Generate statistics, tile by tile, from a masked lattice. More...

#include <LatticeStatistics.h>

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

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 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_p
Bool	noInclude_p
Bool	noExclude_p
Bool	fixedMinMax_p
IPosition	minPos_p
IPosition	maxPos_p
Block< U > *	pSum_p
	Accumulators for sum, sum squared, number of points minimum, and maximum.
Block< U > *	pSumSq_p
Block< U > *	pNPts_p
Block< U > *	pMean_p
Block< U > *	pVariance_p
Block< U > *	pNVariance_p
Block< T > *	pMin_p
Block< T > *	pMax_p
Block< Bool > *	pInitMinMax_p
uInt	n1_p
uInt	n3_p

Detailed Description

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

Generate statistics, tile by tile, from a masked lattice.

Intended use:

Public interface

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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.