[3] | 1 | #include <iostream> |
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| 2 | #include <iomanip> |
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| 3 | #include <fstream> |
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| 4 | #include <vector> |
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[189] | 5 | #include <param.hh> |
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[3] | 6 | #include <Cubes/cubes.hh> |
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| 7 | #include <Utils/utils.hh> |
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[213] | 8 | #include <Utils/feedback.hh> |
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[192] | 9 | #include <Utils/Statistics.hh> |
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[3] | 10 | |
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[103] | 11 | void Cube::CubicSearch() |
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[3] | 12 | { |
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| 13 | /** |
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| 14 | * A front end to the cubic searching routine that does not |
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| 15 | * involve any wavelet reconstruction. |
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[220] | 16 | * The statistics of the cube are calculated first of all. |
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[153] | 17 | * If baseline-removal is required that is done prior to searching. |
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[3] | 18 | * Once searching is complete, the detection map is updated and |
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| 19 | * the intermediate detections are logged in the log file. |
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| 20 | */ |
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| 21 | |
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[219] | 22 | if(this->par.isVerbose()) std::cout << " "; |
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[189] | 23 | this->setCubeStats(); |
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| 24 | |
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[190] | 25 | this->objectList = search3DArray(this->axisDim,this->array, |
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| 26 | this->par,this->Stats); |
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[189] | 27 | |
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[3] | 28 | this->updateDetectMap(); |
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| 29 | if(this->par.getFlagLog()) this->logDetectionList(); |
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| 30 | |
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| 31 | } |
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| 32 | |
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| 33 | |
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[190] | 34 | vector <Detection> search3DArray(long *dim, float *Array, Param &par, |
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| 35 | StatsContainer<float> &stats) |
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[3] | 36 | { |
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| 37 | /** |
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| 38 | * cubicSearch |
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| 39 | * Takes a dimension array and data array as input (and Parameter set) |
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| 40 | * and searches for detections in a combination of 1D and 2D searches. |
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| 41 | * Returns a vector list of Detections. |
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| 42 | * No reconstruction is assumed to have taken place, so statistics are |
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| 43 | * calculated (using robust methods) from the data array itself. |
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| 44 | */ |
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| 45 | |
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| 46 | vector <Detection> outputList; |
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[103] | 47 | long zdim = dim[2]; |
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| 48 | long xySize = dim[0] * dim[1]; |
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[3] | 49 | int num = 0; |
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| 50 | |
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[189] | 51 | bool *doPixel = new bool[xySize]; |
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[103] | 52 | int goodSize=0; |
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| 53 | for(int npix=0; npix<xySize; npix++){ |
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[189] | 54 | doPixel[npix] = false; |
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| 55 | for(int z=0;z<zdim;z++){ |
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| 56 | doPixel[npix] = doPixel[npix] || |
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| 57 | (!par.isBlank(Array[npix]) && !par.isInMW(z)); |
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| 58 | } |
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| 59 | // doPixel[i] is false only when there are no good pixels in spectrum |
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| 60 | // of pixel #i. |
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[103] | 61 | } |
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[187] | 62 | |
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| 63 | ProgressBar bar; |
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[3] | 64 | // FIRST SEARCH -- IN EACH SPECTRUM. |
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| 65 | if(zdim>1){ |
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[175] | 66 | if(par.isVerbose()) { |
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| 67 | std::cout << " 1D: "; |
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[187] | 68 | bar.init(xySize); |
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[175] | 69 | } |
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[3] | 70 | |
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| 71 | for(int npix=0; npix<xySize; npix++){ |
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[86] | 72 | |
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[187] | 73 | if( par.isVerbose() ) bar.update(npix+1); |
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[3] | 74 | |
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[189] | 75 | if(doPixel[npix]){ |
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[103] | 76 | |
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| 77 | long *specdim = new long[2]; |
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| 78 | specdim[0] = zdim; specdim[1]=1; |
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| 79 | Image *spectrum = new Image(specdim); |
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[187] | 80 | delete [] specdim; |
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[103] | 81 | spectrum->saveParam(par); |
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[190] | 82 | spectrum->saveStats(stats); |
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[146] | 83 | spectrum->pars().setBeamSize(2.); |
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| 84 | // beam size: for spectrum, only neighbouring channels correlated |
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[103] | 85 | spectrum->extractSpectrum(Array,dim,npix); |
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| 86 | spectrum->removeMW(); // only works if flagMW is true |
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| 87 | spectrum->setMinSize(par.getMinChannels()); |
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| 88 | spectrum->spectrumDetect(); |
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[146] | 89 | num += spectrum->getNumObj(); |
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[103] | 90 | for(int obj=0;obj<spectrum->getNumObj();obj++){ |
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| 91 | Detection *object = new Detection; |
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| 92 | *object = spectrum->getObject(obj); |
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| 93 | for(int pix=0;pix<object->getSize();pix++) { |
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| 94 | // Fix up coordinates of each pixel to match original array |
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| 95 | object->setZ(pix, object->getX(pix)); |
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| 96 | object->setX(pix, npix%dim[0]); |
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| 97 | object->setY(pix, npix/dim[0]); |
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| 98 | } |
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[221] | 99 | object->setOffsets(par); |
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[103] | 100 | object->calcParams(); |
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| 101 | mergeIntoList(*object,outputList,par); |
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| 102 | delete object; |
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[3] | 103 | } |
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[103] | 104 | delete spectrum; |
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[3] | 105 | } |
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[103] | 106 | } |
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[3] | 107 | |
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[146] | 108 | // num = outputList.size(); |
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[175] | 109 | if(par.isVerbose()) { |
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[219] | 110 | bar.fillSpace("Found "); |
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| 111 | std::cout << num <<";" << std::flush; |
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[175] | 112 | } |
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[3] | 113 | |
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| 114 | } |
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| 115 | |
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| 116 | // SECOND SEARCH -- IN EACH CHANNEL |
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[175] | 117 | if(par.isVerbose()){ |
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| 118 | std::cout << " 2D: "; |
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[187] | 119 | bar.init(zdim); |
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[175] | 120 | } |
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| 121 | |
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[146] | 122 | num = 0; |
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[3] | 123 | |
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| 124 | for(int z=0; z<zdim; z++){ |
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| 125 | |
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[187] | 126 | if( par.isVerbose() ) bar.update(z+1); |
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[3] | 127 | |
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[103] | 128 | if(!par.isInMW(z)){ |
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[3] | 129 | |
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| 130 | long *imdim = new long[2]; |
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| 131 | imdim[0] = dim[0]; imdim[1] = dim[1]; |
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| 132 | Image *channelImage = new Image(imdim); |
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[187] | 133 | delete [] imdim; |
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[3] | 134 | channelImage->saveParam(par); |
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[190] | 135 | channelImage->saveStats(stats); |
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[53] | 136 | channelImage->extractImage(Array,dim,z); |
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[13] | 137 | channelImage->setMinSize(par.getMinPix()); |
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[3] | 138 | channelImage->lutz_detect(); |
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[146] | 139 | num += channelImage->getNumObj(); |
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[3] | 140 | for(int obj=0;obj<channelImage->getNumObj();obj++){ |
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| 141 | Detection *object = new Detection; |
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| 142 | *object = channelImage->getObject(obj); |
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| 143 | // Fix up coordinates of each pixel to match original array |
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| 144 | for(int pix=0;pix<object->getSize();pix++) object->setZ(pix, z); |
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[221] | 145 | object->setOffsets(par); |
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[3] | 146 | object->calcParams(); |
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| 147 | mergeIntoList(*object,outputList,par); |
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| 148 | delete object; |
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| 149 | } |
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| 150 | delete channelImage; |
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| 151 | } |
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| 152 | |
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| 153 | } |
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| 154 | |
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[175] | 155 | if(par.isVerbose()){ |
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[219] | 156 | bar.fillSpace("Found "); |
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| 157 | std::cout << num << ".\n"; |
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[175] | 158 | } |
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[3] | 159 | |
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[189] | 160 | delete [] doPixel; |
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[86] | 161 | |
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[3] | 162 | return outputList; |
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| 163 | } |
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