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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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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45 | void Cube::ReconSearch1D() |
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46 | { |
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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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57 | |
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58 | // Reconstruct the cube by 1d atrous transform in each spatial pixel |
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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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79 | } |
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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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83 | } |
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84 | |
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85 | this->objectList = searchReconArray(this->axisDim,this->array,this->recon,this->par); |
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86 | |
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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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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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104 | |
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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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131 | } |
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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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136 | } |
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137 | |
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138 | this->objectList = searchReconArray(this->axisDim,this->array,this->recon,this->par); |
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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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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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155 | if(this->axisDim[2]==1) this->ReconSearch2D(); |
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156 | else { |
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157 | |
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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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166 | this->objectList = searchReconArray(this->axisDim,this->array,this->recon,this->par); |
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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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177 | vector <Detection> searchReconArray(long *dim, float *originalArray, float *reconArray, Param &par) |
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178 | { |
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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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193 | vector <Detection> outputList; |
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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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197 | int num=0, goodSize; |
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198 | |
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199 | float blankPixValue = par.getBlankPixVal(); |
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200 | bool *isGood = new bool[fullSize]; |
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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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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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216 | if(par.isVerbose()) std::cout << "1D: | |" << std::flush; |
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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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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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271 | } |
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272 | delete spectrum; |
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273 | } |
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274 | } |
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275 | |
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276 | num = outputList.size(); |
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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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279 | |
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280 | } |
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281 | |
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282 | // Second search -- in each channel |
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283 | if(par.isVerbose()) std::cout << "2D: | |" << std::flush; |
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284 | |
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285 | for(int z=0; z<zdim; z++){ // loop over all channels |
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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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289 | for(int i=0;i<(100*(z+1)/zdim)/5;i++) std::cout << "#"; |
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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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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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308 | |
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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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315 | channelImage->extractImage(reconArray,dim,z); |
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316 | channelImage->setStats(imageMedian,imageSigma,par.getCut()); |
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317 | if(par.getFlagFDR()) channelImage->setupFDR(); |
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318 | channelImage->setMinSize(par.getMinPix()); |
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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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334 | delete channelImage; |
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335 | } |
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336 | |
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337 | } |
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338 | |
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339 | |
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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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344 | delete [] doChannel; |
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345 | |
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346 | return outputList; |
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347 | } |
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