ChauvenetCriterionStatistics.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
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//# License for more details.
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#ifndef SCIMATH_CHAUVENETCRITERIONSTATISTICS_H
#define SCIMATH_CHAUVENETCRITERIONSTATISTICS_H
 
#include <casacore/casa/aips.h>
 
#include <casacore/scimath/StatsFramework/ConstrainedRangeStatistics.h>
 
#include <set>
#include <utility>
 
namespace casacore {
 
// 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.
 
template <
    class AccumType, class DataIterator, class MaskIterator=const Bool*,
    class WeightsIterator=DataIterator
>
class ChauvenetCriterionStatistics
    : public ConstrainedRangeStatistics<CASA_STATP> {
public:
 
    ChauvenetCriterionStatistics() = delete;
 
    // If <src>zscore</src> 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 <src>zscore</src> is negative, use
    // Chauvenet's Criterion to determine which outliers to discard.
    // <src>maxIterations</src> 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(Double zscore=-1, Int maxIterations=0);
 
    ChauvenetCriterionStatistics(
        const ChauvenetCriterionStatistics<CASA_STATP>& other
    );
 
    virtual ~ChauvenetCriterionStatistics();
 
    // copy semantics
    ChauvenetCriterionStatistics<CASA_STATP>& operator=(
        const ChauvenetCriterionStatistics<CASA_STATP>& other
    );
 
    // Clone this instance
    virtual StatisticsAlgorithm<CASA_STATP>* clone() const;
 
    // get the algorithm that this object uses for computing stats
    virtual StatisticsData::ALGORITHM algorithm() const {
        return StatisticsData::CHAUVENETCRITERION;
    };
 
    // 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.
    virtual void reset();
 
    // This class does not allow statistics to be calculated as datasets are
    // added, so an exception will be thrown if <src>c</src> is True.
    void setCalculateAsAdded(Bool c);
 
    // get the number of iterations
    uInt getNiter() const { return _niter; }
 
private:
 
    Double _zscore{-1};
    Int _maxIterations{0};
    Bool _rangeIsSet{False};
    uInt _niter{0};
 
    void _setRange();
};
 
}
 
#ifndef CASACORE_NO_AUTO_TEMPLATES
#include <casacore/scimath/StatsFramework/ChauvenetCriterionStatistics.tcc>
#endif
 
#endif