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//# 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,
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//#
//# Correspondence concerning AIPS++ should be addressed as follows:
//# Internet email: aips2-request@nrao.edu.
//# Postal address: AIPS++ Project Office
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//# $Id: Array.h 21545 2015-01-22 19:36:35Z gervandiepen $
#ifndef SCIMATH_CHAUVENETCRITERIONSTATISTICS_H
#define SCIMATH_CHAUVENETCRITERIONSTATISTICS_H
#include <casacore/casa/aips.h>
#include <casacore/scimath/Mathematics/ConstrainedRangeStatistics.h>
#include <set>
#include <vector>
#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. In this case, no iterating is done.
template <class AccumType, class DataIterator, class MaskIterator=const Bool*, class WeightsIterator=DataIterator>
class ChauvenetCriterionStatistics
: public ConstrainedRangeStatistics<CASA_STATP> {
public:
// 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);
virtual ~ChauvenetCriterionStatistics();
// copy semantics
ChauvenetCriterionStatistics<CASA_STATP>& operator=(
const ChauvenetCriterionStatistics<CASA_STATP>& other
);
// 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;
Int _maxIterations;
Bool _rangeIsSet;
uInt _niter;
void _setRange();
};
}
#ifndef CASACORE_NO_AUTO_TEMPLATES
#include <casacore/scimath/Mathematics/ChauvenetCriterionStatistics.tcc>
#endif //# CASACORE_NO_AUTO_TEMPLATES
#endif
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