[299] | 1 | // ----------------------------------------------------------------------- |
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| 2 | // CubicSearch.cc: Searching a 3-dimensional 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 <iostream> |
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| 29 | #include <iomanip> |
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| 30 | #include <fstream> |
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| 31 | #include <vector> |
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[393] | 32 | #include <duchamp/param.hh> |
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| 33 | #include <duchamp/PixelMap/Object3D.hh> |
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| 34 | #include <duchamp/Cubes/cubes.hh> |
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| 35 | #include <duchamp/Utils/utils.hh> |
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| 36 | #include <duchamp/Utils/feedback.hh> |
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| 37 | #include <duchamp/Utils/Statistics.hh> |
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[3] | 38 | |
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[232] | 39 | using std::vector; |
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[258] | 40 | using namespace PixelInfo; |
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[274] | 41 | using namespace Statistics; |
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[232] | 42 | |
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[378] | 43 | namespace duchamp |
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| 44 | { |
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| 45 | |
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[103] | 46 | void Cube::CubicSearch() |
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[3] | 47 | { |
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| 48 | /** |
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| 49 | * A front end to the cubic searching routine that does not |
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| 50 | * involve any wavelet reconstruction. |
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[220] | 51 | * The statistics of the cube are calculated first of all. |
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[153] | 52 | * If baseline-removal is required that is done prior to searching. |
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[3] | 53 | * Once searching is complete, the detection map is updated and |
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| 54 | * the intermediate detections are logged in the log file. |
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| 55 | */ |
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| 56 | |
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[219] | 57 | if(this->par.isVerbose()) std::cout << " "; |
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[258] | 58 | |
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[189] | 59 | this->setCubeStats(); |
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| 60 | |
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[258] | 61 | if(this->par.isVerbose()) std::cout << " Searching... " << std::flush; |
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| 62 | |
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[263] | 63 | // this->objectList = search3DArray(this->axisDim,this->array, |
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| 64 | // this->par,this->Stats); |
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[291] | 65 | *this->objectList = search3DArraySimple(this->axisDim,this->array, |
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[263] | 66 | this->par,this->Stats); |
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[189] | 67 | |
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[258] | 68 | if(this->par.isVerbose()) std::cout << " Updating detection map... " |
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| 69 | << std::flush; |
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[3] | 70 | this->updateDetectMap(); |
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[258] | 71 | if(this->par.isVerbose()) std::cout << "Done.\n"; |
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[3] | 72 | |
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[258] | 73 | if(this->par.getFlagLog()){ |
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| 74 | if(this->par.isVerbose()) |
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| 75 | std::cout << " Logging intermediate detections... " << std::flush; |
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| 76 | this->logDetectionList(); |
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| 77 | if(this->par.isVerbose()) std::cout << "Done.\n"; |
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| 78 | } |
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| 79 | |
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[3] | 80 | } |
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[263] | 81 | //--------------------------------------------------------------- |
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[3] | 82 | |
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| 83 | |
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[275] | 84 | std::vector <Detection> search3DArray(long *dim, float *Array, Param &par, |
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| 85 | StatsContainer<float> &stats) |
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[3] | 86 | { |
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| 87 | /** |
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| 88 | * Takes a dimension array and data array as input (and Parameter set) |
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| 89 | * and searches for detections in a combination of 1D and 2D searches. |
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| 90 | * Returns a vector list of Detections. |
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| 91 | * No reconstruction is assumed to have taken place, so statistics are |
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| 92 | * calculated (using robust methods) from the data array itself. |
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[222] | 93 | * \param dim Array of dimension sizes for the data array. |
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| 94 | * \param Array Array of data. |
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[232] | 95 | * \param par Param set defining how to do detection, and what a |
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| 96 | * BLANK pixel is etc. |
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[222] | 97 | * \param stats The statistics that define what a detection is. |
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| 98 | * \return Vector of detected objects. |
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[3] | 99 | */ |
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| 100 | |
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[275] | 101 | std::vector <Detection> outputList; |
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[103] | 102 | long zdim = dim[2]; |
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| 103 | long xySize = dim[0] * dim[1]; |
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[3] | 104 | int num = 0; |
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| 105 | |
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[187] | 106 | ProgressBar bar; |
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[3] | 107 | // FIRST SEARCH -- IN EACH SPECTRUM. |
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| 108 | if(zdim>1){ |
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[175] | 109 | if(par.isVerbose()) { |
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| 110 | std::cout << " 1D: "; |
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[187] | 111 | bar.init(xySize); |
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[175] | 112 | } |
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[3] | 113 | |
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[258] | 114 | bool *doPixel = new bool[xySize]; |
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[3] | 115 | for(int npix=0; npix<xySize; npix++){ |
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[258] | 116 | doPixel[npix] = false; |
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| 117 | for(int z=0;z<zdim;z++){ |
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| 118 | doPixel[npix] = doPixel[npix] || |
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| 119 | (!par.isBlank(Array[npix]) && !par.isInMW(z)); |
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| 120 | } |
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| 121 | // doPixel[i] is false only when there are no good pixels in spectrum |
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| 122 | // of pixel #i. |
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| 123 | } |
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[86] | 124 | |
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[258] | 125 | long *specdim = new long[2]; |
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| 126 | specdim[0] = zdim; specdim[1]=1; |
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| 127 | Image *spectrum = new Image(specdim); |
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| 128 | delete [] specdim; |
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| 129 | spectrum->saveParam(par); |
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| 130 | spectrum->saveStats(stats); |
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| 131 | spectrum->setMinSize(par.getMinChannels()); |
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| 132 | spectrum->pars().setBeamSize(2.); |
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| 133 | // beam size: for spectrum, only neighbouring channels correlated |
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[3] | 134 | |
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[258] | 135 | for(int y=0; y<dim[1]; y++){ |
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| 136 | for(int x=0; x<dim[0]; x++){ |
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[103] | 137 | |
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[258] | 138 | int npix = y*dim[0] + x; |
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| 139 | if( par.isVerbose() ) bar.update(npix+1); |
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| 140 | |
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| 141 | if(doPixel[npix]){ |
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| 142 | spectrum->extractSpectrum(Array,dim,npix); |
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| 143 | spectrum->removeMW(); // only works if flagMW is true |
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| 144 | std::vector<Scan> objlist = spectrum->spectrumDetect(); |
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| 145 | num += objlist.size(); |
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| 146 | for(int obj=0;obj<objlist.size();obj++){ |
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| 147 | Detection newObject; |
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[103] | 148 | // Fix up coordinates of each pixel to match original array |
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[258] | 149 | for(int z=objlist[obj].getX();z<=objlist[obj].getXmax();z++) { |
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| 150 | newObject.pixels().addPixel(x,y,z); |
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| 151 | } |
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| 152 | newObject.setOffsets(par); |
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| 153 | mergeIntoList(newObject,outputList,par); |
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[103] | 154 | } |
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[3] | 155 | } |
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| 156 | } |
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[103] | 157 | } |
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[3] | 158 | |
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[258] | 159 | delete spectrum; |
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| 160 | delete [] doPixel; |
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| 161 | |
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[175] | 162 | if(par.isVerbose()) { |
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[219] | 163 | bar.fillSpace("Found "); |
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| 164 | std::cout << num <<";" << std::flush; |
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[175] | 165 | } |
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[3] | 166 | |
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| 167 | } |
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| 168 | |
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| 169 | // SECOND SEARCH -- IN EACH CHANNEL |
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[175] | 170 | if(par.isVerbose()){ |
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| 171 | std::cout << " 2D: "; |
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[187] | 172 | bar.init(zdim); |
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[175] | 173 | } |
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| 174 | |
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[146] | 175 | num = 0; |
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[3] | 176 | |
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[258] | 177 | long *imdim = new long[2]; |
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| 178 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 179 | Image *channelImage = new Image(imdim); |
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| 180 | delete [] imdim; |
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| 181 | channelImage->saveParam(par); |
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| 182 | channelImage->saveStats(stats); |
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[263] | 183 | // channelImage->setMinSize(par.getMinPix()); |
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| 184 | channelImage->setMinSize(1); |
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[258] | 185 | |
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[3] | 186 | for(int z=0; z<zdim; z++){ |
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| 187 | |
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[187] | 188 | if( par.isVerbose() ) bar.update(z+1); |
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[3] | 189 | |
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[103] | 190 | if(!par.isInMW(z)){ |
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[3] | 191 | |
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[53] | 192 | channelImage->extractImage(Array,dim,z); |
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[258] | 193 | std::vector<Object2D> objlist = channelImage->lutz_detect(); |
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| 194 | num += objlist.size(); |
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| 195 | for(int obj=0;obj<objlist.size();obj++){ |
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| 196 | Detection newObject; |
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| 197 | newObject.pixels().addChannel(z,objlist[obj]); |
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| 198 | newObject.setOffsets(par); |
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| 199 | mergeIntoList(newObject,outputList,par); |
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[3] | 200 | } |
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| 201 | } |
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| 202 | |
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| 203 | } |
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| 204 | |
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[258] | 205 | delete channelImage; |
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| 206 | |
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[175] | 207 | if(par.isVerbose()){ |
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[219] | 208 | bar.fillSpace("Found "); |
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| 209 | std::cout << num << ".\n"; |
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[175] | 210 | } |
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[3] | 211 | |
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| 212 | return outputList; |
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| 213 | } |
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[263] | 214 | //--------------------------------------------------------------- |
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[258] | 215 | |
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[275] | 216 | std::vector <Detection> search3DArraySimple(long *dim, float *Array, |
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| 217 | Param &par, |
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| 218 | StatsContainer<float> &stats) |
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[263] | 219 | { |
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| 220 | /** |
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| 221 | * Takes a dimension array and data array as input (and Parameter |
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| 222 | * set) and searches for detections just in the channel maps -- no |
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[387] | 223 | * 1D searches are done. |
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| 224 | * Returns a vector list of Detections. |
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| 225 | * No reconstruction is assumed to have taken place, so only the base |
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| 226 | * data array is searched. |
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[263] | 227 | * \param dim Array of dimension sizes for the data array. |
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| 228 | * \param Array Array of data. |
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| 229 | * \param par Param set defining how to do detection, and what a |
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| 230 | * BLANK pixel is etc. |
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| 231 | * \param stats The statistics that define what a detection is. |
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[387] | 232 | * \return A std::vector of detected objects. |
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[263] | 233 | */ |
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[258] | 234 | |
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[275] | 235 | std::vector <Detection> outputList; |
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[263] | 236 | long zdim = dim[2]; |
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| 237 | int num = 0; |
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| 238 | |
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| 239 | ProgressBar bar; |
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[377] | 240 | bool useBar = (zdim>1); |
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| 241 | if(useBar && par.isVerbose()) bar.init(zdim); |
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[263] | 242 | |
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| 243 | num = 0; |
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| 244 | |
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| 245 | long *imdim = new long[2]; |
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| 246 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 247 | Image *channelImage = new Image(imdim); |
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| 248 | delete [] imdim; |
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| 249 | channelImage->saveParam(par); |
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| 250 | channelImage->saveStats(stats); |
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| 251 | channelImage->setMinSize(1); |
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| 252 | |
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| 253 | for(int z=0; z<zdim; z++){ |
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| 254 | |
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[377] | 255 | if( par.isVerbose() && useBar ) bar.update(z+1); |
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[263] | 256 | |
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| 257 | if(!par.isInMW(z)){ |
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| 258 | |
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| 259 | channelImage->extractImage(Array,dim,z); |
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| 260 | std::vector<Object2D> objlist = channelImage->lutz_detect(); |
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| 261 | num += objlist.size(); |
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| 262 | for(int obj=0;obj<objlist.size();obj++){ |
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| 263 | Detection newObject; |
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| 264 | newObject.pixels().addChannel(z,objlist[obj]); |
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| 265 | newObject.setOffsets(par); |
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| 266 | mergeIntoList(newObject,outputList,par); |
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| 267 | } |
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| 268 | } |
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| 269 | |
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| 270 | } |
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| 271 | |
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| 272 | delete channelImage; |
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| 273 | |
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| 274 | if(par.isVerbose()){ |
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[377] | 275 | if(useBar) bar.remove(); |
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| 276 | std::cout << "Found " << num << ".\n"; |
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[263] | 277 | } |
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| 278 | |
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| 279 | return outputList; |
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| 280 | } |
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| 281 | |
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| 282 | |
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[378] | 283 | } |
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