[299] | 1 | // ----------------------------------------------------------------------- |
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| 2 | // ReconSearch.cc: Searching a wavelet-reconstructed cube. |
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| 3 | // ----------------------------------------------------------------------- |
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| 4 | // Copyright (C) 2006, Matthew Whiting, ATNF |
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| 5 | // |
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| 6 | // This program is free software; you can redistribute it and/or modify it |
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| 7 | // under the terms of the GNU General Public License as published by the |
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| 8 | // Free Software Foundation; either version 2 of the License, or (at your |
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| 9 | // option) any later version. |
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| 10 | // |
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| 11 | // Duchamp is distributed in the hope that it will be useful, but WITHOUT |
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| 12 | // ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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| 13 | // FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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| 14 | // for more details. |
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| 15 | // |
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| 16 | // You should have received a copy of the GNU General Public License |
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| 17 | // along with Duchamp; if not, write to the Free Software Foundation, |
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| 18 | // Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA |
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| 19 | // |
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| 20 | // Correspondence concerning Duchamp may be directed to: |
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| 21 | // Internet email: Matthew.Whiting [at] atnf.csiro.au |
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| 22 | // Postal address: Dr. Matthew Whiting |
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| 23 | // Australia Telescope National Facility, CSIRO |
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| 24 | // PO Box 76 |
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| 25 | // Epping NSW 1710 |
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| 26 | // AUSTRALIA |
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| 27 | // ----------------------------------------------------------------------- |
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[3] | 28 | #include <fstream> |
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| 29 | #include <iostream> |
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| 30 | #include <iomanip> |
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| 31 | #include <vector> |
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[120] | 32 | #include <duchamp.hh> |
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[258] | 33 | #include <PixelMap/Object3D.hh> |
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[3] | 34 | #include <Cubes/cubes.hh> |
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[144] | 35 | #include <Detection/detection.hh> |
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[3] | 36 | #include <ATrous/atrous.hh> |
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| 37 | #include <Utils/utils.hh> |
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[213] | 38 | #include <Utils/feedback.hh> |
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[192] | 39 | #include <Utils/Statistics.hh> |
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[3] | 40 | |
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[258] | 41 | using namespace PixelInfo; |
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[274] | 42 | using namespace Statistics; |
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[258] | 43 | |
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[103] | 44 | void Cube::ReconSearch() |
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| 45 | { |
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| 46 | /** |
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[220] | 47 | * The Cube is first reconstructed, using Cube::ReconCube(). |
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| 48 | * The statistics of the cube are calculated next. |
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| 49 | * It is then searched, using searchReconArray. |
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| 50 | * The resulting object list is stored in the Cube, and outputted |
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| 51 | * to the log file if the user so requests. |
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[103] | 52 | */ |
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[285] | 53 | |
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| 54 | if(!this->par.getFlagATrous()){ |
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| 55 | duchampWarning("ReconSearch", |
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| 56 | "You've requested a reconSearch, but not allocated space for the reconstructed array.\nDoing the basic CubicSearch.\n"); |
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| 57 | this->CubicSearch(); |
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| 58 | } |
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| 59 | else { |
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[188] | 60 | |
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[285] | 61 | this->ReconCube(); |
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[188] | 62 | |
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[285] | 63 | if(this->par.isVerbose()) std::cout << " "; |
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[219] | 64 | |
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[285] | 65 | this->setCubeStats(); |
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[189] | 66 | |
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[285] | 67 | if(this->par.isVerbose()) std::cout << " Searching... " << std::flush; |
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[188] | 68 | |
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[291] | 69 | *this->objectList = searchReconArraySimple(this->axisDim,this->array, |
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| 70 | this->recon, |
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| 71 | this->par,this->Stats); |
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[285] | 72 | // this->objectList = searchReconArray(this->axisDim,this->array, |
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| 73 | // this->recon,this->par,this->Stats); |
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[188] | 74 | |
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[285] | 75 | if(this->par.isVerbose()) std::cout << " Updating detection map... " |
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| 76 | << std::flush; |
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| 77 | this->updateDetectMap(); |
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| 78 | if(this->par.isVerbose()) std::cout << "Done.\n"; |
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[188] | 79 | |
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[285] | 80 | if(this->par.getFlagLog()){ |
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| 81 | if(this->par.isVerbose()) |
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| 82 | std::cout << " Logging intermediate detections... " << std::flush; |
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| 83 | this->logDetectionList(); |
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| 84 | if(this->par.isVerbose()) std::cout << "Done.\n"; |
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| 85 | } |
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| 86 | |
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[258] | 87 | } |
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[188] | 88 | } |
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| 89 | |
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| 90 | ///////////////////////////////////////////////////////////////////////////// |
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| 91 | void Cube::ReconCube() |
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| 92 | { |
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| 93 | /** |
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[220] | 94 | * A front-end to the various reconstruction functions, the choice of |
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| 95 | * which is determined by the use of the reconDim parameter. |
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| 96 | * Differs from ReconSearch only in that no searching is done. |
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[188] | 97 | */ |
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[120] | 98 | int dimRecon = this->par.getReconDim(); |
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[146] | 99 | // Test whether we have eg. an image, but have requested a 3-d |
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| 100 | // reconstruction. |
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| 101 | // If dimension of data array is less than dimRecon, change dimRecon |
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| 102 | // to the dimension of the array. |
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[285] | 103 | int numGoodDim = this->head.getNumAxes(); |
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| 104 | if(numGoodDim<dimRecon){ |
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| 105 | dimRecon = numGoodDim; |
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| 106 | this->par.setReconDim(dimRecon); |
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| 107 | std::stringstream errmsg; |
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| 108 | errmsg << "You requested a " << dimRecon << "-dimensional reconstruction," |
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| 109 | << " but the FITS file is only " << numGoodDim << "-dimensional.\n" |
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| 110 | << "Changing reconDim to " << numGoodDim << ".\n"; |
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[293] | 111 | duchampWarning("Reconstruction",errmsg.str()); |
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[285] | 112 | } |
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[120] | 113 | |
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| 114 | switch(dimRecon) |
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[103] | 115 | { |
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[188] | 116 | case 1: this->ReconCube1D(); break; |
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| 117 | case 2: this->ReconCube2D(); break; |
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| 118 | case 3: this->ReconCube3D(); break; |
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[103] | 119 | default: |
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[120] | 120 | if(dimRecon<=0){ |
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| 121 | std::stringstream errmsg; |
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| 122 | errmsg << "reconDim (" << dimRecon |
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| 123 | << ") is less than 1. Performing 1-D reconstruction.\n"; |
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[293] | 124 | duchampWarning("Reconstruction", errmsg.str()); |
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[103] | 125 | this->par.setReconDim(1); |
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[188] | 126 | this->ReconCube1D(); |
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[103] | 127 | } |
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[120] | 128 | else if(dimRecon>3){ |
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| 129 | //this probably won't happen with new code above, but just in case... |
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| 130 | std::stringstream errmsg; |
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| 131 | errmsg << "reconDim (" << dimRecon |
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| 132 | << ") is more than 3. Performing 3-D reconstruction.\n"; |
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[293] | 133 | duchampWarning("Reconstruction", errmsg.str()); |
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[103] | 134 | this->par.setReconDim(3); |
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[188] | 135 | this->ReconCube3D(); |
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[103] | 136 | } |
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| 137 | break; |
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| 138 | } |
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| 139 | } |
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| 140 | |
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[146] | 141 | ///////////////////////////////////////////////////////////////////////////// |
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[188] | 142 | void Cube::ReconCube1D() |
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[3] | 143 | { |
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[103] | 144 | /** |
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[220] | 145 | * This reconstructs a cube by performing a 1D a trous reconstruction |
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| 146 | * in the spectrum of each spatial pixel. |
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[103] | 147 | */ |
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| 148 | long xySize = this->axisDim[0] * this->axisDim[1]; |
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[188] | 149 | |
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[103] | 150 | long zdim = this->axisDim[2]; |
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[3] | 151 | |
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[187] | 152 | ProgressBar bar; |
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[103] | 153 | if(!this->reconExists){ |
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| 154 | std::cout<<" Reconstructing... "; |
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[187] | 155 | if(par.isVerbose()) bar.init(xySize); |
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[103] | 156 | for(int npix=0; npix<xySize; npix++){ |
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[175] | 157 | |
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[187] | 158 | if( par.isVerbose() ) bar.update(npix+1); |
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[175] | 159 | |
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[103] | 160 | float *spec = new float[zdim]; |
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| 161 | float *newSpec = new float[zdim]; |
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| 162 | for(int z=0;z<zdim;z++) spec[z] = this->array[z*xySize + npix]; |
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| 163 | bool verboseFlag = this->par.isVerbose(); |
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| 164 | this->par.setVerbosity(false); |
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| 165 | atrous1DReconstruct(this->axisDim[2],spec,newSpec,this->par); |
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| 166 | this->par.setVerbosity(verboseFlag); |
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| 167 | for(int z=0;z<zdim;z++) this->recon[z*xySize+npix] = newSpec[z]; |
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[205] | 168 | delete [] spec; |
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| 169 | delete [] newSpec; |
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[3] | 170 | } |
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[103] | 171 | this->reconExists = true; |
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[214] | 172 | bar.fillSpace(" All Done."); |
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[175] | 173 | printSpace(22); |
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[188] | 174 | std::cout << "\n"; |
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[3] | 175 | } |
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[103] | 176 | |
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[3] | 177 | } |
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| 178 | |
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[146] | 179 | ///////////////////////////////////////////////////////////////////////////// |
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[188] | 180 | void Cube::ReconCube2D() |
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[3] | 181 | { |
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[103] | 182 | /** |
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[220] | 183 | * This reconstructs a cube by performing a 2D a trous reconstruction |
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| 184 | * in each spatial image (ie. each channel map) of the cube. |
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[103] | 185 | */ |
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| 186 | long xySize = this->axisDim[0] * this->axisDim[1]; |
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[187] | 187 | ProgressBar bar; |
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[377] | 188 | bool useBar = (this->axisDim[2]>1); |
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[3] | 189 | |
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[103] | 190 | if(!this->reconExists){ |
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| 191 | std::cout<<" Reconstructing... "; |
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[377] | 192 | if(useBar&&par.isVerbose()) bar.init(this->axisDim[2]); |
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[103] | 193 | for(int z=0;z<this->axisDim[2];z++){ |
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[175] | 194 | |
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[377] | 195 | if( par.isVerbose() && useBar ) bar.update((z+1)); |
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[175] | 196 | |
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[103] | 197 | if(!this->par.isInMW(z)){ |
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| 198 | float *im = new float[xySize]; |
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| 199 | float *newIm = new float[xySize]; |
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[146] | 200 | for(int npix=0; npix<xySize; npix++) |
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| 201 | im[npix] = this->array[z*xySize+npix]; |
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[103] | 202 | bool verboseFlag = this->par.isVerbose(); |
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| 203 | this->par.setVerbosity(false); |
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[146] | 204 | atrous2DReconstruct(this->axisDim[0],this->axisDim[1], |
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| 205 | im,newIm,this->par); |
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[103] | 206 | this->par.setVerbosity(verboseFlag); |
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[146] | 207 | for(int npix=0; npix<xySize; npix++) |
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| 208 | this->recon[z*xySize+npix] = newIm[npix]; |
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[205] | 209 | delete [] im; |
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| 210 | delete [] newIm; |
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[3] | 211 | } |
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[103] | 212 | else { |
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[146] | 213 | for(int i=z*xySize; i<(z+1)*xySize; i++) |
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| 214 | this->recon[i] = this->array[i]; |
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[103] | 215 | } |
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[3] | 216 | } |
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[103] | 217 | this->reconExists = true; |
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[377] | 218 | if(useBar) bar.fillSpace(" All Done."); |
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[175] | 219 | printSpace(22); |
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[188] | 220 | std::cout << "\n"; |
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[3] | 221 | } |
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| 222 | } |
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| 223 | |
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[146] | 224 | ///////////////////////////////////////////////////////////////////////////// |
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[188] | 225 | void Cube::ReconCube3D() |
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[3] | 226 | { |
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[103] | 227 | /** |
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[220] | 228 | * This performs a full 3D a trous reconstruction of the cube |
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[103] | 229 | */ |
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[188] | 230 | if(this->axisDim[2]==1) this->ReconCube2D(); |
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[3] | 231 | else { |
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| 232 | |
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[71] | 233 | if(!this->reconExists){ |
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| 234 | std::cout<<" Reconstructing... "<<std::flush; |
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| 235 | atrous3DReconstruct(this->axisDim[0],this->axisDim[1],this->axisDim[2], |
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| 236 | this->array,this->recon,this->par); |
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| 237 | this->reconExists = true; |
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[175] | 238 | std::cout << " All Done."; |
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| 239 | printSpace(22); |
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[188] | 240 | std::cout << "\n"; |
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[71] | 241 | } |
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| 242 | |
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[3] | 243 | } |
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| 244 | } |
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| 245 | |
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[146] | 246 | ///////////////////////////////////////////////////////////////////////////// |
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[232] | 247 | std::vector <Detection> searchReconArray(long *dim, float *originalArray, |
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| 248 | float *reconArray, Param &par, |
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| 249 | StatsContainer<float> &stats) |
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[3] | 250 | { |
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[103] | 251 | /** |
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[220] | 252 | * This searches for objects in a cube that has been reconstructed. |
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[103] | 253 | * |
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[220] | 254 | * The search is conducted first in each spatial pixel (xdim*ydim 1D |
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| 255 | * searches), then in each channel image (zdim 2D searches). |
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| 256 | * The searches are done on the reconstructed array, although the detected |
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| 257 | * objects have fluxes drawn from the corresponding pixels of the original |
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| 258 | * array. |
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[103] | 259 | * |
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[220] | 260 | * \param dim Array of dimension sizes |
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| 261 | * \param originalArray Original, un-reconstructed image array. |
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| 262 | * \param reconArray Reconstructed image array |
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| 263 | * \param par The Param set. |
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| 264 | * \param stats The StatsContainer that defines what a detection is. |
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[103] | 265 | * |
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[220] | 266 | * \return A vector of Detections resulting from the search. |
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[103] | 267 | */ |
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[232] | 268 | std::vector <Detection> outputList; |
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[103] | 269 | long zdim = dim[2]; |
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| 270 | long xySize = dim[0] * dim[1]; |
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[192] | 271 | int num=0; |
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[258] | 272 | ProgressBar bar; |
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[3] | 273 | |
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| 274 | // First search -- in each spectrum. |
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| 275 | if(zdim > 1){ |
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[175] | 276 | if(par.isVerbose()){ |
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| 277 | std::cout << "1D: "; |
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[187] | 278 | bar.init(xySize); |
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[175] | 279 | } |
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[3] | 280 | |
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[258] | 281 | bool *doPixel = new bool[xySize]; |
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| 282 | // doPixel is a bool array to say whether to look in a given spectrum |
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[3] | 283 | for(int npix=0; npix<xySize; npix++){ |
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[258] | 284 | doPixel[npix] = false; |
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| 285 | for(int z=0;z<zdim;z++) { |
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| 286 | doPixel[npix] = doPixel[npix] || |
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| 287 | (!par.isBlank(originalArray[npix]) && !par.isInMW(z)); |
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| 288 | } |
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| 289 | // doPixel[i] is false only when there are no good pixels in spectrum |
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| 290 | // of pixel #i. |
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| 291 | } |
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[3] | 292 | |
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[258] | 293 | long *specdim = new long[2]; |
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| 294 | specdim[0] = zdim; specdim[1]=1; |
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| 295 | Image *spectrum = new Image(specdim); |
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| 296 | delete [] specdim; |
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| 297 | spectrum->saveParam(par); |
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| 298 | spectrum->saveStats(stats); |
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| 299 | spectrum->setMinSize(par.getMinChannels()); |
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| 300 | spectrum->pars().setBeamSize(2.); |
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| 301 | // beam size: for spectrum, only neighbouring channels correlated |
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[3] | 302 | |
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[258] | 303 | for(int y=0; y<dim[1]; y++){ |
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| 304 | for(int x=0; x<dim[0]; x++){ |
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[192] | 305 | |
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[258] | 306 | int npix = y*dim[0] + x; |
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| 307 | if( par.isVerbose() ) bar.update(npix+1); |
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| 308 | |
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| 309 | if(doPixel[npix]){ |
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| 310 | |
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| 311 | spectrum->extractSpectrum(reconArray,dim,npix); |
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| 312 | spectrum->removeMW(); // only works if flagMW is true |
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| 313 | std::vector<Scan> objlist = spectrum->spectrumDetect(); |
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| 314 | num += objlist.size(); |
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| 315 | for(int obj=0;obj<objlist.size();obj++){ |
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| 316 | Detection newObject; |
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[103] | 317 | // Fix up coordinates of each pixel to match original array |
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[258] | 318 | for(int z=objlist[obj].getX();z<=objlist[obj].getXmax();z++) { |
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| 319 | newObject.pixels().addPixel(x,y,z); |
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| 320 | } |
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| 321 | newObject.setOffsets(par); |
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| 322 | mergeIntoList(newObject,outputList,par); |
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[103] | 323 | } |
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[3] | 324 | } |
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[258] | 325 | |
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[3] | 326 | } |
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| 327 | } |
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| 328 | |
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[258] | 329 | delete spectrum; |
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| 330 | delete [] doPixel; |
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| 331 | |
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[175] | 332 | if(par.isVerbose()) { |
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[219] | 333 | bar.fillSpace("Found "); |
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| 334 | std::cout << num <<";" << std::flush; |
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[175] | 335 | } |
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[86] | 336 | } |
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[3] | 337 | |
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| 338 | // Second search -- in each channel |
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[175] | 339 | if(par.isVerbose()){ |
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[219] | 340 | std::cout << " 2D: "; |
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[187] | 341 | bar.init(zdim); |
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[175] | 342 | } |
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[71] | 343 | |
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[146] | 344 | num = 0; |
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| 345 | |
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[258] | 346 | long *imdim = new long[2]; |
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| 347 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 348 | Image *channelImage = new Image(imdim); |
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| 349 | delete [] imdim; |
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| 350 | channelImage->saveParam(par); |
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| 351 | channelImage->saveStats(stats); |
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| 352 | channelImage->setMinSize(par.getMinPix()); |
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| 353 | |
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[86] | 354 | for(int z=0; z<zdim; z++){ // loop over all channels |
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[3] | 355 | |
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[187] | 356 | if( par.isVerbose() ) bar.update(z+1); |
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[3] | 357 | |
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[146] | 358 | if(!par.isInMW(z)){ |
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| 359 | // purpose of this is to ignore the Milky Way channels |
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| 360 | // if we are flagging them |
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| 361 | |
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[53] | 362 | channelImage->extractImage(reconArray,dim,z); |
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[258] | 363 | std::vector<Object2D> objlist = channelImage->lutz_detect(); |
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| 364 | num += objlist.size(); |
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| 365 | for(int obj=0;obj<objlist.size();obj++){ |
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| 366 | Detection newObject; |
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| 367 | newObject.pixels().addChannel(z,objlist[obj]); |
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| 368 | newObject.setOffsets(par); |
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| 369 | mergeIntoList(newObject,outputList,par); |
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[3] | 370 | } |
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[258] | 371 | } |
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| 372 | |
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[3] | 373 | } |
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| 374 | |
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[258] | 375 | delete channelImage; |
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| 376 | |
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[219] | 377 | if(par.isVerbose()){ |
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| 378 | bar.fillSpace("Found "); |
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| 379 | std::cout << num << ".\n"; |
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| 380 | } |
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[86] | 381 | |
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[3] | 382 | |
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| 383 | return outputList; |
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| 384 | } |
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[263] | 385 | |
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| 386 | ///////////////////////////////////////////////////////////////////////////// |
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| 387 | std::vector <Detection> |
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| 388 | searchReconArraySimple(long *dim, float *originalArray, |
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| 389 | float *reconArray, Param &par, |
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| 390 | StatsContainer<float> &stats) |
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| 391 | { |
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| 392 | /** |
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| 393 | * This searches for objects in a cube that has been reconstructed. |
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| 394 | * |
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| 395 | * The search is conducted only in each channel image (zdim 2D |
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| 396 | * searches) -- no searches in 1D are done. |
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| 397 | * |
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| 398 | * The searches are done on the reconstructed array, although the detected |
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| 399 | * objects have fluxes drawn from the corresponding pixels of the original |
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| 400 | * array. |
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| 401 | * |
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| 402 | * \param dim Array of dimension sizes |
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| 403 | * \param originalArray Original, un-reconstructed image array. |
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| 404 | * \param reconArray Reconstructed image array |
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| 405 | * \param par The Param set. |
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| 406 | * \param stats The StatsContainer that defines what a detection is. |
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| 407 | * |
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| 408 | * \return A vector of Detections resulting from the search. |
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| 409 | */ |
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| 410 | std::vector <Detection> outputList; |
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| 411 | long zdim = dim[2]; |
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| 412 | int num=0; |
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| 413 | ProgressBar bar; |
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[377] | 414 | bool useBar = (zdim>1); |
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| 415 | if(useBar&&par.isVerbose()) bar.init(zdim); |
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[263] | 416 | |
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| 417 | long *imdim = new long[2]; |
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| 418 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 419 | Image *channelImage = new Image(imdim); |
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| 420 | delete [] imdim; |
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| 421 | channelImage->saveParam(par); |
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| 422 | channelImage->saveStats(stats); |
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| 423 | channelImage->setMinSize(1); |
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| 424 | |
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| 425 | for(int z=0; z<zdim; z++){ // loop over all channels |
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| 426 | |
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[377] | 427 | if( par.isVerbose() && useBar ) bar.update(z+1); |
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[263] | 428 | |
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| 429 | if(!par.isInMW(z)){ |
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| 430 | // purpose of this is to ignore the Milky Way channels |
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| 431 | // if we are flagging them |
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| 432 | |
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| 433 | channelImage->extractImage(reconArray,dim,z); |
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| 434 | std::vector<Object2D> objlist = channelImage->lutz_detect(); |
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| 435 | num += objlist.size(); |
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| 436 | for(int obj=0;obj<objlist.size();obj++){ |
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| 437 | Detection newObject; |
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| 438 | newObject.pixels().addChannel(z,objlist[obj]); |
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| 439 | newObject.setOffsets(par); |
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| 440 | mergeIntoList(newObject,outputList,par); |
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| 441 | } |
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| 442 | } |
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| 443 | |
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| 444 | } |
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| 445 | |
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| 446 | delete channelImage; |
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| 447 | |
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| 448 | if(par.isVerbose()){ |
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[377] | 449 | if(useBar) bar.remove(); |
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| 450 | std::cout << "Found " << num << ".\n"; |
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[263] | 451 | } |
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| 452 | |
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| 453 | |
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| 454 | return outputList; |
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| 455 | } |
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