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LatticeCleaner.tcc
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LatticeCleaner.tcc
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//# Copyright (C) 1997,1998,1999,2000,2001,2002,2003
//# 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,
//# Inc., 675 Massachusetts Ave, Cambridge, MA 02139, USA.
//#
//# Correspondence concerning AIPS++ should be addressed as follows:
//# Internet email: aips2-request@nrao.edu.
//# Postal address: AIPS++ Project Office
//# National Radio Astronomy Observatory
//# 520 Edgemont Road
//# Charlottesville, VA 22903-2475 USA
//#
//# $Id$
#ifndef LATTICES_LATTICECLEANER_TCC
#define LATTICES_LATTICECLEANER_TCC
#include <casacore/casa/Arrays/Matrix.h>
#include <casacore/casa/Arrays/ArrayMath.h>
#include <casacore/casa/Logging/LogIO.h>
#include <casacore/casa/OS/File.h>
#include <casacore/casa/Containers/Record.h>
#include <casacore/lattices/LatticeMath/LatticeCleaner.h>
#include <casacore/lattices/LatticeMath/LatticeCleanProgress.h>
#include <casacore/lattices/Lattices/TiledLineStepper.h>
#include <casacore/lattices/Lattices/LatticeStepper.h>
#include <casacore/lattices/Lattices/LatticeNavigator.h>
#include <casacore/lattices/Lattices/LatticeIterator.h>
#include <casacore/lattices/Lattices/TempLattice.h>
#include <casacore/lattices/LatticeMath/LatticeFFT.h>
#include <casacore/lattices/LEL/LatticeExpr.h>
#include <casacore/lattices/Lattices/SubLattice.h>
#include <casacore/lattices/LRegions/LCBox.h>
#include <casacore/casa/Arrays/Slicer.h>
#include <casacore/lattices/LEL/LatticeExpr.h>
#include <casacore/lattices/LEL/LatticeExprNode.h>
#include <casacore/casa/OS/HostInfo.h>
#include <casacore/casa/System/PGPlotter.h>
#include <casacore/casa/Arrays/ArrayError.h>
#include <casacore/casa/Arrays/ArrayIter.h>
#include <casacore/casa/Arrays/VectorIter.h>
#include <casacore/casa/Utilities/GenSort.h>
#include <casacore/casa/BasicSL/String.h>
#include <casacore/casa/Utilities/Assert.h>
#include <casacore/casa/Utilities/Fallible.h>
#include <casacore/casa/BasicSL/Constants.h>
#include <casacore/casa/Logging/LogSink.h>
#include <casacore/casa/Logging/LogMessage.h>
#include <casacore/casa/Arrays/ArrayMath.h>
#include <casacore/casa/Arrays/Matrix.h>
namespace casacore { //# NAMESPACE CASACORE - BEGIN
template<class T>
Bool LatticeCleaner<T>::validatePsf(const Lattice<T> & psf)
{
LogIO os(LogOrigin("LatticeCleaner", "validatePsf()", WHERE));
// Find the peak of the raw Psf
AlwaysAssert(psf.shape().product() != 0, AipsError);
T maxPsf=0;
itsPositionPeakPsf=IPosition(psf.shape().nelements(), 0);
findMaxAbsLattice(psf, maxPsf, itsPositionPeakPsf);
os << "Peak of PSF = " << maxPsf << " at " << itsPositionPeakPsf+1
<< LogIO::POST;
return True;
}
template<class T>
LatticeCleaner<T>::LatticeCleaner():
itsMask(0),
itsDirty(0),
itsXfr(0),
itsScaleSizes(0),
itsMaximumResidual(0.0),
itsStrengthOptimum(0.0),
itsChoose(True),
itsDoSpeedup(False),
itsIgnoreCenterBox(False),
itsSmallScaleBias(0.6),
itsStopAtLargeScaleNegative(False),
itsStopPointMode(-1),
itsDidStopPointMode(False),
itsJustStarting(True),
itsMaskThreshold(T(0.9))
{
itsMemoryMB=Double(HostInfo::memoryTotal()/1024)/16.0;
itsScales.resize(0);
itsScaleXfrs.resize(0);
itsDirtyConvScales.resize(0);
itsPsfConvScales.resize(0);
itsScaleMasks.resize(0);
itsScalesValid = False;
itsStartingIter = 0;
}
template<class T>
LatticeCleaner<T>::LatticeCleaner(const Lattice<T> & psf,
const Lattice<T> &dirty):
itsMask(0),
itsScaleSizes(0),
itsMaximumResidual(0.0),
itsStrengthOptimum(0.),
itsChoose(True),
itsDoSpeedup(False),
itsIgnoreCenterBox(False),
itsSmallScaleBias(0.6),
itsStopAtLargeScaleNegative(False),
itsStopPointMode(-1),
itsDidStopPointMode(False),
itsJustStarting(True)
{
AlwaysAssert(validatePsf(psf), AipsError);
// Check that everything is the same dimension and that none of the
// dimensions is zero length.
AlwaysAssert(psf.shape().nelements() == dirty.shape().nelements(),
AipsError);
AlwaysAssert(dirty.shape().product() != 0, AipsError);
// looks OK so make the convolver
// We need to guess the memory use. For the moment, we'll assume
// that about 4 scales will be used, giving about 32 TempLattices
// in all. Also we'll try not to take more that half of the memory
// Ah, but when we are doing a mosaic, its actually worse than this!
// So, we pass it in
itsMemoryMB=Double(HostInfo::memoryTotal()/1024)/16.0;
itsDirty = new TempLattice<T>(dirty.shape(), itsMemoryMB);
itsDirty->copyData(dirty);
itsXfr=new TempLattice<Complex>(psf.shape(), itsMemoryMB);
itsXfr->copyData(LatticeExpr<Complex>(toComplex(psf)));
LatticeFFT::cfft2d(*itsXfr, True);
itsScales.resize(0);
itsScaleXfrs.resize(0);
itsDirtyConvScales.resize(0);
itsPsfConvScales.resize(0);
itsScaleMasks.resize(0);
itsScalesValid = False;
itsStartingIter = 0;
}
template <class T> LatticeCleaner<T>::
LatticeCleaner(const LatticeCleaner<T> & other):
itsCleanType(other.itsCleanType),
itsMask(other.itsMask),
itsDirty(other.itsDirty),
itsXfr(other.itsXfr),
itsScales(other.itsScales),
itsScaleXfrs(other.itsScaleXfrs),
itsPsfConvScales(other.itsPsfConvScales),
itsDirtyConvScales(other.itsDirtyConvScales),
itsScaleMasks(other.itsScaleMasks),
itsStartingIter(other.itsStartingIter),
itsMaximumResidual(other.itsMaximumResidual),
itsStrengthOptimum(other.itsStrengthOptimum),
itsIgnoreCenterBox(other.itsIgnoreCenterBox),
itsSmallScaleBias(other.itsSmallScaleBias),
itsStopAtLargeScaleNegative(other.itsStopAtLargeScaleNegative),
itsStopPointMode(other.itsStopPointMode),
itsDidStopPointMode(other.itsDidStopPointMode),
itsJustStarting(other.itsJustStarting),
itsMaskThreshold(other.itsMaskThreshold)
{
}
template<class T> LatticeCleaner<T> & LatticeCleaner<T>::
operator=(const LatticeCleaner<T> & other) {
if (this != &other) {
itsCleanType = other.itsCleanType;
itsXfr = other.itsXfr;
itsMask = other.itsMask;
itsDirty = other.itsDirty;
itsScales = other.itsScales;
itsScaleXfrs = other.itsScaleXfrs;
itsPsfConvScales = other.itsPsfConvScales;
itsDirtyConvScales = other.itsDirtyConvScales;
itsScaleMasks = other.itsScaleMasks;
itsStartingIter = other.itsStartingIter;
itsMaximumResidual = other.itsMaximumResidual;
itsIgnoreCenterBox = other.itsIgnoreCenterBox;
itsSmallScaleBias = other.itsSmallScaleBias;
itsStopAtLargeScaleNegative = other.itsStopAtLargeScaleNegative;
itsStopPointMode = other.itsStopPointMode;
itsDidStopPointMode = other.itsDidStopPointMode;
itsJustStarting = other.itsJustStarting;
itsStrengthOptimum = other.itsStrengthOptimum;
itsMaskThreshold = other.itsMaskThreshold;
}
return *this;
}
template<class T> LatticeCleaner<T>::
~LatticeCleaner()
{
destroyScales();
if(itsDirty) delete itsDirty;
if(itsXfr) delete itsXfr;
if(itsMask) delete itsMask;
}
template<class T>
void LatticeCleaner<T>::update(const Lattice<T> &dirty)
{
AlwaysAssert(dirty.shape()==itsDirty->shape(), AipsError);
itsDirty->copyData(dirty);
LogIO os(LogOrigin("LatticeCleaner", "clean()", WHERE));
TempLattice<Complex> dirtyFT(itsDirty->shape(), itsMemoryMB);
dirtyFT.copyData(LatticeExpr<Complex>(toComplex(*itsDirty)));
LatticeFFT::cfft2d(dirtyFT, True);
// Now we can redo the relevant convolutions
TempLattice<Complex> cWork(itsDirty->shape(), itsMemoryMB);
for (Int scale=0; scale<itsNscales;scale++) {
// Dirty * scale
os << "Updating dirty * scale image for scale " << scale+1 << LogIO::POST;
LatticeExpr<Complex> dpsExpr( (dirtyFT)*(*itsScaleXfrs[scale]));
cWork.copyData(dpsExpr);
LatticeFFT::cfft2d(cWork, False);
AlwaysAssert(itsDirtyConvScales[scale], AipsError);
LatticeExpr<T> realWork2(real(cWork));
itsDirtyConvScales[scale]->copyData(realWork2);
}
}
// add a mask image
template<class T>
void LatticeCleaner<T>::setMask(Lattice<T> & mask, const T& maskThreshold)
{
itsMaskThreshold = maskThreshold;
IPosition maskShape = mask.shape();
IPosition dirtyShape = itsDirty->shape();
AlwaysAssert((mask.shape() == itsDirty->shape()), AipsError);
// This is not needed after the first steps
itsMask = new TempLattice<T>(mask.shape(), itsMemoryMB);
itsMask->copyData(mask);
if (itsScalesValid) {
makeScaleMasks();
}
}
template <class T>
Bool LatticeCleaner<T>::setcontrol(CleanEnums::CleanType cleanType,
const Int niter,
const Float gain,
const Quantity& threshold,
const Bool choose)
{
return setcontrol(cleanType, niter, gain, threshold, Quantity(0.0, "%"), choose);
}
// Set up the control parameters
template <class T>
Bool LatticeCleaner<T>::setcontrol(CleanEnums::CleanType cleanType,
const Int niter,
const Float gain,
const Quantity& aThreshold,
const Quantity& fThreshold,
const Bool choose)
{
itsCleanType=cleanType;
itsMaxNiter=niter;
itsGain=gain;
itsThreshold=aThreshold;
itsFracThreshold=fThreshold;
itsChoose=choose;
return True;
}
// Set up speedup parameters
template <class T>
void LatticeCleaner<T>::speedup(const Float nDouble)
{
itsDoSpeedup=True;
itsNDouble = nDouble;
};
// Do the clean as set up
template <class T>
Int LatticeCleaner<T>::clean(Lattice<T>& model,
LatticeCleanProgress* progress)
{
AlwaysAssert(model.shape()==itsDirty->shape(), AipsError);
LogIO os(LogOrigin("LatticeCleaner", "clean()", WHERE));
T tmpMaximumResidual;
tmpMaximumResidual=T();
Int nScalesToClean=itsNscales;
if (itsCleanType==CleanEnums::HOGBOM) {
os << LogIO::NORMAL1 << "Hogbom clean algorithm" << LogIO::POST;
nScalesToClean=1;
}
else if (itsCleanType==CleanEnums::MULTISCALE) {
if (nScalesToClean==1) {
os << LogIO::NORMAL1 << "Multi-scale clean with only one scale" << LogIO::POST;
}
else {
os << LogIO::NORMAL1 << "Multi-scale clean algorithm" << LogIO::POST;
}
}
Int scale;
Vector<T> scaleBias(nScalesToClean);
if (nScalesToClean > 1) {
os << LogIO::NORMAL1 << "Scale biases =";
for (scale=0;scale<nScalesToClean;scale++) {
scaleBias(scale) = 1 - itsSmallScaleBias *
itsScaleSizes(scale)/itsScaleSizes(nScalesToClean-1);
if(scale) os << ",";
os << " " << scaleBias(scale);
}
os << LogIO::POST;
} else {
scaleBias(0) = 1.0;
}
AlwaysAssert(itsScalesValid, AipsError);
// Find the peaks of the convolved Psfs
Vector<T> maxPsfConvScales(nScalesToClean);
for (scale=0;scale<nScalesToClean;scale++) {
IPosition positionPeakPsfConvScales(model.shape().nelements(), 0);
findMaxAbsLattice(*itsPsfConvScales[scale], maxPsfConvScales(scale),
positionPeakPsfConvScales);
if(nScalesToClean==1) {
os << LogIO::NORMAL << "Peak of PSF: " << maxPsfConvScales(scale)
<< " at " << positionPeakPsfConvScales+1 << LogIO::POST;
}
else {
os << LogIO::NORMAL
<< " " << scale+1 << " " << positionPeakPsfConvScales+1
<< " " << maxPsfConvScales(scale)
<< LogIO::POST;
}
if ( maxPsfConvScales(scale) < 0.0) {
os << "As Peak of PSF is negative, you should setscales again with a smaller scale size"
<< LogIO::SEVERE;
return -1;
}
}
// Define a subregion for the inner quarter
IPosition blcDirty(model.shape().nelements(), 0);
IPosition trcDirty(model.shape()-1);
if(itsMask){
os << "Cleaning using given mask" << LogIO::POST;
if (itsMaskThreshold<0) {
os << LogIO::NORMAL
<< "Mask thresholding is not used, values are interpreted as weights"
<<LogIO::POST;
} else {
os << LogIO::NORMAL
<< "Cleaning pixels with mask values above " << itsMaskThreshold
<< LogIO::POST;
}
Int nx=model.shape()(0);
Int ny=model.shape()(1);
AlwaysAssert(itsMask->shape()(0)==nx, AipsError);
AlwaysAssert(itsMask->shape()(1)==ny, AipsError);
LatticeStepper mls(itsMask->shape(),
IPosition(4, nx, ny, 1, 1),
IPosition(4, 0, 1, 3, 2));
RO_LatticeIterator<Float> maskli(*itsMask, mls);
maskli.reset();
Int xbeg=nx-1;
Int ybeg=ny-1;
Int xend=0;
Int yend=0;
for (Int iy=0;iy<ny;iy++) {
for (Int ix=0;ix<nx;ix++) {
if(maskli.matrixCursor()(ix,iy)>0.000001) {
xbeg=min(xbeg,ix);
ybeg=min(ybeg,iy);
xend=max(xend,ix);
yend=max(yend,iy);
}
}
}
if (!itsIgnoreCenterBox) {
if((xend - xbeg)>nx/2) {
xbeg=nx/4-1; //if larger than quarter take inner of mask
os << LogIO::WARN << "Mask span over more than half the x-axis: Considering inner half of the x-axis" << LogIO::POST;
}
if((yend - ybeg)>ny/2) {
ybeg=ny/4-1;
os << LogIO::WARN << "Mask span over more than half the y-axis: Considering inner half of the y-axis" << LogIO::POST;
}
xend=min(xend,xbeg+nx/2-1);
yend=min(yend,ybeg+ny/2-1);
}
blcDirty(0)=xbeg;
blcDirty(1)=ybeg;
trcDirty(0)=xend;
trcDirty(1)=yend;
}
else {
if (itsIgnoreCenterBox) {
os << LogIO::NORMAL << "Cleaning entire image" << LogIO::POST;
os << LogIO::NORMAL1 << "as per MF/WF" << LogIO::POST; // ???
}
else {
os << "Cleaning inner quarter of the image" << LogIO::POST;
for (Int i=0;i<Int(model.shape().nelements());i++) {
blcDirty(i)=model.shape()(i)/4;
trcDirty(i)=blcDirty(i)+model.shape()(i)/2-1;
if(trcDirty(i)<0) trcDirty(i)=1;
}
}
}
LCBox centerBox(blcDirty, trcDirty, model.shape());
PtrBlock<Lattice<T>* > scaleMaskSubs;
if (itsMask) {
scaleMaskSubs.resize(itsNscales);
for (Int is=0; is < itsNscales; is++) {
scaleMaskSubs[is] = new SubLattice<T>(*(itsScaleMasks[is]), centerBox);
}
}
// Start the iteration
Vector<T> maxima(nScalesToClean);
Block<IPosition> posMaximum(nScalesToClean);
Vector<T> totalFluxScale(nScalesToClean); totalFluxScale=0.0;
T totalFlux=0.0;
Int converged=0;
Int stopPointModeCounter = 0;
Int optimumScale=0;
itsStrengthOptimum=0.0;
IPosition positionOptimum(model.shape().nelements(), 0);
os << "Starting iteration"<< LogIO::POST;
itsIteration = itsStartingIter;
for (Int ii=itsStartingIter; ii < itsMaxNiter; ii++) {
itsIteration++;
// Find the peak residual
itsStrengthOptimum = 0.0;
optimumScale = 0;
for (scale=0; scale<nScalesToClean; scale++) {
// Find absolute maximum for the dirty image
SubLattice<T> dirtySub(*itsDirtyConvScales[scale], centerBox);
maxima(scale)=0;
posMaximum[scale]=IPosition(model.shape().nelements(), 0);
if (itsMask) {
findMaxAbsMaskLattice(dirtySub, *(scaleMaskSubs[scale]),
maxima(scale), posMaximum[scale]);
} else {
findMaxAbsLattice(dirtySub, maxima(scale), posMaximum[scale]);
}
// Remember to adjust the position for the window and for
// the flux scale
maxima(scale)/=maxPsfConvScales(scale);
maxima(scale) *= scaleBias(scale);
posMaximum[scale]+=blcDirty;
if(abs(maxima(scale))>abs(itsStrengthOptimum)) {
optimumScale=scale;
itsStrengthOptimum=maxima(scale);
positionOptimum=posMaximum[scale];
}
}
AlwaysAssert(optimumScale<nScalesToClean, AipsError);
// Now add to the total flux
totalFlux += (itsStrengthOptimum*itsGain);
totalFluxScale(optimumScale) += (itsStrengthOptimum*itsGain);
if(ii==itsStartingIter ) {
itsMaximumResidual=abs(itsStrengthOptimum);
tmpMaximumResidual=itsMaximumResidual;
os << "Initial maximum residual is " << itsMaximumResidual
<< LogIO::POST;
}
// Various ways of stopping:
// 1. stop if below threshold
if(abs(itsStrengthOptimum)<threshold() ) {
os << "Reached stopping threshold " << threshold() << " at iteration "<<
ii << LogIO::POST;
os << "Optimum flux is " << abs(itsStrengthOptimum) << LogIO::POST;
converged = 1;
break;
}
// 2. negatives on largest scale?
if ((nScalesToClean > 1) && itsStopAtLargeScaleNegative &&
optimumScale == (nScalesToClean-1) &&
itsStrengthOptimum < 0.0) {
os << "Reached negative on largest scale" << LogIO::POST;
converged = -2;
break;
}
// 3. stop point mode at work
if (itsStopPointMode > 0) {
if (optimumScale == 0) {
stopPointModeCounter++;
} else {
stopPointModeCounter = 0;
}
if (stopPointModeCounter >= itsStopPointMode) {
os << "Cleaned " << stopPointModeCounter <<
" consecutive components from the smallest scale, stopping prematurely"
<< LogIO::POST;
itsDidStopPointMode = True;
converged = -1;
break;
}
}
//4. Diverging large scale
//If actual value is 50% above the maximum residual. ..good chance it will not recover at this stage
if(((abs(itsStrengthOptimum)-abs(tmpMaximumResidual)) > (abs(tmpMaximumResidual)/2.0))
&& !(itsStopAtLargeScaleNegative)){
os << "Diverging due to large scale?"
<< LogIO::POST;
//clean is diverging most probably due to the large scale
converged=-2;
break;
}
//5. Diverging for some other reason; may just need another CS-style reconciling
if((abs(itsStrengthOptimum)-abs(tmpMaximumResidual)) > (abs(tmpMaximumResidual)/2.0)){
os << "Diverging due to unknown reason"
<< LogIO::POST;
converged=-3;
break;
}
if(progress) {
progress->info(False, itsIteration, itsMaxNiter, maxima,
posMaximum, itsStrengthOptimum,
optimumScale, positionOptimum,
totalFlux, totalFluxScale,
itsJustStarting );
itsJustStarting = False;
} else {
if (itsIteration == itsStartingIter + 1) {
os << "iteration MaximumResidual CleanedFlux" << LogIO::POST;
}
if ((itsIteration % (itsMaxNiter/10 > 0 ? itsMaxNiter/10 : 1)) == 0) {
//Good place to re-up the fiducial maximum residual
//tmpMaximumResidual=abs(itsStrengthOptimum);
os << itsIteration <<" "<<itsStrengthOptimum<<" "
<< totalFlux <<LogIO::POST;
}
}
T scaleFactor;
scaleFactor=itsGain*itsStrengthOptimum;
// Continuing: subtract the peak that we found from all dirty images
// Define a subregion so that that the peak is centered
IPosition support(model.shape());
support(0)=max(Int(itsScaleSizes(itsNscales-1)+0.5), support(0));
support(1)=max(Int(itsScaleSizes(itsNscales-1)+0.5), support(1));
IPosition inc(model.shape().nelements(), 1);
IPosition blc(positionOptimum-support/2);
IPosition trc(positionOptimum+support/2-1);
LCBox::verify(blc, trc, inc, model.shape());
IPosition blcPsf(blc+itsPositionPeakPsf-positionOptimum);
IPosition trcPsf(trc+itsPositionPeakPsf-positionOptimum);
LCBox::verify(blcPsf, trcPsf, inc, model.shape());
makeBoxesSameSize(blc,trc,blcPsf,trcPsf);
LCBox subRegion(blc, trc, model.shape());
LCBox subRegionPsf(blcPsf, trcPsf, model.shape());
SubLattice<T> modelSub(model, subRegion, True);
SubLattice<T> scaleSub(*itsScales[optimumScale], subRegionPsf, True);
// Now do the addition of this scale to the model image....
LatticeExpr<T> add(scaleFactor*scaleSub);
addTo(modelSub, add);
// and then subtract the effects of this scale from all the precomputed
// dirty convolutions.
for (scale=0;scale<nScalesToClean;scale++) {
SubLattice<T> dirtySub(*itsDirtyConvScales[scale], subRegion, True);
AlwaysAssert(itsPsfConvScales[index(scale,optimumScale)], AipsError);
SubLattice<T> psfSub(*itsPsfConvScales[index(scale,optimumScale)],
subRegionPsf, True);
LatticeExpr<T> sub((-scaleFactor)*psfSub);
addTo(dirtySub, sub);
}
}
// End of iteration
for (scale=0;scale<nScalesToClean;scale++) {
os << LogIO::NORMAL
<< " " << scale+1 << " " << totalFluxScale(scale)
<< LogIO::POST;
}
if(itsMask) {
for (Int is=0; is < itsNscales; is++) {
delete scaleMaskSubs[is];
}
scaleMaskSubs.resize(0);
}
// Finish off the plot, etc.
if(progress) {
progress->info(True, itsIteration, itsMaxNiter, maxima, posMaximum,
itsStrengthOptimum,
optimumScale, positionOptimum,
totalFlux, totalFluxScale);
}
if(!converged) {
os << "Failed to reach stopping threshold" << LogIO::POST;
}
return converged;
}
template<class T>
Bool LatticeCleaner<T>::findMaxAbsLattice(const Lattice<T>& lattice,
T& maxAbs,
IPosition& posMaxAbs)
{
posMaxAbs = IPosition(lattice.shape().nelements(), 0);
maxAbs=0.0;
const IPosition tileShape = lattice.niceCursorShape();
TiledLineStepper ls(lattice.shape(), tileShape, 0);
{
RO_LatticeIterator<T> li(lattice, ls);
for(li.reset();!li.atEnd();li++) {
IPosition posMax=li.position();
IPosition posMin=li.position();
T maxVal=0.0;
T minVal=0.0;
minMax(minVal, maxVal, posMin, posMax, li.cursor());
if(abs(minVal)>abs(maxAbs)) {
maxAbs=minVal;
posMaxAbs=li.position();
posMaxAbs(0)=posMin(0);
}
if(abs(maxVal)>abs(maxAbs)) {
maxAbs=maxVal;
posMaxAbs=li.position();
posMaxAbs(0)=posMax(0);
}
}
}
return True;
}
template<class T>
Bool LatticeCleaner<T>::findMaxAbsMaskLattice(const Lattice<T>& lattice,
const Lattice<T>& mask,
T& maxAbs,
IPosition& posMaxAbs)
{
posMaxAbs = IPosition(lattice.shape().nelements(), 0);
maxAbs=0.0;
const IPosition tileShape = lattice.niceCursorShape();
TiledLineStepper ls(lattice.shape(), tileShape, 0);
{
RO_LatticeIterator<T> li(lattice, ls);
RO_LatticeIterator<T> mi(mask, ls);
for(li.reset(),mi.reset();!li.atEnd();li++, mi++) {
IPosition posMax=li.position();
IPosition posMin=li.position();
IPosition posMaxMask=li.position();
IPosition posMinMask=li.position();
T maxVal=0.0;
T minVal=0.0;
minMaxMasked(minVal, maxVal, posMin, posMax, li.cursor(), mi.cursor());
if (itsMaskThreshold<0) {
// Mask threhsolding is not used, i.e. mask values are interpreted as weights.
// This means that minVal and maxVal are optima of the mask * lattice product,
// we need just values of lattice and have to redetermine them.
minVal = li.cursor()(posMin);
maxVal = li.cursor()(posMax);
}
if(abs(minVal)>abs(maxAbs)) {
maxAbs=minVal;
posMaxAbs=li.position();
posMaxAbs(0)=posMin(0);
}
if(abs(maxVal)>abs(maxAbs)) {
maxAbs=maxVal;
posMaxAbs=li.position();
posMaxAbs(0)=posMax(0);
}
}
}
return True;
}
template<class T>
Bool LatticeCleaner<T>::setscales(const Int nscales, const Float scaleInc)
{
LogIO os(LogOrigin("deconvolver", "setscales()", WHERE));
itsNscales=nscales;
if(itsNscales<1) {
os << "Using default of 5 scales" << LogIO::POST;
itsNscales=5;
}
Vector<Float> scaleSizes(itsNscales);
// Validate scales
os << "Creating " << itsNscales << " scales" << LogIO::POST;
scaleSizes(0) = 0.00001 * scaleInc;
os << "scale 1 = 0.0 arcsec" << LogIO::POST;
for (Int scale=1; scale<itsNscales;scale++) {
scaleSizes(scale) =
scaleInc * pow(10.0, (Float(scale)-2.0)/2.0);
os << "scale " << scale+1 << " = " << scaleSizes(scale)
<< " arcsec" << LogIO::POST;
}
return setscales(scaleSizes);
}
// We calculate all the scales and the corresponding convolutions
// and cross convolutions.
template<class T>
Bool LatticeCleaner<T>::setscales(const Vector<Float>& scaleSizes)
{
LogIO os(LogOrigin("deconvolver", "setscales()", WHERE));
Int scale;
if(itsScales.nelements()>0) {
destroyScales();
}
destroyMasks();
itsNscales=scaleSizes.nelements();
// Residual, psf, and mask, plus cross terms
// e.g. for 5 scales this is 45. for 6 it is 60.
Int nImages=3*itsNscales+itsNscales*(itsNscales+1);
os << "Expect to use " << nImages << " scratch images" << LogIO::POST;
// Now we can update the size of memory allocated
itsMemoryMB=0.5*Double(HostInfo::memoryTotal()/1024)/Double(nImages);
os << "Maximum memory allocated per image " << itsMemoryMB << "MB" << LogIO::POST;
itsScaleSizes.resize(itsNscales);
itsScaleSizes=scaleSizes; // make a copy that we can call our own
GenSort<Float>::sort(itsScaleSizes);
itsScales.resize(itsNscales);
itsDirtyConvScales.resize(itsNscales);
itsScaleMasks.resize(itsNscales);
itsScaleXfrs.resize(itsNscales);
itsPsfConvScales.resize((itsNscales+1)*(itsNscales+1));
for(scale=0; scale<itsNscales;scale++) {
itsScales[scale] = 0;
itsDirtyConvScales[scale] = 0;
itsScaleMasks[scale] = 0;
itsScaleXfrs[scale] = 0;
}
for(scale=0; scale<((itsNscales+1)*(itsNscales+1));scale++) {
itsPsfConvScales[scale] = 0;
}
AlwaysAssert(itsDirty, AipsError);
TempLattice<Complex> dirtyFT(itsDirty->shape(), itsMemoryMB);
dirtyFT.copyData(LatticeExpr<Complex>(toComplex(*itsDirty)));
LatticeFFT::cfft2d(dirtyFT, True);
for (scale=0; scale<itsNscales;scale++) {
os << "Calculating scale image and Fourier transform for scale " << scale+1 << LogIO::POST;
itsScales[scale] = new TempLattice<T>(itsDirty->shape(),
itsMemoryMB);
AlwaysAssert(itsScales[scale], AipsError);
// First make the scale
makeScale(*itsScales[scale], scaleSizes(scale));
itsScaleXfrs[scale] = new TempLattice<Complex> (itsScales[scale]->shape(),
itsMemoryMB);
// Now store the XFR
itsScaleXfrs[scale]->copyData(LatticeExpr<Complex>(toComplex(*itsScales[scale])));
// Now FFT
LatticeFFT::cfft2d(*itsScaleXfrs[scale], True);
}
// Now we can do all the convolutions
TempLattice<Complex> cWork(itsDirty->shape(), itsMemoryMB);
for (scale=0; scale<itsNscales;scale++) {
os << "Calculating convolutions for scale " << scale+1 << LogIO::POST;
// PSF * scale
LatticeExpr<Complex> ppsExpr( (*itsXfr)*(*itsScaleXfrs[scale]));
cWork.copyData(ppsExpr);
LatticeFFT::cfft2d(cWork, False);
itsPsfConvScales[scale] = new TempLattice<T>(itsDirty->shape(),
itsMemoryMB);
AlwaysAssert(itsPsfConvScales[scale], AipsError);
LatticeExpr<T> realWork(real(cWork));
itsPsfConvScales[scale]->copyData(realWork);
// Dirty * scale
LatticeExpr<Complex> dpsExpr( (dirtyFT)*(*itsScaleXfrs[scale]));
cWork.copyData(dpsExpr);
LatticeFFT::cfft2d(cWork, False);
itsDirtyConvScales[scale] = new TempLattice<T>(itsDirty->shape(),
itsMemoryMB);
AlwaysAssert(itsDirtyConvScales[scale], AipsError);
LatticeExpr<T> realWork2(real(cWork));
itsDirtyConvScales[scale]->copyData(realWork2);
for (Int otherscale=scale;otherscale<itsNscales;otherscale++) {
AlwaysAssert(index(scale, otherscale)<Int(itsPsfConvScales.nelements()),
AipsError);
// PSF * scale * otherscale
LatticeExpr<Complex> ppsoExpr( (*itsXfr)*conj(*itsScaleXfrs[scale])*(*itsScaleXfrs[otherscale]));
cWork.copyData(ppsoExpr);
LatticeFFT::cfft2d(cWork, False);
itsPsfConvScales[index(scale,otherscale)] =
new TempLattice<T>(itsDirty->shape(), itsMemoryMB);
AlwaysAssert(itsPsfConvScales[index(scale,otherscale)], AipsError);
LatticeExpr<T> realWork3(real(cWork));
itsPsfConvScales[index(scale,otherscale)]->copyData(realWork3);
}
}
itsScalesValid=True;
if (itsMask) {
makeScaleMasks();
}
return True;
}
// Make a single scale size image
template <class T>
void LatticeCleaner<T>::makeScale(Lattice<T>& scale, const Float& scaleSize)
{
Int nx=scale.shape()(0);
Int ny=scale.shape()(1);
Matrix<T> iscale(nx, ny);
iscale=0.0;
Double refi=nx/2;
Double refj=ny/2;
if(scaleSize==0.0) {
iscale(Int(refi), Int(refj)) = 1.0;
}
else {
AlwaysAssert(scaleSize>0.0,AipsError);
Int mini = max( 0, (Int)(refi-scaleSize));
Int maxi = min(nx-1, (Int)(refi+scaleSize));
Int minj = max( 0, (Int)(refj-scaleSize));
Int maxj = min(ny-1, (Int)(refj+scaleSize));
Float ypart=0.0;
Float volume=0.0;
Float rad2=0.0;
Float rad=0.0;
for (Int j=minj;j<=maxj;j++) {
ypart = square( (refj - (Double)(j)) / scaleSize );
for (Int i=mini;i<=maxi;i++) {
rad2 = ypart + square( (refi - (Double)(i)) / scaleSize );
if (rad2 < 1.0) {
if (rad2 <= 0.0) {
rad = 0.0;
} else {
rad = sqrt(rad2);
}
iscale(i,j) = (1.0 - rad2) * spheroidal(rad);
volume += iscale(i,j);
} else {
iscale(i,j) = 0.0;
}
}
}
iscale/=volume;
}
scale.putSlice(iscale, IPosition(scale.ndim(),0), IPosition(scale.ndim(),1));
}
// Calculate the spheroidal function
template<class T>
Float LatticeCleaner<T>::spheroidal(Float nu) {
if (nu <= 0) {
return 1.0;
} else if (nu >= 1.0) {
return 0.0;
} else {
uInt np = 5;
uInt nq = 3;
Matrix<float> p(np, 2);
Matrix<float> q(nq, 2);
p(0,0) = 8.203343e-2;
p(1,0) = -3.644705e-1;
p(2,0) = 6.278660e-1;
p(3,0) = -5.335581e-1;
p(4,0) = 2.312756e-1;
p(0,1) = 4.028559e-3;
p(1,1) = -3.697768e-2;
p(2,1) = 1.021332e-1;
p(3,1) = -1.201436e-1;
p(4,1) = 6.412774e-2;
q(0,0) = 1.0000000e0;
q(1,0) = 8.212018e-1;
q(2,0) = 2.078043e-1;
q(0,1) = 1.0000000e0;
q(1,1) = 9.599102e-1;
q(2,1) = 2.918724e-1;
uInt part = 0;
Float nuend = 0.0;
if (nu >= 0.0 && nu < 0.75) {
part = 0;
nuend = 0.75;
} else if (nu >= 0.75 && nu <= 1.00) {
part = 1;
nuend = 1.0;
}
Float top = p(0,part);
Float delnusq = pow(nu,2.0) - pow(nuend,2.0);
uInt k;
for (k=1; k<np; k++) {
top += p(k, part) * pow(delnusq, (Float)k);
}
Float bot = q(0, part);
for (k=1; k<nq; k++) {