[299] | 1 | // ----------------------------------------------------------------------- |
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| 2 | // cubicSearchNMerge.cc: Combining both the searching and the merging |
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| 3 | // functions. |
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| 4 | // ----------------------------------------------------------------------- |
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| 5 | // Copyright (C) 2006, Matthew Whiting, ATNF |
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| 6 | // |
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| 7 | // This program is free software; you can redistribute it and/or modify it |
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| 8 | // under the terms of the GNU General Public License as published by the |
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| 9 | // Free Software Foundation; either version 2 of the License, or (at your |
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| 10 | // option) any later version. |
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| 11 | // |
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| 12 | // Duchamp is distributed in the hope that it will be useful, but WITHOUT |
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| 13 | // ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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| 14 | // FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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| 15 | // for more details. |
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| 16 | // |
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| 17 | // You should have received a copy of the GNU General Public License |
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| 18 | // along with Duchamp; if not, write to the Free Software Foundation, |
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| 19 | // Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA |
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| 20 | // |
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| 21 | // Correspondence concerning Duchamp may be directed to: |
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| 22 | // Internet email: Matthew.Whiting [at] atnf.csiro.au |
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| 23 | // Postal address: Dr. Matthew Whiting |
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| 24 | // Australia Telescope National Facility, CSIRO |
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| 25 | // PO Box 76 |
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| 26 | // Epping NSW 1710 |
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| 27 | // AUSTRALIA |
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| 28 | // ----------------------------------------------------------------------- |
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[3] | 29 | #include <iostream> |
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| 30 | #include <iomanip> |
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| 31 | #include <fstream> |
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| 32 | #include <vector> |
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[393] | 33 | #include <duchamp/Cubes/cubes.hh> |
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| 34 | #include <duchamp/Utils/utils.hh> |
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[3] | 35 | using std::endl; |
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| 36 | using std::setw; |
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| 37 | |
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| 38 | vector <Detection> cubicSearchNMerge(long *dim, float *Array, Param &par) |
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| 39 | { |
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[528] | 40 | /// @details |
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| 41 | /// Takes a dimension array and data array as input (and Parameter set) |
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| 42 | /// and searches for detections in a combination of 1D and 2D searches. |
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| 43 | /// Returns a vector list of Detections. |
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| 44 | /// No reconstruction is assumed to have taken place, so statistics are |
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| 45 | /// calculated (using robust methods) from the data array itself. |
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[3] | 46 | |
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| 47 | vector <Detection> outputList; |
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| 48 | int zdim = dim[2]; |
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[921] | 49 | size_t xySize = dim[0] * dim[1]; |
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| 50 | size_t fullSize = zdim * xySize; |
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[3] | 51 | int num=0; |
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| 52 | |
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| 53 | // bool flagBlank=par.getFlagBlankPix(); |
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| 54 | float blankPixValue = par.getBlankPixVal(); |
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| 55 | bool *isGood = new bool[fullSize]; |
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[921] | 56 | for(size_t pos=0;pos<fullSize;pos++) |
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[3] | 57 | isGood[pos] = !par.isBlank(Array[pos]); |
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| 58 | // isGood[pos] = (!flagBlank) || (Array[pos]!=blankPixValue); |
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| 59 | |
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| 60 | float dud; |
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| 61 | |
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| 62 | // FIRST SEARCH -- IN EACH SPECTRUM. |
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| 63 | // FIRST, GET STATS |
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| 64 | if(zdim>1){ |
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| 65 | if(par.isVerbose()) std::cout << " 1D: | |" << std::flush; |
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| 66 | // if(par.isVerbose()) std::cout << "Done 0%" << "\b\b\b\b\b\b\b\b" << std::flush; |
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| 67 | float *specMedian = new float[xySize]; |
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| 68 | float *specSigma = new float[xySize]; |
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| 69 | |
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| 70 | for(int npix=0; npix<xySize; npix++){ |
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| 71 | float *spec = new float[zdim]; |
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| 72 | int goodSize=0; |
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| 73 | for(int z=0;z<zdim;z++) if(isGood[z*xySize+npix]) spec[goodSize++] = Array[z*xySize+npix]; |
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| 74 | if(goodSize>0) findMedianStats(spec,goodSize,specMedian[npix],dud); |
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| 75 | else specMedian[npix] = blankPixValue; |
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| 76 | // if(goodSize>0) findNormalStats(spec,goodSize,dud,specSigma[npix]); |
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| 77 | if(goodSize>0){ |
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| 78 | findMedianStats(spec,goodSize,dud,specSigma[npix]); |
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| 79 | specSigma[npix] /= correctionFactor; |
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| 80 | } |
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| 81 | else specSigma[npix] = 1.; |
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| 82 | delete spec; |
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| 83 | } |
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| 84 | // NEXT, DO SOURCE FINDING |
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| 85 | int numSearches = xySize + zdim; |
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| 86 | for(int npix=0; npix<xySize; npix++){ |
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| 87 | |
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| 88 | // if(par.isVerbose() && ((1000*npix/xySize)%10==0) ) |
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| 89 | // std::cout << "Done " << setw(2) << 100*npix/xySize << "%\b\b\b\b\b\b\b\b" << std::flush; |
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| 90 | if( par.isVerbose() && ((100*(npix+1)/xySize)%5 == 0) ){ |
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| 91 | std::cout << "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b|"; |
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| 92 | for(int i=0;i<(100*(npix+1)/xySize)/5;i++) std::cout << "#"; |
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| 93 | for(int i=(100*(npix+1)/xySize)/5;i<20;i++) std::cout << " "; |
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| 94 | std::cout << "|" << std::flush; |
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| 95 | } |
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| 96 | |
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| 97 | float *spec = new float[zdim]; |
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| 98 | for(int z=0;z<zdim;z++) spec[z] = Array[z*xySize + npix]; |
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| 99 | long *specdim = new long[2]; |
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| 100 | specdim[0] = zdim; specdim[1]=1; |
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| 101 | Image *spectrum = new Image(specdim); |
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| 102 | spectrum->saveParam(par); |
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| 103 | spectrum->pars().setBeamSize(2.); // for spectrum, only neighbouring channels correlated |
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| 104 | spectrum->saveArray(spec,zdim); |
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| 105 | spectrum->setStats(specMedian[npix],specSigma[npix],par.getCut()); |
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| 106 | if(par.getFlagFDR()) spectrum->setupFDR(); |
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[582] | 107 | spectrum->findSources2D(); |
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[3] | 108 | for(int obj=0;obj<spectrum->getNumObj();obj++){ |
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| 109 | Detection *object = new Detection; |
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| 110 | *object = spectrum->getObject(obj); |
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| 111 | // if(par.getFlagGrowth()) growObject(*object,*spectrum); |
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| 112 | for(int pix=0;pix<object->getSize();pix++) { |
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| 113 | // Fix up coordinates of each pixel to match original array |
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| 114 | object->setZ(pix, object->getX(pix)); |
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| 115 | object->setX(pix, npix%dim[0]); |
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| 116 | object->setY(pix, npix/dim[0]); |
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| 117 | } |
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| 118 | object->addOffsets(par); |
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| 119 | object->calcParams(); |
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| 120 | // outputList.push_back(*object); |
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| 121 | mergeIntoList(*object,outputList,par); |
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| 122 | delete object; |
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| 123 | } |
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| 124 | delete spectrum; |
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| 125 | delete spec; |
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| 126 | delete specdim; |
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| 127 | } |
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| 128 | |
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| 129 | delete [] specMedian; |
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| 130 | delete [] specSigma; |
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| 131 | |
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| 132 | num = outputList.size(); |
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| 133 | if(par.isVerbose()) |
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| 134 | std::cout <<"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\bFound " << num <<";" << std::flush; |
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| 135 | |
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| 136 | } |
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| 137 | |
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| 138 | // SECOND SEARCH -- IN EACH CHANNEL |
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| 139 | // FIRST, GET STATS |
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| 140 | if(par.isVerbose()) std::cout << " 2D: | |" << std::flush; |
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| 141 | // if(par.isVerbose()) std::cout << "Done 0%" << "\b\b\b\b\b\b\b\b" << std::flush; |
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| 142 | float *imageMedian = new float[zdim]; |
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| 143 | float *imageSigma = new float[zdim]; |
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| 144 | for(int z=0; z<zdim; z++){ |
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| 145 | float *image = new float[xySize]; |
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| 146 | int goodSize=0; |
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| 147 | for(int npix=0; npix<xySize; npix++) |
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| 148 | if(isGood[z*xySize + npix]) image[goodSize++] = Array[z*xySize + npix]; |
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| 149 | if(goodSize>0) findMedianStats(image,goodSize,imageMedian[z],dud); |
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| 150 | else imageMedian[z] = blankPixValue; |
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| 151 | if(goodSize>0) findNormalStats(image,goodSize,dud,imageSigma[z]); |
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| 152 | else imageSigma[z] = 1.; |
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| 153 | delete image; |
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| 154 | } |
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| 155 | // NEXT, DO SOURCE FINDING |
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| 156 | bool *doChannel = new bool[zdim]; |
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| 157 | for(int z=0;z<zdim;z++) |
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| 158 | doChannel[z] = !( par.getFlagMW() && (z>=par.getMinMW()) && (z<=par.getMaxMW()) ); |
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| 159 | |
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| 160 | for(int z=0; z<zdim; z++){ |
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| 161 | |
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| 162 | // if(par.isVerbose() && ((1000*z/zdim)%10==0) ) |
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| 163 | // std::cout << "Done " << setw(2) << 100*z/zdim << "%\b\b\b\b\b\b\b\b" << std::flush; |
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| 164 | if( par.isVerbose() && ((100*(z+1)/zdim)%5 == 0) ){ |
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| 165 | std::cout << "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b|"; |
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| 166 | for(int i=0;i<(100*(z+1)/zdim)/5;i++) std::cout << "#"; |
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| 167 | for(int i=(100*(z+1)/zdim)/5;i<20;i++) std::cout << " "; |
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| 168 | std::cout << "|" << std::flush; |
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| 169 | } |
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| 170 | |
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| 171 | if( doChannel[z] ){ |
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| 172 | |
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| 173 | float *image = new float[xySize]; |
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| 174 | for(int npix=0; npix<xySize; npix++) image[npix] = Array[z*xySize + npix]; |
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| 175 | long *imdim = new long[2]; |
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| 176 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 177 | Image *channelImage = new Image(imdim); |
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| 178 | channelImage->saveParam(par); |
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| 179 | channelImage->saveArray(image,xySize); |
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| 180 | channelImage->setStats(imageMedian[z],imageSigma[z],par.getCut()); |
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| 181 | if(par.getFlagFDR()) channelImage->setupFDR(); |
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[582] | 182 | channelImage->findSources2D(); |
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[3] | 183 | for(int obj=0;obj<channelImage->getNumObj();obj++){ |
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| 184 | Detection *object = new Detection; |
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| 185 | *object = channelImage->getObject(obj); |
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| 186 | // if(par.getFlagGrowth()) growObject(*object,*channelImage); |
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| 187 | // Fix up coordinates of each pixel to match original array |
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| 188 | for(int pix=0;pix<object->getSize();pix++) object->setZ(pix, z); |
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| 189 | object->addOffsets(par); |
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| 190 | object->calcParams(); |
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| 191 | mergeIntoList(*object,outputList,par); |
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| 192 | // outputList.push_back(*object); |
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| 193 | delete object; |
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| 194 | } |
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| 195 | delete image; |
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| 196 | delete channelImage; |
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| 197 | delete imdim; |
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| 198 | } |
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| 199 | |
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| 200 | } |
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| 201 | |
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| 202 | if(par.isVerbose()) |
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| 203 | std::cout << "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\bFound " << outputList.size() - num |
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| 204 | << ". " << std::endl << std::flush; |
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| 205 | |
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| 206 | delete [] imageMedian; |
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| 207 | delete [] imageSigma; |
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| 208 | delete [] isGood; |
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| 209 | delete [] doChannel; |
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| 210 | |
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| 211 | return outputList; |
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| 212 | } |
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| 213 | |
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