casacore
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Class to calculate statistics in a "classical" sense, ie using accumulators with no special filtering beyond optional range filtering etc. More...
#include <ClassicalStatistics.h>
Public Member Functions | |
ClassicalStatistics () | |
ClassicalStatistics (const ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > &cs) | |
copy semantics More... | |
virtual | ~ClassicalStatistics () |
ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > & | operator= (const ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > &other) |
copy semantics More... | |
virtual StatisticsData::ALGORITHM | algorithm () const |
get the algorithm that this object uses for computing stats More... | |
virtual AccumType | getMedian (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. More... | |
virtual 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) |
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. More... | |
virtual 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. More... | |
virtual 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. More... | |
virtual void | getMinMax (AccumType &mymin, AccumType &mymax) |
scan the dataset(s) that have been added, and find the min and max. More... | |
virtual uInt64 | getNPts () |
scan the dataset(s) that have been added, and find the number of good points. More... | |
virtual std::pair< Int64, Int64 > | getStatisticIndex (StatisticsData::STATS stat) |
see base class description More... | |
virtual void | reset () |
reset object to initial state. More... | |
virtual void | setCalculateAsAdded (Bool c) |
Should statistics be updated with calls to addData or should they only be calculated upon calls to getStatistics etc? Beware that calling this will automatically reinitialize the object, so that it will contain no references to data et al. More... | |
void | setDataProvider (StatsDataProvider< AccumType, DataIterator, MaskIterator, WeightsIterator > *dataProvider) |
An exception will be thrown if setCalculateAsAdded(True) has been called. More... | |
void | setStatsToCalculate (std::set< StatisticsData::STATS > &stats) |
Provide guidance to algorithms by specifying a priori which statistics the caller would like calculated. More... | |
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virtual | ~StatisticsAlgorithm () |
virtual 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. More... | |
virtual void | addData (const DataIterator &first, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False) |
virtual void | addData (const DataIterator &first, const MaskIterator &maskFirst, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | addData (const DataIterator &first, const MaskIterator &maskFirst, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | addData (const DataIterator &first, const WeightsIterator &weightFirst, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False) |
virtual void | addData (const DataIterator &first, const WeightsIterator &weightFirst, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False) |
virtual void | addData (const DataIterator &first, const WeightsIterator &weightFirst, const MaskIterator &maskFirst, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | addData (const DataIterator &first, const WeightsIterator &weightFirst, const MaskIterator &maskFirst, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
void | deleteSortedArray () |
delete any (partially) sorted array More... | |
AccumType | getQuantile (Double quantile, CountedPtr< uInt64 > knownNpts=NULL, CountedPtr< AccumType > knownMin=NULL, CountedPtr< AccumType > knownMax=NULL, uInt binningThreshholdSizeBytes=4096 *4096, Bool persistSortedArray=False, uInt64 nBins=10000) |
virtual AccumType | getStatistic (StatisticsData::STATS stat) |
get the value of the specified statistic More... | |
virtual StatsData< AccumType > | getStatistics () |
virtual 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. More... | |
virtual void | setData (const DataIterator &first, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False) |
virtual void | setData (const DataIterator &first, const MaskIterator &maskFirst, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | setData (const DataIterator &first, const MaskIterator &maskFirst, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | setData (const DataIterator &first, const WeightsIterator &weightFirst, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False) |
virtual void | setData (const DataIterator &first, const WeightsIterator &weightFirst, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False) |
virtual void | setData (const DataIterator &first, const WeightsIterator &weightFirst, const MaskIterator &maskFirst, uInt nr, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | setData (const DataIterator &first, const WeightsIterator &weightFirst, const MaskIterator &maskFirst, uInt nr, const DataRanges &dataRanges, Bool isInclude=True, uInt dataStride=1, Bool nrAccountsForStride=False, uInt maskStride=1) |
virtual void | setDataProvider (StatsDataProvider< CASA_STATP > *dataProvider) |
instead of settng and adding data "by hand", set the data provider that will provide all the data sets. More... | |
Protected Member Functions | |
virtual void | _accumNpts (uInt64 &npts, const DataIterator &dataBegin, Int64 nr, uInt dataStride) const |
scan through the data set to determine the number of good (unmasked, weight > 0, within range) points. More... | |
virtual void | _accumNpts (uInt64 &npts, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const |
virtual void | _accumNpts (uInt64 &npts, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const |
virtual void | _accumNpts (uInt64 &npts, const DataIterator &dataBegin, Int64 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, Int64 nr, uInt dataStride) const |
virtual void | _accumNpts (uInt64 &npts, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const |
virtual void | _accumNpts (uInt64 &npts, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 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, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const |
void | _accumulate (AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const AccumType &datum, Int64 count) |
void | _accumulate (AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const AccumType &datum, const AccumType &weight, Int64 count) |
void | _addData () |
Allows derived classes to do things after data is set or added. More... | |
void | _clearData () |
void | _clearStats () |
void | _doMinMax (AccumType &vmin, AccumType &vmax) |
scan dataset(s) to find min and max More... | |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
Get the counts of data within the specified histogram bins. More... | |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
virtual void | _findBins (vector< vector< uInt64 > > &binCounts, vector< CountedPtr< AccumType > > &sameVal, vector< Bool > &allSame, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, const vector< AccumType > &maxLimit) const |
AccumType | _getStatistic (StatisticsData::STATS stat) |
StatsData< AccumType > | _getStatistics () |
virtual StatsData< AccumType > & | _getStatsData () |
retreive stats structure. More... | |
virtual const StatsData< AccumType > & | _getStatsData () const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, Int64 nr, uInt dataStride) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const |
virtual void | _minMax (CountedPtr< AccumType > &mymin, CountedPtr< AccumType > &mymax, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride) const |
populate an unsorted array with valid data. More... | |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const |
ranges More... | |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const |
mask and ranges More... | |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride) const |
weights More... | |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) const |
weights and ranges More... | |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) const |
weights and mask More... | |
virtual void | _populateArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) const |
weights, mask, ranges More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
Create a vector of unsorted arrays, one array for each bin defined by includeLimits . More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
ranges More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
mask and ranges More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
weights More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
weights and ranges More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
weights and mask More... | |
virtual void | _populateArrays (vector< vector< AccumType > > &arys, uInt ¤tCount, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) const |
weights, mask, ranges More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, uInt maxElements) const |
no weights, no mask, no ranges More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude, uInt maxElements) const |
ranges More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, uInt maxElements) const |
mask More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude, uInt maxElements) const |
mask and ranges More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, uInt maxElements) const |
weights More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude, uInt maxElements) const |
weights and ranges More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, uInt maxElements) const |
weights and mask More... | |
virtual Bool | _populateTestArray (vector< AccumType > &ary, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude, uInt maxElements) const |
weights, mask, ranges More... | |
virtual void | _unweightedStats (uInt64 &ngood, AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, Int64 nr, uInt dataStride) |
no weights, no mask, no ranges More... | |
virtual void | _unweightedStats (uInt64 &ngood, AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) |
no weights, no mask More... | |
virtual void | _unweightedStats (uInt64 &ngood, AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) |
virtual void | _unweightedStats (uInt64 &ngood, AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) |
virtual void | _weightedStats (AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride) |
has weights, but no mask, no ranges More... | |
virtual void | _weightedStats (AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, const WeightsIterator &weightsBegin, Int64 nr, uInt dataStride, const DataRanges &ranges, Bool isInclude) |
virtual void | _weightedStats (AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride) |
virtual void | _weightedStats (AccumType &mymin, AccumType &mymax, Int64 &minpos, Int64 &maxpos, const DataIterator &dataBegin, const WeightsIterator &weightBegin, Int64 nr, uInt dataStride, const MaskIterator &maskBegin, uInt maskStride, const DataRanges &ranges, Bool isInclude) |
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StatisticsAlgorithm () | |
StatisticsAlgorithm< CASA_STATP > & | operator= (const StatisticsAlgorithm< CASA_STATP > &other) |
use copy semantics More... | |
const vector< Int64 > & | _getCounts () const |
const vector< DataIterator > & | _getData () const |
StatsDataProvider< CASA_STATP > * | _getDataProvider () |
const vector< uInt > & | _getDataStrides () const |
const std::map< uInt, Bool > & | _getIsIncludeRanges () const |
const std::map< uInt, MaskIterator > | _getMasks () const |
const std::map< uInt, uInt > & | _getMaskStrides () const |
const std::map< uInt, DataRanges > & | _getRanges () const |
const std::set< StatisticsData::STATS > | _getStatsToCalculate () const |
std::vector< AccumType > & | _getSortedArray () |
virtual const std::set< StatisticsData::STATS > & | _getUnsupportedStatistics () const |
const std::map< uInt, WeightsIterator > & | _getWeights () const |
void | _setSortedArray (const vector< AccumType > &v) |
Private Member Functions | |
vector< vector< uInt64 > > | _binCounts (vector< CountedPtr< AccumType > > &sameVal, const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc) |
tally the number of data points that fall into each bin provided by binDesc Any points that are less than binDesc.minLimit or greater than binDesc.minLimit + binDesc.nBins*binDesc.binWidth are not included in the counts. More... | |
void | _createDataArray (vector< AccumType > &array) |
Create an unsorted array of the complete data set. More... | |
void | _createDataArrays (vector< vector< AccumType > > &arrays, const vector< std::pair< AccumType, AccumType > > &includeLimits, uInt maxCount) |
vector< std::map< uInt64, AccumType > > | _dataFromMultipleBins (const vector< typename StatisticsUtilities< AccumType >::BinDesc > &binDesc, uInt maxArraySize, const vector< std::set< uInt64 > > &dataIndices, uInt64 nBins) |
extract data from multiple histograms given by binDesc . More... | |
vector< std::map< uInt64, AccumType > > | _dataFromSingleBins (const vector< uInt64 > &binNpts, uInt maxArraySize, const vector< std::pair< AccumType, AccumType > > &binLimits, const vector< std::set< uInt64 > > &dataIndices, uInt64 nBins) |
Int64 | _doNpts () |
std::map< uInt64, AccumType > | _indicesToValues (CountedPtr< uInt64 > knownNpts, CountedPtr< AccumType > knownMin, CountedPtr< AccumType > knownMax, uInt maxArraySize, const std::set< uInt64 > &dataIndices, Bool persistSortedArray, uInt64 nBins) |
get the values for the specified indices in the sorted array of all good data More... | |
void | _initIterators () |
void | _initLoopVars () |
Bool | _isNptsSmallerThan (vector< AccumType > &arrayToSort, uInt maxArraySize) |
Determine by scanning the dataset if the number of good points is smaller than maxArraySize . More... | |
std::set< uInt64 > | _medianIndices (CountedPtr< uInt64 > knownNpts) |
If input set has one value, that is the median, if it has two, the median is the average of those. More... | |
virtual void | _updateMaxMin (AccumType mymin, AccumType mymax, Int64 minpos, Int64 maxpos, uInt dataStride, const Int64 ¤tDataset) |
update min and max if necessary More... | |
Bool | _valuesFromSortedArray (std::map< uInt64, AccumType > &values, CountedPtr< uInt64 > knownNpts, const std::set< uInt64 > &indices, uInt maxArraySize, Bool persistSortedArray) |
get values from sorted array if the array is small enough to be held in memory. More... | |
Static Private Member Functions | |
static void | _convertToAbsDevMedArray (vector< AccumType > &myArray, AccumType median) |
convert in place by taking the absolute value of the difference of the vector and the median More... | |
static void | _makeBins (typename StatisticsUtilities< AccumType >::BinDesc &bins, AccumType minData, AccumType maxData, uInt maxBins, Bool allowPad) |
If allowPad is True, then pad the lower side of the lowest bin and the higher side of the highest bin so that minData and maxData do not fall on the edge of their respective bins. More... | |
Private Attributes | |
StatsData< AccumType > | _statsData |
Int64 | _idataset |
Bool | _calculateAsAdded |
Bool | _doMaxMin |
Bool | _doMedAbsDevMed |
Bool | _mustAccumulate |
vector< DataIterator >::const_iterator | _dend |
mutables, used to mitigate repeated code More... | |
vector< DataIterator >::const_iterator | _diter |
vector< Int64 >::const_iterator | _citer |
vector< uInt >::const_iterator | _dsiter |
std::map< uInt, MaskIterator > | _masks |
uInt | _maskStride |
std::map< uInt, WeightsIterator > | _weights |
std::map< uInt, DataRanges > | _ranges |
std::map< uInt, Bool > | _isIncludeRanges |
Bool | _hasMask |
Bool | _hasRanges |
Bool | _hasWeights |
Bool | _myIsInclude |
DataRanges | _myRanges |
MaskIterator | _myMask |
DataIterator | _myData |
WeightsIterator | _myWeights |
uInt | _dataCount |
uInt | _myStride |
uInt64 | _myCount |
Additional Inherited Members | |
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static std::map< Double, uInt64 > | _indicesFromQuantiles (uInt64 npts, const std::set< Double > &quantiles) |
*static std::map< uInt64, AccumType > | _valuesFromArray (vector< AccumType > &myArray, const std::set< uInt64 > &indices) |
The array can be changed by paritally sorting it up to the largest index. More... | |
Class to calculate statistics in a "classical" sense, ie using accumulators with no special filtering beyond optional range filtering etc.
setCalculateAsAdded() allows one to specify if statistics should be calculated and updated on upon each call to set/addData(). If False, statistics will be calculated only when getStatistic(), getStatistics(), or similar methods are called. Setting this value to True allows the caller to not have to keep all the data accessible at once. Note however, that all data must be simultaneously accessible if quantile (eg median) calculations are desired.
I attempted to write this class using the Composite design pattern, with eg the _unweightedStats() and _weightedStats() methods in their own class, but for reasons I don't understand, that impacted performance significantly. So I'm using the current architecture, which I know is a bit a maintenance nightmare.
Definition at line 58 of file ClassicalStatistics.h.
casacore::ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::ClassicalStatistics | ( | ) |
casacore::ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::ClassicalStatistics | ( | const ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > & | cs | ) |
copy semantics
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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.
Reimplemented in casacore::ConstrainedRangeStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, casacore::ConstrainedRangeStatistics< CASA_STATP >, and casacore::HingesFencesStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Allows derived classes to do things after data is set or added.
Default implementation does nothing.
Reimplemented from casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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tally the number of data points that fall into each bin provided by binDesc
Any points that are less than binDesc.minLimit or greater than binDesc.minLimit + binDesc.nBins*binDesc.binWidth are not included in the counts.
A data point that falls exactly on a bin boundary is considered to be in the higher index bin. sameVal
will be non-null if all the good values in the histogram range are the same. In that case, the value held will be the value of each of those data points.
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Reimplemented from casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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convert in place by taking the absolute value of the difference of the vector and the median
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Create an unsorted array of the complete data set.
If includeLimits
is specified, only points within those limits (including min but excluding max, as per definition of bins), are included.
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extract data from multiple histograms given by binDesc
.
dataIndices
represent the indices of the sorted arrays of values to extract. There should be exactly one set of data indices to extract for each supplied histogram. The data indices are relative to the minimum value of the minimum bin in their repsective histograms. The ordering of the maps in the returned vector represent the ordering of histograms in binDesc
. binDesc
should contain non-overlapping histograms and the histograms should be specified in ascending order.
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scan dataset(s) to find min and max
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Get the counts of data within the specified histogram bins.
The number of arrays within binCounts will be equal to the number of histograms in binDesc
. Each array within binCounts
will have the same number of elements as the number of bins in its corresponding histogram in binDesc
.
Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
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retreive stats structure.
Allows derived classes to maintain their own StatsData structs.
Reimplemented in casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Definition at line 349 of file ClassicalStatistics.h.
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Reimplemented in casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Definition at line 351 of file ClassicalStatistics.h.
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get the values for the specified indices in the sorted array of all good data
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Determine by scanning the dataset if the number of good points is smaller than maxArraySize
.
If so, arrayToSort
will contain the unsorted data values. If not, this vector will be empty.
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If allowPad
is True, then pad the lower side of the lowest bin and the higher side of the highest bin so that minData and maxData do not fall on the edge of their respective bins.
If false, no padding so that minData and maxData are also exactly the histogram abscissa limits.
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If input set has one value, that is the median, if it has two, the median is the average of those.
static AccumType _medianFromSet(const std::map<uInt64, AccumType>& values);
get the index (for odd npts) or indices (for even npts) of the median of the sorted array. If knownNpts is not null, it will be used and must be correct. If it is null, the value of _npts will be used if it has been previously calculated. If not, the data sets will be scanned to determine npts.
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Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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populate an unsorted array with valid data.
no weights, no mask, no ranges
Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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ranges
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mask and ranges
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weights
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weights and ranges
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weights and mask
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weights, mask, ranges
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Create a vector of unsorted arrays, one array for each bin defined by includeLimits
.
includeLimits
should be non-overlapping and should be given in ascending order (the algorithm used assumes this). Once the sum of the lengths of all arrays equals maxCount
the method will return with no further processing. no weights, no mask, no ranges
Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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ranges
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mask and ranges
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weights
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weights and ranges
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weights and mask
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weights, mask, ranges
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no weights, no mask, no ranges
Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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ranges
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mask
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mask and ranges
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weights
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weights and ranges
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weights and mask
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weights, mask, ranges
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no weights, no mask, no ranges
Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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no weights, no mask
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update min and max if necessary
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get values from sorted array if the array is small enough to be held in memory.
Note that this is the array containing all good data, not data in just a single bin representing a subset of good data. Returns True if the data were successfully retrieved. If True is returned, the values map will contain a map of index to value.
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has weights, but no mask, no ranges
Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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get the algorithm that this object uses for computing stats
Implements casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Reimplemented in casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, and casacore::HingesFencesStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Definition at line 75 of file ClassicalStatistics.h.
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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. 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. nBins
is the number of bins, per histogram, to use to bin the data. More bins decrease the likelihood that multiple passes of the data set will be necessary, but also increase the amount of memory used. If nBins is set to less than 1,000, it is automatically increased to 1,000; there should be no reason to ever set nBins to be this small.
Implements casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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get the median of the absolute deviation about the median of the data.
Implements casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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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 quantiles
map. Values in the fractions
set represent the locations in the CDF and should be between 0 and 1, exclusive.
Implements casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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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. If setCalculateAsAdded(True) has previously been called after this object has been (re)initialized, an exception will be thrown.
Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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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 in casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, casacore::ConstrainedRangeStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, and casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Get the specified quantiles.
fractions
must be between 0 and 1, noninclusive.
Implements casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Reimplemented in casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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see base class description
Implements casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Reimplemented in casacore::ConstrainedRangeStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, and casacore::ConstrainedRangeStatistics< CASA_STATP >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
ClassicalStatistics<AccumType, DataIterator, MaskIterator, WeightsIterator>& casacore::ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::operator= | ( | const ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator > & | other | ) |
copy semantics
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reset object to initial state.
Clears all private fields including data, accumulators, etc.
Reimplemented in casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, casacore::ConstrainedRangeStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, casacore::ConstrainedRangeStatistics< CASA_STATP >, casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, and casacore::HingesFencesStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Should statistics be updated with calls to addData or should they only be calculated upon calls to getStatistics etc? Beware that calling this will automatically reinitialize the object, so that it will contain no references to data et al.
after this method has been called.
Reimplemented in casacore::FitToHalfStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, casacore::ChauvenetCriterionStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >, and casacore::HingesFencesStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
void casacore::ClassicalStatistics< AccumType, DataIterator, MaskIterator, WeightsIterator >::setDataProvider | ( | StatsDataProvider< AccumType, DataIterator, MaskIterator, WeightsIterator > * | dataProvider | ) |
An exception will be thrown if setCalculateAsAdded(True) has been called.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Provide guidance to algorithms by specifying a priori which statistics the caller would like calculated.
Reimplemented from casacore::StatisticsAlgorithm< AccumType, DataIterator, MaskIterator, WeightsIterator >.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::algorithm().
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Definition at line 652 of file ClassicalStatistics.h.
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Definition at line 656 of file ClassicalStatistics.h.
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Definition at line 668 of file ClassicalStatistics.h.
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mutables, used to mitigate repeated code
Definition at line 655 of file ClassicalStatistics.h.
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Definition at line 655 of file ClassicalStatistics.h.
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Definition at line 652 of file ClassicalStatistics.h.
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Definition at line 652 of file ClassicalStatistics.h.
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Definition at line 657 of file ClassicalStatistics.h.
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Definition at line 663 of file ClassicalStatistics.h.
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Definition at line 663 of file ClassicalStatistics.h.
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Definition at line 663 of file ClassicalStatistics.h.
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Definition at line 651 of file ClassicalStatistics.h.
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Definition at line 662 of file ClassicalStatistics.h.
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Definition at line 658 of file ClassicalStatistics.h.
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Definition at line 659 of file ClassicalStatistics.h.
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Definition at line 652 of file ClassicalStatistics.h.
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Definition at line 669 of file ClassicalStatistics.h.
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Definition at line 666 of file ClassicalStatistics.h.
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Definition at line 663 of file ClassicalStatistics.h.
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Definition at line 665 of file ClassicalStatistics.h.
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Definition at line 664 of file ClassicalStatistics.h.
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Definition at line 668 of file ClassicalStatistics.h.
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Definition at line 667 of file ClassicalStatistics.h.
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Definition at line 661 of file ClassicalStatistics.h.
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Definition at line 650 of file ClassicalStatistics.h.
Referenced by casacore::ClassicalStatistics< CASA_STATP >::_getStatsData().
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Definition at line 660 of file ClassicalStatistics.h.