[3] | 1 | #include <fstream> |
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| 2 | #include <iostream> |
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| 3 | #include <iomanip> |
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| 4 | #include <vector> |
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| 5 | #include <Cubes/cubes.hh> |
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| 6 | #include <ATrous/atrous.hh> |
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| 7 | #include <Utils/utils.hh> |
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| 8 | |
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| 9 | using std::setw; |
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| 10 | |
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| 11 | ////////////////////////////////////////////////////////////////////////////////////// |
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[96] | 12 | void Cube::ReconSearch() |
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| 13 | { |
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| 14 | /** |
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| 15 | * Cube::ReconSearch() |
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| 16 | * A front-end to the various ReconSearch functions, the choice of which |
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| 17 | * is determined by the use of the reconDim parameter. |
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| 18 | */ |
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| 19 | int dim = this->par.getReconDim(); |
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| 20 | switch(dim) |
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| 21 | { |
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| 22 | case 1: this->ReconSearch1D(); break; |
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| 23 | case 2: this->ReconSearch2D(); break; |
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| 24 | case 3: this->ReconSearch3D(); break; |
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| 25 | default: |
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| 26 | if(dim<=0){ |
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| 27 | std::cerr << " WARNING <ReconSearch> : reconDim (" << dim |
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| 28 | << ") is less than 1. Performing 1-D reconstruction.\n"; |
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| 29 | this->par.setReconDim(1); |
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| 30 | this->ReconSearch1D(); |
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| 31 | } |
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| 32 | else if(dim>3){ |
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| 33 | std::cerr << " WARNING <ReconSearch> : reconDim (" << dim |
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| 34 | << ") is more than 3. Performing 3-D reconstruction.\n"; |
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| 35 | this->par.setReconDim(3); |
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| 36 | this->ReconSearch3D(); |
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| 37 | } |
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| 38 | break; |
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| 39 | } |
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| 40 | |
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| 41 | } |
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| 42 | |
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| 43 | |
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| 44 | ////////////////////////////////////////////////////////////////////////////////////// |
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[3] | 45 | void Cube::ReconSearch1D() |
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| 46 | { |
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[96] | 47 | /** |
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| 48 | * Cube::ReconSearch1D() |
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| 49 | * This reconstructs a cube by performing a 1D a trous reconstruction |
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| 50 | * in the spectrum of each spatial pixel. |
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| 51 | * It then searches the cube using searchReconArray (below). |
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| 52 | * |
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| 53 | * The resulting object list is stored in the Cube. |
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| 54 | */ |
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| 55 | long xySize = this->axisDim[0] * this->axisDim[1]; |
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| 56 | long zdim = this->axisDim[2]; |
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[3] | 57 | |
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| 58 | // Reconstruct the cube by 1d atrous transform in each spatial pixel |
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[100] | 59 | if(!this->reconExists){ |
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| 60 | std::cout<<" Reconstructing... "; |
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| 61 | if(par.isVerbose()) std::cout << "| |" << std::flush; |
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| 62 | for(int npix=0; npix<xySize; npix++){ |
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| 63 | if( par.isVerbose() && ((100*(npix+1)/xySize)%5 == 0) ){ |
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| 64 | 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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| 65 | for(int i=0;i<(100*(npix+1)/xySize)/5;i++) std::cout << "#"; |
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| 66 | for(int i=(100*(npix+1)/xySize)/5;i<20;i++) std::cout << " "; |
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| 67 | std::cout << "|" << std::flush; |
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| 68 | } |
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| 69 | float *spec = new float[zdim]; |
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| 70 | float *newSpec = new float[zdim]; |
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| 71 | for(int z=0;z<zdim;z++) spec[z] = this->array[z*xySize + npix]; |
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| 72 | bool verboseFlag = this->par.isVerbose(); |
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| 73 | this->par.setVerbosity(false); |
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| 74 | atrous1DReconstruct(this->axisDim[2],spec,newSpec,this->par); |
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| 75 | this->par.setVerbosity(verboseFlag); |
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| 76 | for(int z=0;z<zdim;z++) this->recon[z*xySize+npix] = newSpec[z]; |
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| 77 | delete spec; |
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| 78 | delete newSpec; |
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[96] | 79 | } |
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[100] | 80 | this->reconExists = true; |
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| 81 | std::cout<<"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b All Done. \n" |
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| 82 | <<" Searching... "<<std::flush; |
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[3] | 83 | } |
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| 84 | |
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[96] | 85 | this->objectList = searchReconArray(this->axisDim,this->array,this->recon,this->par); |
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[100] | 86 | |
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[3] | 87 | this->updateDetectMap(); |
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| 88 | if(this->par.getFlagLog()) this->logDetectionList(); |
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| 89 | |
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| 90 | } |
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| 91 | |
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| 92 | ////////////////////////////////////////////////////////////////////////////////////// |
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| 93 | void Cube::ReconSearch2D() |
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| 94 | { |
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[96] | 95 | /** |
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| 96 | * Cube::ReconSearch2D() |
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| 97 | * This reconstructs a cube by performing a 2D a trous reconstruction |
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| 98 | * in each spatial image (ie. each channel map) of the cube. |
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| 99 | * It then searches the cube using searchReconArray (below). |
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| 100 | * |
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| 101 | * The resulting object list is stored in the Cube. |
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| 102 | */ |
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| 103 | long xySize = this->axisDim[0] * this->axisDim[1]; |
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[3] | 104 | |
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[100] | 105 | if(!this->reconExists){ |
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| 106 | // RECONSTRUCT THE CUBE BY 2D ATROUS TRANSFORM IN EACH CHANNEL |
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| 107 | std::cout<<" Reconstructing... "; |
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| 108 | if(par.isVerbose()) std::cout << "| |" << std::flush; |
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| 109 | for(int z=0;z<this->axisDim[2];z++){ |
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| 110 | if( par.isVerbose() && ((100*(z+1)/this->axisDim[2])%5 == 0) ){ |
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| 111 | 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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| 112 | for(int i=0;i<(100*(z+1)/this->axisDim[2])/5;i++) std::cout << "#"; |
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| 113 | for(int i=(100*(z+1)/this->axisDim[2])/5;i<20;i++) std::cout << " "; |
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| 114 | std::cout << "|" << std::flush; |
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| 115 | } |
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| 116 | if(!this->par.isInMW(z)){ |
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| 117 | float *im = new float[xySize]; |
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| 118 | float *newIm = new float[xySize]; |
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| 119 | for(int npix=0; npix<xySize; npix++) im[npix] = this->array[z*xySize+npix]; |
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| 120 | bool verboseFlag = this->par.isVerbose(); |
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| 121 | this->par.setVerbosity(false); |
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| 122 | atrous2DReconstruct(this->axisDim[0],this->axisDim[1],im,newIm,this->par); |
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| 123 | this->par.setVerbosity(verboseFlag); |
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| 124 | for(int npix=0; npix<xySize; npix++) this->recon[z*xySize+npix] = newIm[npix]; |
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| 125 | delete im; |
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| 126 | delete newIm; |
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| 127 | } |
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| 128 | else { |
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| 129 | for(int i=z*xySize; i<(z+1)*xySize; i++) this->recon[i] = this->array[i]; |
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| 130 | } |
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[96] | 131 | } |
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[100] | 132 | this->reconExists = true; |
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| 133 | std::cout<<"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b All Done. \n" |
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| 134 | <<"Searching... "<<std::flush; |
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| 135 | |
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[3] | 136 | } |
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| 137 | |
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[96] | 138 | this->objectList = searchReconArray(this->axisDim,this->array,this->recon,this->par); |
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[3] | 139 | |
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| 140 | this->updateDetectMap(); |
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| 141 | if(this->par.getFlagLog()) this->logDetectionList(); |
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| 142 | |
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| 143 | } |
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| 144 | |
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| 145 | ////////////////////////////////////////////////////////////////////////////////////// |
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| 146 | void Cube::ReconSearch3D() |
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| 147 | { |
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[96] | 148 | /** |
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| 149 | * Cube::ReconSearch3D() |
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| 150 | * This performs a full 3D a trous reconstruction of the cube |
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| 151 | * It then searches the cube using searchReconArray (below). |
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| 152 | * |
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| 153 | * The resulting object list is stored in the Cube. |
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| 154 | */ |
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[3] | 155 | if(this->axisDim[2]==1) this->ReconSearch2D(); |
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| 156 | else { |
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| 157 | |
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[71] | 158 | if(!this->reconExists){ |
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| 159 | std::cout<<" Reconstructing... "<<std::flush; |
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| 160 | atrous3DReconstruct(this->axisDim[0],this->axisDim[1],this->axisDim[2], |
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| 161 | this->array,this->recon,this->par); |
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| 162 | this->reconExists = true; |
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| 163 | std::cout<<"All Done. \n Searching... "<<std::flush; |
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| 164 | } |
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| 165 | |
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[96] | 166 | this->objectList = searchReconArray(this->axisDim,this->array,this->recon,this->par); |
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[3] | 167 | |
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| 168 | this->updateDetectMap(); |
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| 169 | if(this->par.getFlagLog()) this->logDetectionList(); |
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| 170 | |
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| 171 | } |
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| 172 | |
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| 173 | } |
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| 174 | |
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| 175 | |
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| 176 | ////////////////////////////////////////////////////////////////////////////////////// |
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[96] | 177 | vector <Detection> searchReconArray(long *dim, float *originalArray, float *reconArray, Param &par) |
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[3] | 178 | { |
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[96] | 179 | /** |
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| 180 | * searchReconArray(long *dim, float *originalArray, float *reconArray, Param &par) |
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| 181 | * This searches for objects in a cube that has been reconstructed. |
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| 182 | * |
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| 183 | * Inputs: - dimension array |
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| 184 | * - original, un-reconstructed image array |
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| 185 | * - reconstructed image array |
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| 186 | * - parameters |
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| 187 | * |
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| 188 | * Searches first in each spatial pixel (1D search), |
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| 189 | * then in each channel image (2D search). |
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| 190 | * |
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| 191 | * Returns: vector of Detections resulting from the search. |
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| 192 | */ |
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[3] | 193 | vector <Detection> outputList; |
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[96] | 194 | long zdim = dim[2]; |
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| 195 | long xySize = dim[0] * dim[1]; |
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| 196 | long fullSize = zdim * xySize; |
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[86] | 197 | int num=0, goodSize; |
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[3] | 198 | |
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| 199 | float blankPixValue = par.getBlankPixVal(); |
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| 200 | bool *isGood = new bool[fullSize]; |
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[96] | 201 | for(int pos=0;pos<fullSize;pos++){ |
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| 202 | isGood[pos] = !par.isBlank(originalArray[pos]) && !par.isInMW(pos/xySize); |
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| 203 | } |
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| 204 | bool *doChannel = new bool[xySize]; |
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| 205 | goodSize=0; |
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| 206 | for(int npix=0; npix<xySize; npix++){ |
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| 207 | for(int z=0;z<zdim;z++) if(isGood[z*xySize+npix]) goodSize++; |
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| 208 | if(goodSize==0) doChannel[npix] = false; |
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| 209 | else doChannel[npix] = true; |
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| 210 | } |
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[3] | 211 | |
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| 212 | float dud; |
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| 213 | |
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| 214 | // First search -- in each spectrum. |
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| 215 | if(zdim > 1){ |
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[71] | 216 | if(par.isVerbose()) std::cout << "1D: | |" << std::flush; |
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[3] | 217 | |
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| 218 | for(int npix=0; npix<xySize; npix++){ |
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| 219 | |
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| 220 | if( par.isVerbose() && ((100*(npix+1)/xySize)%5 == 0) ){ |
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| 221 | 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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| 222 | for(int i=0;i<(100*(npix+1)/xySize)/5;i++) std::cout << "#"; |
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| 223 | for(int i=(100*(npix+1)/xySize)/5;i<20;i++) std::cout << " "; |
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| 224 | std::cout << "|" << std::flush; |
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| 225 | } |
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| 226 | |
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[96] | 227 | if(doChannel[npix]){ |
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| 228 | |
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| 229 | // First, get stats |
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| 230 | float *spec = new float[zdim]; |
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| 231 | float specMedian,specSigma; |
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| 232 | goodSize=0; |
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| 233 | for(int z=0;z<zdim;z++) |
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| 234 | if(isGood[z*xySize+npix]) spec[goodSize++] = originalArray[z*xySize+npix]; |
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| 235 | specMedian = findMedian(spec,goodSize); |
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| 236 | goodSize=0; |
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| 237 | for(int z=0;z<zdim;z++) |
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| 238 | if(isGood[z*xySize+npix]) |
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| 239 | spec[goodSize++] = originalArray[z*xySize+npix]-reconArray[z*xySize+npix]; |
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| 240 | specSigma = findMADFM(spec,goodSize) / correctionFactor; |
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| 241 | delete [] spec; |
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| 242 | |
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| 243 | // Next, do source finding. |
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| 244 | long *specdim = new long[2]; |
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| 245 | specdim[0] = zdim; specdim[1]=1; |
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| 246 | Image *spectrum = new Image(specdim); |
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| 247 | delete [] specdim; |
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| 248 | spectrum->saveParam(par); |
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| 249 | spectrum->pars().setBeamSize(2.); // for spectrum, only neighbouring channels correlated |
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| 250 | spectrum->extractSpectrum(reconArray,dim,npix); |
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| 251 | spectrum->removeMW(); // only works if flagMW is true |
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| 252 | spectrum->setStats(specMedian,specSigma,par.getCut()); |
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| 253 | if(par.getFlagFDR()) spectrum->setupFDR(); |
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| 254 | spectrum->setMinSize(par.getMinChannels()); |
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| 255 | spectrum->spectrumDetect(); |
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| 256 | for(int obj=0;obj<spectrum->getNumObj();obj++){ |
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| 257 | Detection *object = new Detection; |
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| 258 | *object = spectrum->getObject(obj); |
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| 259 | for(int pix=0;pix<object->getSize();pix++) { |
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| 260 | // Fix up coordinates of each pixel to match original array |
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| 261 | object->setZ(pix, object->getX(pix)); |
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| 262 | object->setX(pix, npix%dim[0]); |
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| 263 | object->setY(pix, npix/dim[0]); |
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| 264 | object->setF(pix, originalArray[object->getX(pix)+object->getY(pix)*dim[0]+object->getZ(pix)*xySize]); |
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| 265 | // NB: set F to the original value, not the recon value. |
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| 266 | } |
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| 267 | object->addOffsets(par); |
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| 268 | object->calcParams(); |
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| 269 | mergeIntoList(*object,outputList,par); |
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| 270 | delete object; |
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[3] | 271 | } |
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[96] | 272 | delete spectrum; |
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[3] | 273 | } |
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| 274 | } |
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| 275 | |
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| 276 | num = outputList.size(); |
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[96] | 277 | if(par.isVerbose()) |
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| 278 | 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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[3] | 279 | |
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[86] | 280 | } |
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[3] | 281 | |
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| 282 | // Second search -- in each channel |
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[71] | 283 | if(par.isVerbose()) std::cout << "2D: | |" << std::flush; |
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| 284 | |
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[86] | 285 | for(int z=0; z<zdim; z++){ // loop over all channels |
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[3] | 286 | |
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| 287 | if( par.isVerbose() && ((100*(z+1)/zdim)%5 == 0) ){ |
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| 288 | 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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[86] | 289 | for(int i=0;i<(100*(z+1)/zdim)/5;i++) std::cout << "#"; |
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[3] | 290 | for(int i=(100*(z+1)/zdim)/5;i<20;i++) std::cout << " "; |
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| 291 | std::cout << "|" << std::flush; |
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| 292 | } |
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| 293 | |
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[96] | 294 | if(!par.isInMW(z)){ // purpose of this is to ignore the Milky Way channels if we are flagging them |
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| 295 | // First, get stats |
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| 296 | float *image = new float[xySize]; |
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| 297 | float imageMedian,imageSigma; |
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| 298 | goodSize=0; |
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| 299 | for(int npix=0; npix<xySize; npix++) |
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| 300 | if(isGood[z*xySize + npix]) image[goodSize++] = originalArray[z*xySize + npix]; |
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| 301 | imageMedian = findMedian(image,goodSize); |
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| 302 | goodSize=0; |
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| 303 | for(int npix=0; npix<xySize; npix++) |
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| 304 | if(isGood[z*xySize+npix]) |
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| 305 | image[goodSize++]=originalArray[z*xySize+npix]-reconArray[z*xySize+npix]; |
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| 306 | imageSigma = findMADFM(image,goodSize) / correctionFactor; |
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| 307 | delete [] image; |
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[86] | 308 | |
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[96] | 309 | // Next, do source finding. |
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| 310 | long *imdim = new long[2]; |
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| 311 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 312 | Image *channelImage = new Image(imdim); |
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| 313 | channelImage->saveParam(par); |
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| 314 | delete [] imdim; |
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[53] | 315 | channelImage->extractImage(reconArray,dim,z); |
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[96] | 316 | channelImage->setStats(imageMedian,imageSigma,par.getCut()); |
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[3] | 317 | if(par.getFlagFDR()) channelImage->setupFDR(); |
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[13] | 318 | channelImage->setMinSize(par.getMinPix()); |
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[3] | 319 | channelImage->lutz_detect(); |
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| 320 | for(int obj=0;obj<channelImage->getNumObj();obj++){ |
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| 321 | Detection *object = new Detection; |
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| 322 | *object = channelImage->getObject(obj); |
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| 323 | // Fix up z coordinates of each pixel to match original array (x & y are fine) |
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| 324 | for(int pix=0;pix<object->getSize();pix++){ |
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| 325 | object->setZ(pix, z); |
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| 326 | object->setF(pix, originalArray[object->getX(pix)+object->getY(pix)*dim[0]+z*xySize]); |
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| 327 | // NB: set F to the original value, not the recon value. |
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| 328 | } |
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| 329 | object->addOffsets(par); |
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| 330 | object->calcParams(); |
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| 331 | mergeIntoList(*object,outputList,par); |
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| 332 | delete object; |
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| 333 | } |
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[96] | 334 | delete channelImage; |
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| 335 | } |
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[86] | 336 | |
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[3] | 337 | } |
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| 338 | |
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[86] | 339 | |
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[3] | 340 | 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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| 341 | << ". " << std::endl << std::flush; |
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| 342 | |
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| 343 | delete [] isGood; |
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[96] | 344 | delete [] doChannel; |
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[3] | 345 | |
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| 346 | return outputList; |
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| 347 | } |
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