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Current view: top level - synthesis/ImagerObjects - SDAlgorithmMSMFS.cc (source / functions) Hit Total Coverage
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Date: 2024-10-28 15:53:10 Functions: 0 8 0.0 %

          Line data    Source code
       1             : //# SDAlgorithmMSMFS.cc: Implementation of SDAlgorithmMSMFS classes
       2             : //# Copyright (C) 1996,1997,1998,1999,2000,2001,2002,2003
       3             : //# Associated Universities, Inc. Washington DC, USA.
       4             : //#
       5             : //# This library is free software; you can redistribute it and/or modify it
       6             : //# under the terms of the GNU Library General Public License as published by
       7             : //# the Free Software Foundation; either version 2 of the License, or (at your
       8             : //# option) any later version.
       9             : //#
      10             : //# This library is distributed in the hope that it will be useful, but WITHOUT
      11             : //# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
      12             : //# FITNESS FOR A PARTICULAR PURPOSE.  See the GNU Library General Public
      13             : //# License for more details.
      14             : //#
      15             : //# You should have received a copy of the GNU Library General Public License
      16             : //# along with this library; if not, write to the Free Software Foundation,
      17             : //# Inc., 675 Massachusetts Ave, Cambridge, MA 02139, USA.
      18             : //#
      19             : //# Correspondence concerning AIPS++ should be addressed as follows:
      20             : //#        Internet email: casa-feedback@nrao.edu.
      21             : //#        Postal address: AIPS++ Project Office
      22             : //#                        National Radio Astronomy Observatory
      23             : //#                        520 Edgemont Road
      24             : //#                        Charlottesville, VA 22903-2475 USA
      25             : //#
      26             : //# $Id$
      27             : 
      28             : #include <casacore/casa/Arrays/ArrayMath.h>
      29             : #include <casacore/casa/OS/HostInfo.h>
      30             : #include <synthesis/ImagerObjects/SDAlgorithmMSMFS.h>
      31             : #include <components/ComponentModels/SkyComponent.h>
      32             : #include <components/ComponentModels/ComponentList.h>
      33             : #include <casacore/images/Images/TempImage.h>
      34             : #include <casacore/images/Images/SubImage.h>
      35             : #include <casacore/images/Regions/ImageRegion.h>
      36             : #include <casacore/casa/OS/File.h>
      37             : #include <casacore/lattices/LEL/LatticeExpr.h>
      38             : #include <casacore/lattices/Lattices/TiledLineStepper.h>
      39             : #include <casacore/lattices/Lattices/LatticeStepper.h>
      40             : #include <casacore/lattices/Lattices/LatticeIterator.h>
      41             : #include <synthesis/TransformMachines/StokesImageUtil.h>
      42             : #include <casacore/coordinates/Coordinates/StokesCoordinate.h>
      43             : #include <casacore/casa/Exceptions/Error.h>
      44             : #include <casacore/casa/BasicSL/String.h>
      45             : #include <casacore/casa/Utilities/Assert.h>
      46             : #include <casacore/casa/OS/Directory.h>
      47             : #include <casacore/tables/Tables/TableLock.h>
      48             : #include <imageanalysis/ImageAnalysis/CasaImageBeamSet.h>
      49             : 
      50             : #include<synthesis/ImagerObjects/SIMinorCycleController.h>
      51             : 
      52             : #include <sstream>
      53             : 
      54             : #include <casacore/casa/Logging/LogMessage.h>
      55             : #include <casacore/casa/Logging/LogIO.h>
      56             : #include <casacore/casa/Logging/LogSink.h>
      57             : 
      58             : #include <casacore/casa/System/Choice.h>
      59             : #include <msvis/MSVis/StokesVector.h>
      60             : 
      61             : 
      62             : using namespace casacore;
      63             : namespace casa { //# NAMESPACE CASA - BEGIN
      64             : 
      65             : 
      66           0 :   SDAlgorithmMSMFS::SDAlgorithmMSMFS( uInt nTaylorTerms, Vector<Float> scalesizes, Float smallscalebias):
      67             :     SDAlgorithmBase(),
      68             :     //    itsImages(),
      69           0 :     itsMatPsfs(), itsMatResiduals(), itsMatModels(),
      70           0 :     itsNTerms(nTaylorTerms),
      71           0 :     itsScaleSizes(scalesizes),
      72           0 :     itsSmallScaleBias(smallscalebias),
      73           0 :     itsMTCleaner(),
      74           0 :     itsMTCsetup(false)
      75             :   {
      76           0 :     itsAlgorithmName=String("mtmfs");
      77           0 :     if( itsScaleSizes.nelements()==0 ){ itsScaleSizes.resize(1); itsScaleSizes[0]=0.0; }
      78           0 :   }
      79             : 
      80           0 :   SDAlgorithmMSMFS::~SDAlgorithmMSMFS()
      81             :   {
      82             : 
      83           0 :   }
      84             : 
      85             : 
      86             :   //  void SDAlgorithmMSMFS::initializeDeconvolver( Float &peakresidual, Float &modelflux )
      87           0 :   void SDAlgorithmMSMFS::initializeDeconvolver()
      88             :   {
      89           0 :     LogIO os( LogOrigin("SDAlgorithmMSMFS","initializeDeconvolver",WHERE) );
      90             : 
      91           0 :     AlwaysAssert( (bool) itsImages, AipsError );
      92           0 :     AlwaysAssert( itsNTerms == itsImages->getNTaylorTerms() , AipsError );
      93             : 
      94           0 :     itsMatPsfs.resize( 2*itsNTerms-1 );
      95           0 :     itsMatResiduals.resize( itsNTerms );
      96           0 :     itsMatModels.resize( itsNTerms );
      97             : 
      98             :     ////  Why is this needed ?  I hope this is by reference.
      99           0 :     for(uInt tix=0; tix<2*itsNTerms-1; tix++)
     100             :     {
     101           0 :         if(tix<itsNTerms)
     102             :         {
     103           0 :           (itsImages->residual(tix))->get( itsMatResiduals[tix], true );
     104           0 :           (itsImages->model(tix))->get( itsMatModels[tix], true );
     105             :         }
     106           0 :         (itsImages->psf(tix))->get( itsMatPsfs[tix], true );
     107             :     }
     108             : 
     109           0 :     itsImages->mask()->get( itsMatMask, true );
     110             : 
     111             :     //// Initialize the MultiTermMatrixCleaner.
     112             : 
     113             :     ///  ----------- do once ----------
     114           0 :     if( itsMTCsetup == false)
     115             :     {
     116             :         //cout << "Setting up the MT Cleaner once" << endl;
     117             :         //Vector<Float> scalesizes(1); scalesizes[0]=0.0;
     118           0 :         itsMTCleaner.setscales( itsScaleSizes );
     119             : 
     120           0 :         if(itsSmallScaleBias > 1)
     121             :         {
     122           0 :           os << LogIO::WARN << "Acceptable smallscalebias values are [-1,1].Changing smallscalebias from " << itsSmallScaleBias <<" to 1." << LogIO::POST;
     123           0 :           itsSmallScaleBias = 1;
     124             :         }
     125             : 
     126           0 :         if(itsSmallScaleBias < -1)
     127             :         {
     128           0 :           os << LogIO::WARN << "Acceptable smallscalebias values are [-1,1].Changing smallscalebias from " << itsSmallScaleBias <<" to -1." << LogIO::POST;
     129           0 :           itsSmallScaleBias = -1;
     130             :         }
     131             : 
     132             : 
     133           0 :         itsMTCleaner.setSmallScaleBias(itsSmallScaleBias);
     134           0 :         itsMTCleaner.setntaylorterms( itsNTerms );
     135           0 :         itsMTCleaner.initialise( itsImages->getShape()[0], itsImages->getShape()[1] );
     136             : 
     137           0 :         for(uInt tix=0; tix<2*itsNTerms-1; tix++)
     138             :         {
     139           0 :         Matrix<Float> tempMat;
     140           0 :         tempMat.reference( itsMatPsfs[tix] );
     141           0 :         itsMTCleaner.setpsf( tix, tempMat );
     142             :         ///     itsMTCleaner.setpsf( tix, itsMatPsfs[tix] );
     143           0 :         }
     144           0 :         itsMTCsetup=true;
     145             :     }
     146             :     /// -----------------------------------------
     147             : 
     148             :     /*
     149             :     /// Find initial max vals..
     150             :     findMaxAbsMask( itsMatResiduals[0], itsMatMask, itsPeakResidual, itsMaxPos );
     151             :     itsModelFlux = sum( itsMatModels[0] );
     152             : 
     153             :     peakresidual = itsPeakResidual;
     154             :     modelflux = itsModelFlux;
     155             :     */
     156             : 
     157             :     // Parts to be repeated at each minor cycle start....
     158             : 
     159           0 :     Matrix<Float> tempmask(itsMatMask);
     160           0 :     itsMTCleaner.setmask( tempmask );
     161             : 
     162           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     163             :     {
     164           0 :         Matrix<Float> tempMat;
     165           0 :         tempMat.reference( itsMatResiduals[tix] );
     166           0 :         itsMTCleaner.setresidual( tix, tempMat );
     167             :         //      itsMTCleaner.setresidual( tix, itsMatResiduals[tix] );
     168             : 
     169           0 :         Matrix<Float> tempMat2;
     170           0 :         tempMat2.reference( itsMatModels[tix] );
     171           0 :         itsMTCleaner.setmodel( tix, tempMat2 );
     172             :         //      itsMTCleaner.setmodel( tix, itsMatModels[tix] );
     173           0 :     }
     174             : 
     175             :     // Print some useful info about the frequency setup for this MTMFS run
     176           0 :     itsImages->calcFractionalBandwidth();
     177           0 :   }
     178             : 
     179           0 :   Long SDAlgorithmMSMFS::estimateRAM(const vector<int>& imsize){
     180             :     ///taken from imager_resource_predictor.py
     181             : 
     182           0 :     Long mem=0;
     183           0 :     IPosition shp;
     184           0 :     if(itsImages){
     185           0 :       shp=itsImages->getShape();
     186             :     }
     187           0 :     else if(imsize.size() >1){
     188           0 :       shp=IPosition(imsize);
     189             :     }
     190             :     else
     191           0 :       return 0;
     192             :       //throw(AipsError("Deconvolver cannot estimate the memory usage at this point"));
     193             : 
     194             :       // psf patches in the Hessian
     195           0 :     Long nscales=itsScaleSizes.nelements();
     196           0 :     Long n4d = (nscales * (nscales+1) / 2.0) * (itsNTerms * (itsNTerms+1) / 2);
     197             : 
     198           0 :       Long nsupport = Long(Float(100.0/Float(shp(0)))* Float(100.0/Float(shp(1))* Float(n4d + nscales)));
     199             : 
     200           0 :       Long nfull = 2 + 2 + 3 * nscales + 3 * itsNTerms + (2 * itsNTerms - 1) + 2 * itsNTerms * nscales;
     201           0 :       Long nfftserver = 1 + 2*2 ; /// 1 float and 2 complex
     202             : 
     203           0 :       Long mystery = 1 + 1;  /// TODO
     204             : 
     205           0 :       Long ntotal = nsupport + nfull + nfftserver + mystery;
     206           0 :       mem=sizeof(Float)*(shp(0))*(shp(1))*ntotal/1024;
     207             : 
     208           0 :     return mem;
     209           0 :   }
     210             : 
     211           0 :   void SDAlgorithmMSMFS::takeOneStep( Float loopgain, Int cycleNiter, Float cycleThreshold, Float &peakresidual, Float &modelflux, Int &iterdone)
     212             :   {
     213             : 
     214           0 :     iterdone = itsMTCleaner.mtclean( cycleNiter, 0.0, loopgain, cycleThreshold );
     215             : 
     216           0 :     if( iterdone==-2 ) throw(AipsError("MT-Cleaner error : Non-invertible Hessian. Please check if the multi-frequency data selection is appropriate for a polynomial fit of the desired order."));
     217             : 
     218           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     219             :     {
     220           0 :         Matrix<Float> tempMat;
     221           0 :         tempMat.reference( itsMatModels[tix] );
     222             : 
     223           0 :         itsMTCleaner.getmodel( tix, tempMat ); //itsMatModels[tix] );
     224           0 :     }
     225             : 
     226             :     /////////////////
     227             :     //findMaxAbs( itsMatResiduals[0], itsPeakResidual, itsMaxPos );
     228             :     //peakresidual = itsPeakResidual;
     229             : 
     230           0 :     peakresidual = itsMTCleaner.getpeakresidual();
     231             :     // cout << "Peak res from matR : " << peakresidual << endl; // Uncomment for debugging
     232             : 
     233             : 
     234             :     // Retrieve residual to be saved to the .residual file in finalizeDeconvolver
     235           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     236             :     {
     237           0 :       casacore::Matrix<Float> tmp;
     238           0 :       itsMTCleaner.getresidual(tix, tmp); // possible room for optimization here -> get residual without extra tmp copy? maybe change getResidual to accept an array?
     239           0 :       itsMatResiduals[tix] = tmp;
     240           0 :     }
     241             : 
     242           0 :     peakresidual = max(abs(itsMatResiduals[0]*itsMatMask));
     243             :     // cout << "Peak res from new math : " << peakresidual << endl; // Uncomment for debugging
     244           0 :     modelflux = sum( itsMatModels[0] ); // Performance hog ?
     245             : 
     246           0 :   }         
     247             : 
     248           0 :   void SDAlgorithmMSMFS::finalizeDeconvolver()
     249             :   {
     250             :     //    itsResidual.put( itsMatResidual );
     251             :     //    itsModel.put( itsMatModel );
     252             : 
     253             :     // Why is this needed ?  If the matrices are by reference, then why do we need this ?
     254           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     255             :     {
     256           0 :         (itsImages->residual(tix))->put( itsMatResiduals[tix] );
     257           0 :         (itsImages->model(tix))->put( itsMatModels[tix] );
     258             :     }
     259           0 :   }
     260             : 
     261           0 :   void SDAlgorithmMSMFS::restore(std::shared_ptr<SIImageStore> imagestore)
     262             :   {
     263             : 
     264           0 :     LogIO os( LogOrigin("SDAlgorithmMSMFS","restore",WHERE) );
     265             : 
     266           0 :     if( ! imagestore->hasResidualImage() ) return;
     267             :     
     268             :     // Compute principal solution ( if it hasn't already been done to this ImageStore......  )
     269             :     //////  Put some image misc info in here, to say if it has been done or not.
     270             : 
     271             :     // Loop over polarization planes here, as MTC knows only about Matrices.
     272             :     Int nSubChans, nSubPols;
     273             :     
     274           0 :     queryDesiredShape(nSubChans, nSubPols, imagestore->getShape());
     275             :     
     276             :     // CAS-13401 : Store restoring beam per plane, so it can be set in the final restored image.
     277           0 :     ImageBeamSet restoringBeams;
     278           0 :     restoringBeams.resize(nSubChans, nSubPols);
     279             : 
     280           0 :     for( Int chanid=0; chanid<nSubChans;chanid++) // redundant since only 1 chan
     281             :     {
     282             : 
     283           0 :         for( Int polid=0; polid<nSubPols;polid++) // one pol plane at a time
     284             :       {
     285           0 :             itsImages = imagestore->getSubImageStore( 0, 1, chanid, nSubChans, polid, nSubPols );
     286             : 
     287             :             //cout << "Units for chan " << chanid << " and pol " << polid << " are " << itsImages->image()->units().getName() << endl;
     288             : 
     289             :     ///  ----------- do once if trying to 'only restore' without model ----------
     290           0 :     if( itsMTCsetup == false)
     291             :       {
     292             : 
     293           0 :         itsMatPsfs.resize( 2*itsNTerms-1 );
     294           0 :         for(uInt tix=0; tix<2*itsNTerms-1; tix++)
     295             :           {
     296           0 :             (itsImages->psf(tix))->get( itsMatPsfs[tix], True );
     297             :           }
     298             : 
     299             :         //cout << "Setting up the MT Cleaner once" << endl;
     300             :         //Vector<Float> scalesizes(1); scalesizes[0]=0.0;
     301           0 :         itsMTCleaner.setscales( itsScaleSizes );
     302           0 :         itsMTCleaner.setntaylorterms( itsNTerms );
     303           0 :         itsMTCleaner.initialise( itsImages->getShape()[0], itsImages->getShape()[1] );
     304             : 
     305           0 :         for(uInt tix=0; tix<2*itsNTerms-1; tix++)
     306             :           {
     307           0 :             Matrix<Float> tempMat;
     308           0 :             tempMat.reference( itsMatPsfs[tix] );
     309           0 :             itsMTCleaner.setpsf( tix, tempMat );
     310             :             /// itsMTCleaner.setpsf( tix, itsMatPsfs[tix] );
     311           0 :           }
     312           0 :         itsMTCsetup=true;
     313             :       }
     314             :     /// -----------------------------------------
     315             : 
     316             : 
     317           0 :     Vector<TempImage<Float> > tempResOrig(itsNTerms);
     318             : 
     319             :     // Set residual images into mtcleaner
     320           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     321             :       {
     322           0 :         Array<Float> tempArr;
     323           0 :         (itsImages->residual(tix))->get( tempArr, True );
     324           0 :         Matrix<Float> tempMat;
     325           0 :         tempMat.reference( tempArr );
     326           0 :         itsMTCleaner.setresidual( tix, tempMat );
     327             : 
     328             :         // Also save them temporarily (copies)
     329           0 :         tempResOrig[tix] = TempImage<Float>(itsImages->getShape(), itsImages->residual(tix)->coordinates());
     330           0 :         tempResOrig[tix].copyData( LatticeExpr<Float>(* ( itsImages->residual(tix) ) ) );
     331           0 :       }
     332             : 
     333             :     // Modify the original in place
     334           0 :     itsMTCleaner.computeprincipalsolution();
     335             : 
     336           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     337             :       {
     338           0 :         Matrix<Float> tempRes;
     339           0 :         itsMTCleaner.getresidual(tix,tempRes);
     340           0 :         (itsImages->residual(tix))->put( tempRes );
     341           0 :       }
     342             : 
     343             :     // Calculate restored image and alpha using modified residuals
     344           0 :     SDAlgorithmBase::restore( itsImages );
     345             :     
     346             :     // This is required because imageInfo() only contains the beam for this chan/pol.
     347           0 :     GaussianBeam thisBeam = itsImages->image(0)->imageInfo().getBeamSet().getBeam(chanid, polid);
     348           0 :     restoringBeams.setBeam(chanid, polid, thisBeam);
     349             : 
     350             :     // Put back original unmodified residuals.o
     351           0 :     for(uInt tix=0; tix<itsNTerms; tix++) {
     352           0 :       (itsImages->residual(tix))->copyData( LatticeExpr<Float>( tempResOrig(tix) ) );
     353             :       }
     354           0 :       } // for polid loop
     355             :     }// for chanid loop
     356             : 
     357             : 
     358             :     // This log message is important. This call of imagestore->image(...) is the first call if there is
     359             :     // a multi-channel or multi-pol image. This is what will set the units correctly. Ref. CAS-13153
     360           0 :     os << LogIO::POST << "Restored images : ";
     361           0 :     for(uInt tix=0; tix<itsNTerms; tix++)
     362             :       {
     363           0 :         os << LogIO::POST << imagestore->image(tix)->name() << "  (model=" << imagestore->model(tix)->name() << ") " ;
     364             : 
     365             :       // CAS-13401 : Set the per-chan per-pol beam info for the restored image.
     366           0 :       ImageInfo iminf = imagestore->image(tix)->imageInfo();
     367             :       
     368           0 :       iminf.removeRestoringBeam();
     369             : 
     370             :       // If restoringbeam="common", then calculate and only set one beam
     371           0 :       if (itsRestoringBeam.isNull() && itsUseBeam == "common"){
     372           0 :         GaussianBeam cbeam = CasaImageBeamSet(restoringBeams).getCommonBeam();
     373           0 :         iminf.setRestoringBeam(cbeam);
     374           0 :       }
     375           0 :       else if (! itsRestoringBeam.isNull()) {
     376           0 :         iminf.setRestoringBeam(itsRestoringBeam);
     377             :       }
     378             :       else {
     379           0 :         iminf.setBeams(restoringBeams);
     380             :       }
     381           0 :       imagestore->image(tix)->setImageInfo(iminf);
     382             : 
     383           0 :       }
     384           0 :     os << LogIO::POST << endl;
     385             : 
     386             :     //cout << "Units for  " << imagestore->image()->name() << "  aaaaaare " << imagestore->image()->units().getName() << endl;
     387           0 :   }// ::restore
     388             : 
     389             : 
     390             :   /*
     391             :   void SDAlgorithmMSMFS::restorePlane()
     392             :   {
     393             : 
     394             :     LogIO os( LogOrigin("SDAlgorithmMSMFS","restorePlane",WHERE) );
     395             : 
     396             :     try
     397             :       {
     398             :         // Fit a Gaussian to the PSF.
     399             :         GaussianBeam beam = itsImages->getPSFGaussian();
     400             : 
     401             :         os << "Restore with beam : "
     402             :            << beam.getMajor(Unit("arcmin")) << " arcmin, "
     403             :            << beam.getMinor(Unit("arcmin"))<< " arcmin, "
     404             :            << beam.getPA(Unit("deg")) << " deg" << LogIO::POST;
     405             : 
     406             :         // Compute principal solution ( if it hasn't already been done to this ImageStore......  )
     407             :         itsMTCleaner.computeprincipalsolution();
     408             :         for(uInt tix=0; tix<itsNTerms; tix++)
     409             :           {
     410             :             Matrix<Float> tempRes;
     411             :             itsMTCleaner.getresidual(tix,tempRes);
     412             :             (itsImages->residual(tix))->put( tempRes );
     413             :           }
     414             : 
     415             :         // Restore all terms
     416             :         ImageInfo ii = itsImages->image(0)->imageInfo();
     417             :         ii.setRestoringBeam( beam );
     418             : 
     419             :         for(uInt tix=0; tix<itsNTerms; tix++)
     420             :           {
     421             :             (itsImages->image(tix))->set(0.0);
     422             :             (itsImages->image(tix))->copyData( LatticeExpr<Float>(*(itsImages->model(tix))) );
     423             :             StokesImageUtil::Convolve( *(itsImages->image(tix)) , beam);
     424             :             (itsImages->image(tix))->copyData( LatticeExpr<Float>
     425             :                                                ( *(itsImages->model(tix)) + *(itsImages->residual(tix)) )   );
     426             :             itsImages->image()->setImageInfo(ii);
     427             :           }
     428             : 
     429             :         // Calculate alpha and beta
     430             :         LatticeExprNode leMaxRes = max( *( itsImages->residual(0) ) );
     431             :         Float maxres = leMaxRes.getFloat();
     432             :         Float specthreshold = maxres/5.0;  //////////// do something better here.....
     433             : 
     434             :       os << "Calculating spectral parameters for  Intensity > peakresidual/5 = " << specthreshold << " Jy/beam" << LogIO::POST;
     435             :       LatticeExpr<Float> mask1(iif(((*(itsImages->image(0))))>(specthreshold),1.0,0.0));
     436             :       LatticeExpr<Float> mask0(iif(((*(itsImages->image(0))))>(specthreshold),0.0,1.0));
     437             : 
     438             :       /////// Calculate alpha
     439             :       LatticeExpr<Float> alphacalc( (((*(itsImages->image(1))))*mask1)/(((*(itsImages->image(0))))+(mask0)) );
     440             :       itsImages->alpha()->copyData(alphacalc);
     441             : 
     442             :       // Set the restoring beam for alpha
     443             :       itsImages->alpha()->setImageInfo(ii);
     444             :       //      itsImages->alpha()->table().unmarkForDelete();
     445             : 
     446             :       // Make a mask for the alpha image
     447             :       LatticeExpr<Bool> lemask(iif(((*(itsImages->image(0))) > specthreshold) , true, false));
     448             : 
     449             :       createMask(lemask, *(itsImages->alpha()));
     450             : 
     451             :       }
     452             :     catch(AipsError &x)
     453             :       {
     454             :         throw( AipsError("Restoration Error : " + x.getMesg() ) );
     455             :       }
     456             : 
     457             :   }
     458             : 
     459             : 
     460             : Bool SDAlgorithmMSMFS::createMask(LatticeExpr<Bool> &lemask, ImageInterface<Float> &outimage)
     461             : {
     462             :       ImageRegion outreg = outimage.makeMask("mask0",false,true);
     463             :       LCRegion& outmask=outreg.asMask();
     464             :       outmask.copyData(lemask);
     465             :       outimage.defineRegion("mask0",outreg, RegionHandler::Masks, true);
     466             :       outimage.setDefaultMask("mask0");
     467             :       return true;
     468             : }
     469             : 
     470             : */
     471             : 
     472             : } //# NAMESPACE CASA - END
     473             : 

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