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Current view: top level - synthesis/MeasurementEquations - ConvolutionEquation.cc (source / functions) Hit Total Coverage
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Date: 2024-10-10 19:51:30 Functions: 0 15 0.0 %

          Line data    Source code
       1             : //# ConvolutionEquation.cc:  this defines ConvolutionEquation
       2             : //# Copyright (C) 1996,1997,1998,1999,2000,2003
       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 <synthesis/MeasurementEquations/ConvolutionEquation.h>
      29             : #include <casacore/casa/Arrays/ArrayMath.h>
      30             : #include <casacore/casa/BasicMath/Math.h>
      31             : #include <casacore/casa/Arrays/Vector.h>
      32             : 
      33             : using namespace casacore;
      34             : namespace casa { //# NAMESPACE CASA - BEGIN
      35             : 
      36           0 : ConvolutionEquation::ConvolutionEquation(){
      37           0 : };
      38             : 
      39           0 : ConvolutionEquation::ConvolutionEquation(const Array<Float> & psf, 
      40           0 :                                          const Array<Float> & dirtyImage){
      41           0 :   theConv.setPsf(psf, dirtyImage.shape());
      42           0 :   theConv.setFastConvolve();
      43           0 :   theRealPsfSize = psf.shape();
      44           0 :   theMeas.resize(dirtyImage.shape());
      45           0 :   theMeas = dirtyImage;
      46           0 : };
      47             : 
      48           0 : ConvolutionEquation::ConvolutionEquation(const Array<Float>& psf, 
      49           0 :                                          const MaskedArray<Float>& dirtyImage){
      50           0 :   theConv.setPsf(psf, dirtyImage.shape());
      51           0 :   theConv.setFastConvolve();
      52           0 :   theRealPsfSize = psf.shape();
      53           0 :   theMeas.resize(dirtyImage.shape());
      54           0 :   theMeas = dirtyImage.getArray();
      55           0 : };
      56             : 
      57           0 : ConvolutionEquation::~ConvolutionEquation(){
      58           0 : };
      59             : 
      60           0 : Bool ConvolutionEquation::evaluate(Array<Float> & result, 
      61             :                                    const LinearModel<Array<Float> > & model){
      62           0 :   const Array<Float> modelArray = model.getModel();
      63           0 :   theConv.linearConv(result, modelArray, false); 
      64           0 :   return true;
      65           0 : };
      66             : 
      67           0 : Bool ConvolutionEquation::evaluate(Array<Float> & result, 
      68             :                                    const LinearModel< MaskedArray<Float> > & model) {
      69           0 :   const MaskedArray<Float> modelArray = model.getModel();
      70           0 :   theConv.linearConv(result, modelArray.getArray(), false); 
      71           0 :   return true;
      72           0 : }
      73             : 
      74           0 : Bool ConvolutionEquation::evaluate(Array<Float> & result, 
      75             :                                    const IPosition & position, 
      76             :                                    const Float amplitude,
      77             :                                    const IPosition & modelSize){
      78           0 :   if (thePsf.nelements() == 0){
      79           0 :     thePsf = theConv.getPsf(false);
      80           0 :     thePsfOrigin = thePsf.shape()/2;
      81             :   }
      82           0 :   IPosition psfSize = thePsf.shape();
      83           0 :   IPosition blc = thePsfOrigin - position;
      84           0 :   IPosition trc = blc + modelSize - 1;
      85             :   // Check if the required bounds are outside the psf. If they are then
      86             :   // resize the psf (with zero padding) to encompass the requested
      87             :   // convolution.  Another way to do this is to just return the required
      88             :   // portion of the psf (of size modelSize) suitably padded. This will be
      89             :   // quicker and more memory efficient for just one evaluation, but if the
      90             :   // user is cleaning near the edges of their image, then it will have to be
      91             :   // done for each iteration that is near the edge. By resizing the whole
      92             :   // psf when necessary it will after a few resizes be at the required size
      93             :   // for all the iterations.
      94           0 :   if ((min(blc.asVector()) < 0) || 
      95           0 :       (max((trc-psfSize).asVector()) >= 0))
      96             :     {
      97           0 :       IPosition newSize(thePsf.ndim(), 0);
      98           0 :       IPosition newtrc(thePsf.ndim(), 0);
      99           0 :       IPosition newblc(thePsf.ndim(), 0);
     100           0 :       for(uInt i = 0; i < thePsf.ndim(); i++){
     101           0 :         newblc(i) = -std::min(blc(i), (ssize_t)0);
     102           0 :         newSize(i) = std::max(trc(i)+1, psfSize(i)) + newblc(i);
     103           0 :         newtrc(i) = newblc(i) + psfSize(i) - 1;
     104             :       }
     105             :       {
     106           0 :         Array<Float> newPsf(newSize);
     107           0 :         newPsf = 0;
     108           0 :         newPsf(newblc,newtrc) = thePsf;
     109           0 :         thePsf.reference(newPsf);
     110           0 :       }
     111           0 :       thePsfOrigin = thePsfOrigin + newblc;
     112           0 :       result = thePsf(blc+newblc, trc+newblc);
     113           0 :       if (!nearAbs(Double(amplitude),Double(1.0)))
     114           0 :         result = thePsf(blc+newblc, trc+newblc)*amplitude;
     115           0 :       return true;
     116           0 :     }
     117             :   else {
     118           0 :     result = thePsf(blc, trc);
     119           0 :     if (!nearAbs(Double(amplitude),1.0))
     120           0 :       result = result * amplitude;
     121           0 :     return true;
     122             :   }
     123           0 : };
     124             : 
     125           0 : Bool ConvolutionEquation::
     126             : residual(Array<Float> & result, 
     127             :          Float & chisq,
     128             :          const LinearModel< Array<Float> > & model) {
     129           0 :   if (residual(result, model)) {
     130           0 :     chisq = sum(result*result);
     131           0 :     return true;
     132             :   }
     133             :   else
     134           0 :     return false;
     135             : }
     136             : 
     137             : 
     138           0 : Bool ConvolutionEquation::
     139             : residual(Array<Float> & result, 
     140             :          Float & chisq,
     141             :          Array<Float> & mask,
     142             :          const LinearModel< Array<Float> > & model) {
     143           0 :   if (residual(result, model)) {
     144           0 :     result = result * mask;
     145           0 :     chisq = sum(result*result);
     146           0 :     return true;
     147             :   }
     148             :   else
     149           0 :     return false;
     150             : }
     151             : 
     152             : 
     153           0 : Bool ConvolutionEquation::
     154             : residual(Array<Float> & result, 
     155             :          const LinearModel< Array<Float> > & model) {
     156           0 :   if (evaluate(result, model)) {
     157           0 :     result = theMeas - result;
     158           0 :     return true;
     159             :   }
     160             :   else
     161           0 :     return false;
     162             : }
     163             : 
     164             : 
     165             : 
     166             : 
     167           0 : Bool ConvolutionEquation::residual(Array<Float> & result, 
     168             :                                    const LinearModel< MaskedArray<Float> > & model) {
     169           0 :   if (evaluate(result, model)) {
     170           0 :     result = theMeas - result;
     171           0 :     return true;
     172             :   }
     173             :   else
     174           0 :     return false;
     175             : }
     176             : 
     177           0 : Bool ConvolutionEquation::residual(MaskedArray<Float> & result, 
     178             :                                    const LinearModel< MaskedArray<Float> > & model) {
     179           0 :   Array<Float> farray;
     180           0 :   if (residual(farray, model)) {
     181           0 :     result.setData(farray, model.getModel().getMask());
     182           0 :     return true;
     183             :   }
     184             :   else
     185           0 :     return false;
     186           0 : }
     187             : 
     188           0 : IPosition ConvolutionEquation::psfSize(){
     189           0 :   return theRealPsfSize;
     190             : }
     191             : 
     192           0 : void ConvolutionEquation::flushPsf(){
     193           0 :   thePsf.resize(IPosition(0));
     194           0 : }
     195             : 
     196             : } //# NAMESPACE CASA - END
     197             : 

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