ClarkCleanLatModel.h

Classes

ClarkCleanLatModel -- A Class for performing the Clark Clean Algorithm on Arrays (full description)

class ClarkCleanLatModel: public LinearModel< Lattice<Float> >, public Iterate

Interface

Public Members
ClarkCleanLatModel()
ClarkCleanLatModel(Lattice<Float> & model)
ClarkCleanLatModel(Lattice<Float> & model, Lattice<Float> & mask)
ClarkCleanLatModel(Lattice<Float> & model, Lattice<Float> & residual, Lattice<Float> & mask)
virtual ~ClarkCleanLatModel()
virtual const Lattice<Float> & getModel() const
virtual void setModel(const Lattice<Float> & model)
virtual void setModel(Lattice<Float> & model)
const Lattice<Float> & getMask() const
void setMask(const Lattice<Float> & mask)
void setResidual( Lattice<Float> & residual)
Float getMaxResidual()
Bool solve(LatConvEquation & eqn)
Bool singleSolve(LatConvEquation & eqn, Lattice<Float> & residual)
virtual void setChoose(const Bool askForChoice)
virtual Bool getChoose()
virtual void setPsfPatchSize(const IPosition & psfPatchSize)
virtual IPosition getPsfPatchSize()
virtual void setHistLength(const uInt histBins)
virtual uInt getHistLength()
virtual void setMaxNumberMinorIterations(const uInt maxNumMinorIterations)
virtual uInt getMaxNumberMinorIterations()
virtual void setInitialNumberIterations(const uInt initialNumberIterations)
virtual uInt getInitialNumberIterations()
virtual void setMaxNumberMajorCycles(const uInt maxNumMajorCycles)
virtual uInt getMaxNumberMajorCycles()
virtual void setMaxNumPix(const uInt maxNumPix )
virtual uInt getMaxNumPix()
virtual void setMaxExtPsf(const Float maxExtPsf )
virtual Float getMaxExtPsf()
virtual void setSpeedup(const Float speedup)
virtual Float getSpeedup()
virtual void setCycleFactor(const Float factor)
virtual void setProgress(ClarkCleanProgress& ccp)
virtual ClarkCleanProgress& getProgress()
Private Members
void doMinorIterations(CCList & activePixels, Matrix<Float> & psfPatch, Float fluxLimit, uInt & numberIterations, Float Fmn, const uInt totalIterations, Float& totalFlux)
void cacheActivePixels(CCList & activePixels, const Lattice<Float> & residual, Float fluxLimit)
void absHistogram(Vector<Int> & hist, Float & minVal, Float & maxVal, const Lattice<Float> & data)
Float biggestResiduals(Float & maxRes, const uInt maxNumPix, const Float fluxLimit, const Lattice<Float> & residual)
Float getPsfPatch(Matrix<Float> & psfPatch, LatConvEquation & eqn)
Float maxResidual(const Lattice<Float> & residual)
void maxVect(Block<Float> & maxVal, Float & absVal, Int & offset, const CCList & activePixels)
void subtractComponent(CCList & activePixels, const Block<Float> & maxVal, const Block<Int> & maxPos, const Matrix<Float> & psf)
Float absMaxBeyondDist(const IPosition & maxDist, const IPosition & centre, const Lattice<Float> & psf)
Bool stopnow()
Int getbig(Float const * pixValPtr, Int const * pixPosPtr, const Int nPix, const Float fluxLimit, const Float * const residualPtr, const Float * const maskPtr, const uInt npol, const Int nx, const Int ny)
void updateModel(CCList & cleanComponents)

Description

Review Status

Date Reviewed:
yyyy/mm/dd

Prerequisite

Etymology

This class is called ClarkCleanLatModel because thats the algorithm it uses deconvolve the lattice-based model.

Synopsis

This class is used to perform the Clark Clean Algorithm on an Array. Only the deconvolved model of the sky are directly stored by this class. The point spread function (psf) and convolved (dirty) image are stored in a companion class which is must be derived from ResidualEquation.

The cleaning works like this. The user constructs a ClarkCleanLatModel by specifying an initial model of the sky. This can by be one,two,three... dimensional depending on the dimension of the psf (see below). The user then constructs a class which implements the forward equation between the model and the dirty image. Typically this will be the ConvolutionEquation class, although any class which has a ResidualEquation interface will be work (but perhaps very slowly, as the ConvolutionEquation class has member functions optimised for cleaning)

The user then calls the solve() function (with the appropriate equation class as an arguement), and this class will perform the Clark clean. The various clean parameters are set (prior to calling solve) using the functions derived from the Iterate class, in particular setGain(), setNumberIterations() & setThreshold() (to set a flux limit).

The solve() function does not return either the deconvolved model or the residuals. The solved model can be obtained using the getModel() function (derived from ArrayModel()) and the residual can be obtained using the residual() member function of the Convolution/Residual Equation Class.

The size and shape of the model used in this class MUST be the same as the convolved data (Dirty Image), stored in the companion ResidualEquation Class. However the model (and convolved data) can have more dimensions than the psf, as well as a different size (either larger or smaller). When the dimensionality is different the cleaning is done independendtly in each "plane" of the model. (Note this has not been implemented yet but is relatively simple to do if necessary).

This multi-dimensionalty is exploited when cleaning arrays of StokesVectors. Here the Array of StokesVectors is decomposed into a stack of 4 Floating point arrays and the cleaning is done on all the the arrays simultaneosly. The criterion for choosing the brightest pixel has been generalised by using the "length" of the Stokesvector in 4 dimensional space.

A companion class to this one is MaskedClarkCleanLatModel. This provides the same functionality but is used with MaskedArrays which indicate which regions of the model to search for clean components.

Example

    Matrix<Float> psf(12,12), dirty(10,10), initialModel(10,10);
    ...put appropriate values into psf, dirty, & initialModel....
    ClarkCleanLatModel<Float> deconvolvedModel(initialModel); 
    ConvolutionEquation convEqn(psf, dirty);
    deconvolvedModel.setGain(0.2); 
    deconvolvedModel.setNumberIterations(1000);
    Bool convWorked = deconvolvedModel.solve(convEqn);
    Array<Float> finalModel, residuals;
    if (convWorked){
      finalModel = deconvolvedModel.getModel();
      ConvEqn.residual(deconvolvedModel, finalResidual);
    }
    

Motivation

This class is needed to deconvolve images.

Template Type Argument Requirements (T)

To Do

Member Description

ClarkCleanLatModel()

The default constructor does nothing more than initialise a zero length array to hold the deconvolved model. If this constructor is used then the actual model must be set using the setModel() function of the LatticeModel class.

ClarkCleanLatModel(Lattice<Float> & model)

Construct the ClarkCleanLatModel object and initialise the model.

ClarkCleanLatModel(Lattice<Float> & model, Lattice<Float> & mask)

Construct the ClarkCleanLatModel object and initialise the model ans mask

ClarkCleanLatModel(Lattice<Float> & model, Lattice<Float> & residual, Lattice<Float> & mask)

Construct the ClarkCleanLatModel object and initialise the model ans mask

virtual ~ClarkCleanLatModel()

Destroy!

virtual const Lattice<Float> & getModel() const

virtual void setModel(const Lattice<Float> & model)

virtual void setModel(Lattice<Float> & model)

const Lattice<Float> & getMask() const

void setMask(const Lattice<Float> & mask)

void setResidual( Lattice<Float> & residual)

Float getMaxResidual()

Bool solve(LatConvEquation & eqn)
Bool singleSolve(LatConvEquation & eqn, Lattice<Float> & residual)

Using a Clark clean deconvolution proceedure solve for an improved estimate of the deconvolved object. The convolution/residual equation contains the psf and dirty image. When called with a ResidualEquation arguement a quite general interface is used that is slow. The convolution equation contains functions that speed things up. The functions return False if the deconvolution could not be done.

virtual void setChoose(const Bool askForChoice)
virtual Bool getChoose()

The user can be asked whether to stop after every minor cycle

virtual void setPsfPatchSize(const IPosition & psfPatchSize)
virtual IPosition getPsfPatchSize()

These remaining functions set various "knobs" that the user can tweak and are specific to the Clark clean algorithm. The more generic parameters ie. clean gain, and maximum residual fluxlimit, are set using functions in the Iterate base class. The get functions return the value that was actually used after the cleaning was done.

set the size of the PSF used in the minor iterations. If not set it defaults to the largest useful Psf (ie. min(modelSize*2, psfSize))

virtual void setHistLength(const uInt histBins)
virtual uInt getHistLength()

Set the size of the histogram used to determine how many pixels are "active" in a minor iteration. Default value of 1000 is OK for everything except very small cleans.

virtual void setMaxNumberMinorIterations(const uInt maxNumMinorIterations)
virtual uInt getMaxNumberMinorIterations()

Set the maximum number of minor iterations to perform for each major cycle.

virtual void setInitialNumberIterations(const uInt initialNumberIterations)
virtual uInt getInitialNumberIterations()

Set and get the initial number of iterations

virtual void setMaxNumberMajorCycles(const uInt maxNumMajorCycles)
virtual uInt getMaxNumberMajorCycles()

Set the maximum number of major cycles to perform

virtual void setMaxNumPix(const uInt maxNumPix )
virtual uInt getMaxNumPix()

Set the maximum number of active pixels to use in the minor iterations. The specified number can be exceeded if the topmost bin of the histogram contains more pixels than specified here. The default is 10,000 which is suitable for images of 512by512 pixels. Reduce this for smaller images and increase it for larger ones.

virtual void setMaxExtPsf(const Float maxExtPsf )
virtual Float getMaxExtPsf()

Set the maximum exterior psf value. This is used to determine when to stop the minor itartions. This is normally determined from the psf and the number set here is only used if this cannot be determined. The default is zero.

virtual void setSpeedup(const Float speedup)
virtual Float getSpeedup()

An exponent on the F(m,n) factor (see Clark[1980]) which influences how quickly active pixels are treated as unreliable. Larger values mean more major iterations. The default is zero. I have no experience on when to use this factor.

virtual void setCycleFactor(const Float factor)

Set the cycle factor....the larger this is the shallower is the minor cycle

virtual void setProgress(ClarkCleanProgress& ccp)
virtual ClarkCleanProgress& getProgress()

Set/get the progress display

void doMinorIterations(CCList & activePixels, Matrix<Float> & psfPatch, Float fluxLimit, uInt & numberIterations, Float Fmn, const uInt totalIterations, Float& totalFlux)

Do all the minor iterations for one major cycle. Cleaning stops when the flux or iteration limit is reached.

void cacheActivePixels(CCList & activePixels, const Lattice<Float> & residual, Float fluxLimit)

void absHistogram(Vector<Int> & hist, Float & minVal, Float & maxVal, const Lattice<Float> & data)

make histogram of absolute values in array

Float biggestResiduals(Float & maxRes, const uInt maxNumPix, const Float fluxLimit, const Lattice<Float> & residual)

Determine the flux limit if we only select the maxNumPix biggest residuals. Flux limit is not exact due to quantising by the histogram

Float getPsfPatch(Matrix<Float> & psfPatch, LatConvEquation & eqn)

Work out the size of the Psf patch to use.

Float maxResidual(const Lattice<Float> & residual)

The maximum residual is the absolute maximum.

void maxVect(Block<Float> & maxVal, Float & absVal, Int & offset, const CCList & activePixels)

void subtractComponent(CCList & activePixels, const Block<Float> & maxVal, const Block<Int> & maxPos, const Matrix<Float> & psf)

Float absMaxBeyondDist(const IPosition & maxDist, const IPosition & centre, const Lattice<Float> & psf)

Bool stopnow()

Int getbig(Float const * pixValPtr, Int const * pixPosPtr, const Int nPix, const Float fluxLimit, const Float * const residualPtr, const Float * const maskPtr, const uInt npol, const Int nx, const Int ny)

void updateModel(CCList & cleanComponents)