc>
#endif
#endif
DataRanges
#define DataRanges
Definition StatisticsTypes.h:49
casacore::ClassicalStatistics< CASA_STATP >::ClassicalStatistics
ClassicalStatistics()
casacore::ConstrainedRangeQuantileComputer
Basic concrete QuantileComputer class for data constrained to be in a specified range.
Definition ConstrainedRangeQuantileComputer.h:46
casacore::ConstrainedRangeStatistics::~ConstrainedRangeStatistics
virtual ~ConstrainedRangeStatistics()
casacore::ConstrainedRangeStatistics::_weightedStats
virtual void _weightedStats(StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride)
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::getStatisticIndex
virtual LocationType getStatisticIndex(StatisticsData::STATS stat)
see base class description
casacore::ConstrainedRangeStatistics::_unweightedStats
virtual void _unweightedStats(StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride)
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride) const
casacore::ConstrainedRangeStatistics::reset
virtual void reset()
reset object to initial state.
casacore::ConstrainedRangeStatistics::ConstrainedRangeStatistics
ConstrainedRangeStatistics()=delete
casacore::ConstrainedRangeStatistics::_getStatistics
virtual StatsData< AccumType > _getStatistics()
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataStart, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride) const
Sometimes we want the min, max, and npts all in one scan.
casacore::ConstrainedRangeStatistics::_range
std::shared_ptr< std::pair< AccumType, AccumType > > _range
Definition ConstrainedRangeStatistics.h:410
casacore::ConstrainedRangeStatistics::ConstrainedRangeStatistics
ConstrainedRangeStatistics(const ConstrainedRangeStatistics< CASA_STATP > &other)
copy semantics
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const
casacore::ConstrainedRangeStatistics::ConstrainedRangeStatistics
ConstrainedRangeStatistics(std::shared_ptr< ConstrainedRangeQuantileComputer< CASA_STATP > > qc)
Concrete derived classes are responsible for providing an appropriate QuantileComputer object to the ...
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const
casacore::ConstrainedRangeStatistics::_weightedStats
virtual void _weightedStats(StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude)
casacore::ConstrainedRangeStatistics::getQuantiles
virtual std::map< Double, AccumType > getQuantiles(const std::set< Double > &quantiles, std::shared_ptr< uInt64 > knownNpts=nullptr, std::shared_ptr< AccumType > knownMin=nullptr, std::shared_ptr< AccumType > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt nBins=10000)
Get the specified quantiles.
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::getMedianAbsDevMed
virtual 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.
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::getMinMax
virtual void getMinMax(AccumType &mymin, AccumType &mymax)
get the min and max of the data set
casacore::ConstrainedRangeStatistics::_unweightedStats
virtual void _unweightedStats(StatsData< AccumType > &stats, uInt64 &ngood, LocationType &location, const DataIterator &dataBegin, uInt64 nr, uInt dataStride)
no weights, no mask, no ranges
casacore::ConstrainedRangeStatistics::_accumNpts
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...
casacore::ConstrainedRangeStatistics::operator=
ConstrainedRangeStatistics< CASA_STATP > & operator=(const ConstrainedRangeStatistics< CASA_STATP > &other)
copy semantics
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::_getStatistic
virtual AccumType _getStatistic(StatisticsData::STATS stat)
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataBegin, const WeightsIterator &weightBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const
casacore::ConstrainedRangeStatistics::_weightedStats
virtual void _weightedStats(StatsData< AccumType > &stats, LocationType &location, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride)
has weights, but no mask, no ranges
casacore::ConstrainedRangeStatistics::_unweightedStats
virtual 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
casacore::ConstrainedRangeStatistics::_weightedStats
virtual 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)
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const
casacore::ConstrainedRangeStatistics::getMedian
virtual 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)
In the following group of methods, if the size of the composite dataset is smaller than binningThresh...
casacore::ConstrainedRangeStatistics::_setRange
virtual void _setRange()=0
derived classes need to implement how to set their respective range
casacore::ConstrainedRangeStatistics::_accumNpts
virtual void _accumNpts(uInt64 &npts, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride) const
casacore::ConstrainedRangeStatistics::getNPts
virtual uInt64 getNPts()
scan the dataset(s) that have been added, and find the number of good points.
casacore::ConstrainedRangeStatistics::_minMaxNpts
virtual void _minMaxNpts(uInt64 &npts, std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const
casacore::ConstrainedRangeStatistics::_setRange
void _setRange(std::shared_ptr< std::pair< AccumType, AccumType > > r)
This method is purposefully non-virtual.
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, uInt64 nr, uInt dataStride) const
casacore::ConstrainedRangeStatistics::getMedianAndQuantiles
virtual AccumType getMedianAndQuantiles(std::map< Double, AccumType > &quantileToValue, const std::set< Double > &quantiles, 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)
If one needs to compute both the median and quantile values, it is better to call getMedianAndQuantil...
casacore::ConstrainedRangeStatistics::_unweightedStats
virtual 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)
casacore::ConstrainedRangeStatistics::_minMax
virtual void _minMax(std::shared_ptr< AccumType > &mymin, std::shared_ptr< AccumType > &mymax, const DataIterator &dataBegin, uInt64 nr, uInt dataStride) const
casacore::StatisticsData::STATS
STATS
Definition StatisticsData.h:53
casacore
this file contains all the compiler specific defines
Definition mainpage.dox:28
casacore::False
const Bool False
Definition aipstype.h:42
casacore::uInt
unsigned int uInt
Definition aipstype.h:49
casacore::LocationType
std::pair< Int64, Int64 > LocationType
Definition StatisticsTypes.h:53
casacore::Bool
bool Bool
Define the standard types used by Casacore.
Definition aipstype.h:40
casacore::uInt64
unsigned long long uInt64
Definition aipsxtype.h:37
casacore::StatsData
Definition StatisticsTypes.h:55