casacore::StatsTiledCollapser< T, U > Class Template Reference

Generate statistics, tile by tile, from a masked lattice NOTE this version was moved from LatticeStatistics (early Dec 2014 version) and slightly modified mostly for style issues (no significant semantic differences from that version). For a large number of statistics sets that need to be computed simultaneously, this version is more efficient than using the new stats framework, because creating large numbers of eg ClassicalStatistics objects is much less efficient than the direct manipulation of pointers to primitive types that this class does. More...

#include <StatsTiledCollapser.h>

Inheritance diagram for casacore::StatsTiledCollapser< T, U >:

List of all members.

Public Member Functions
	StatsTiledCollapser (const Vector< T > &pixelRange, Bool noInclude, Bool noExclude, Bool fixedMinMax)
	Constructor provides pixel selection range and whether that range is an inclusion or exclusion range.
virtual	~StatsTiledCollapser ()
virtual void	init (uInt nOutPixelsPerCollapse)
	Initialize process, making some checks.
virtual void	initAccumulator (uInt n1, uInt n3)
	Initialiaze the accumulator.
virtual void	process (uInt accumIndex1, uInt accumIndex3, const T inData, const Bool inMask, uInt dataIncr, uInt maskIncr, uInt nrval, const IPosition &startPos, const IPosition &shape)
	Process the data in the current chunk.
virtual void	endAccumulator (Array< U > &result, Array< Bool > &resultMask, const IPosition &shape)
	End the accumulation process and return the result arrays.
virtual Bool	canHandleNullMask () const
	Can handle null mask.
void	minMaxPos (IPosition &minPos, IPosition &maxPos)
	Find the location of the minimum and maximum data values in the input lattice.
Private Attributes
Vector< T >	_range
Bool	_include
Bool	_exclude
Bool	_fixedMinMax
Bool	_isReal
IPosition	_minpos
IPosition	_maxpos
CountedPtr< Block< U > >	_sum
	Accumulators for sum, sum squared, number of points minimum, and maximum.
CountedPtr< Block< U > >	_sumSq
CountedPtr< Block< U > >	_npts
CountedPtr< Block< U > >	_mean
CountedPtr< Block< U > >	_variance
CountedPtr< Block< U > >	_nvariance
CountedPtr< Block< T > >	_min
CountedPtr< Block< T > >	_max
CountedPtr< Block< Bool > >	_initMinMax
uInt	_n1
uInt	_n3

Detailed Description

template<class T, class U = T>
class casacore::StatsTiledCollapser< T, U >

Generate statistics, tile by tile, from a masked lattice NOTE this version was moved from LatticeStatistics (early Dec 2014 version) and slightly modified mostly for style issues (no significant semantic differences from that version). For a large number of statistics sets that need to be computed simultaneously, this version is more efficient than using the new stats framework, because creating large numbers of eg ClassicalStatistics objects is much less efficient than the direct manipulation of pointers to primitive types that this class does.

Intended use:

Public interface

Review Status

Date Reviewed:: yyyy/mm/dd

Prerequisite

Etymology

This class is used by LatticeStatistics to generate statistical sum from an input MaskedLattice. The input lattice is iterated through in tile-sized chunks and fed to an object of this class.

Synopsis

StatsTiledCollapser is derived from TiledCollapser which is a base class used to define methods. Objects of this base class are used by LatticeApply functions. In this particular case, we are interested in LatticeApply::tiledApply. This function iterates through a MaskedLattice and allows you to collapse one or more axes, computing some values from it, and placing those values into an output MaskedLattice. It iterates through the input lattice in optimal tile-sized chunks. LatticeStatistics uses a StatsTiledCollapser object which it gives to LatticeApply::tiledApply for digestion. After it has done its work, LatticeStatistics then accesses the output Lattice that it made.

Example

// Create collapser. Control information is passed in via the constructor
 
 StatsTiledCollapser<T> collapser(range_p, noInclude_p, noExclude_p,   
 fixedMinMax_p, blcParent_p);
 
// This is the first output axis getting  collapsed values. In LatticeStatistics
// this is the last axis of the output lattice
 
 Int newOutAxis = outLattice.ndim()-1;
 
// tiledApply does the work by passing the collapser data in chunks
// and by writing the results into the output lattice 
 
 LatticeApply<T>::tiledApply(outLattice, inLattice,
 collapser, collapseAxes,
 newOutAxis);

In this example, a collapser is made and passed to LatticeApply. Afterwards, the output Lattice is available for use. The Lattices must all be the correct shapes on input to tiledApply

Motivation

The LatticeApply classes enable the ugly details of optimal Lattice iteration to be hidden from the user.