[3] | 1 | #include <iostream> |
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| 2 | #include <iomanip> |
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| 3 | #include <vector> |
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| 4 | #include <string> |
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| 5 | #include <wcs.h> |
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| 6 | #include <Cubes/cubes.hh> |
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| 7 | #include <Utils/utils.hh> |
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| 8 | using std::endl; |
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| 9 | |
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| 10 | /****************************************************************/ |
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| 11 | /////////////////////////////////////////////////// |
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| 12 | //// Functions for DataArray class: |
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| 13 | /////////////////////////////////////////////////// |
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| 14 | |
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| 15 | DataArray::DataArray(short int nDim, long size){ |
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| 16 | // need error handling in case size<0 !!! |
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| 17 | if(size>0) this->array = new float[size]; |
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| 18 | this->numPixels = size; |
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| 19 | if(nDim>0) this->axisDim = new long[nDim]; |
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| 20 | this->numDim = nDim; |
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| 21 | } |
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| 22 | |
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| 23 | DataArray::DataArray(short int nDim, long *dimensions){ |
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| 24 | int size = dimensions[0]; |
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| 25 | for(int i=1;i<nDim;i++) size *= dimensions[i]; |
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| 26 | this->numPixels = size; |
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| 27 | if(size>0){ |
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| 28 | this->array = new float[size]; |
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| 29 | } |
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| 30 | this->numDim=nDim; |
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| 31 | if(nDim>0) this->axisDim = new long[nDim]; |
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| 32 | for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i]; |
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| 33 | } |
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| 34 | |
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| 35 | void DataArray::getDimArray(long *output){ |
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| 36 | for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i]; |
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| 37 | } |
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| 38 | |
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| 39 | void DataArray::getArray(float *output){ |
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| 40 | for(int i=0;i<this->numPixels;i++) output[i] = this->array[i]; |
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| 41 | } |
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| 42 | |
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| 43 | void DataArray::saveArray(float *input, long size){ |
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| 44 | delete [] this->array; |
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| 45 | // Need check for change in number of pixels! |
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| 46 | this->numPixels = size; |
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| 47 | this->array = new float[size]; |
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| 48 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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| 49 | } |
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| 50 | |
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| 51 | void DataArray::getDim(long &x, long &y, long &z){ |
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| 52 | if(numDim>0) x=axisDim[0]; |
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| 53 | else x=0; |
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| 54 | if(numDim>1) y=axisDim[1]; |
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| 55 | else y=0; |
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| 56 | if(numDim>2) z=axisDim[2]; |
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| 57 | else z=0; |
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| 58 | } |
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| 59 | |
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| 60 | void DataArray::addObject(Detection object){ |
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| 61 | // adds a single detection to the object list |
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| 62 | // objectList is a vector, so just use push_back() |
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| 63 | this->objectList.push_back(object); |
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| 64 | } |
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| 65 | |
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| 66 | void DataArray::addObjectList(vector <Detection> newlist) { |
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| 67 | for(int i=0;i<newlist.size();i++) this->objectList.push_back(newlist[i]); |
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| 68 | } |
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| 69 | |
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| 70 | std::ostream& operator<< ( std::ostream& theStream, DataArray &array){ |
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| 71 | |
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| 72 | for(int i=0;i<array.numDim;i++){ |
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| 73 | if(i>0) theStream<<"x"; |
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| 74 | theStream<<array.axisDim[i]; |
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| 75 | } |
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| 76 | theStream<<endl; |
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| 77 | theStream<<array.objectList.size()<<" detections:"<<endl<<"--------------\n"; |
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| 78 | for(int i=0;i<array.objectList.size();i++){ |
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| 79 | theStream << "Detection #" << array.objectList[i].getID()<<endl; |
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| 80 | Detection *obj = new Detection; |
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| 81 | *obj = array.objectList[i]; |
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| 82 | for(int j=0;j<obj->getSize();j++){ |
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| 83 | obj->setX(j,obj->getX(j)+obj->getXOffset()); |
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| 84 | obj->setY(j,obj->getY(j)+obj->getYOffset()); |
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| 85 | obj->setZ(j,obj->getZ(j)+obj->getZOffset()); |
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| 86 | } |
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| 87 | theStream<<*obj; |
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| 88 | delete obj; |
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| 89 | } |
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| 90 | theStream<<"--------------\n"; |
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| 91 | } |
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| 92 | |
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| 93 | /****************************************************************/ |
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| 94 | ///////////////////////////////////////////////////////////// |
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| 95 | //// Functions for Image class |
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| 96 | ///////////////////////////////////////////////////////////// |
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| 97 | |
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| 98 | Image::Image(long size){ |
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| 99 | // need error handling in case size<0 !!! |
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| 100 | if(size>0){ |
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| 101 | this->array = new float[size]; |
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| 102 | this->pValue = new float[size]; |
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| 103 | this->mask = new short int[size]; |
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| 104 | } |
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| 105 | this->numPixels = size; |
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| 106 | this->axisDim = new long[2]; |
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| 107 | this->numDim = 2; |
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| 108 | } |
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| 109 | |
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| 110 | Image::Image(long *dimensions){ |
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| 111 | int size = dimensions[0] * dimensions[1]; |
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| 112 | this->numPixels = size; |
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| 113 | if(size>0){ |
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| 114 | this->array = new float[size]; |
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| 115 | this->pValue = new float[size]; |
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| 116 | this->mask = new short int[size]; |
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| 117 | } |
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| 118 | this->numDim=2; |
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| 119 | this->axisDim = new long[2]; |
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| 120 | for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i]; |
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| 121 | for(int i=0;i<size;i++) this->mask[i] = 0; |
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| 122 | } |
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| 123 | |
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| 124 | void Image::saveArray(float *input, long size){ |
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| 125 | // Need check for change in number of pixels! |
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| 126 | if(this->numPixels>0){ |
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| 127 | delete [] array; |
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| 128 | delete [] pValue; |
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| 129 | delete [] mask; |
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| 130 | } |
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| 131 | this->numPixels = size; |
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| 132 | this->array = new float[size]; |
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| 133 | this->pValue = new float[size]; |
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| 134 | this->mask = new short int[size]; |
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| 135 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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| 136 | for(int i=0;i<size;i++) this->mask[i] = 0; |
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| 137 | } |
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| 138 | |
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| 139 | void Image::maskObject(Detection &object) |
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| 140 | { |
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| 141 | /** |
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| 142 | * Image::maskObject(Detection &) |
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| 143 | * A function that increments the mask for each pixel of the detection. |
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| 144 | */ |
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| 145 | for(long i=0;i<object.getSize();i++){ |
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| 146 | this->setMaskValue(object.getX(i),object.getY(i),1); |
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| 147 | } |
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[53] | 148 | } |
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[3] | 149 | |
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[53] | 150 | void Image::extractSpectrum(float *Array, long *dim, long pixel) |
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| 151 | { |
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| 152 | /** |
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| 153 | * Image::extractSpectrum(float *, int) |
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| 154 | * A function to extract a 1-D spectrum from a 3-D array. |
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| 155 | * The array is assumed to be 3-D with the third dimension the spectral one. |
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| 156 | * The dimensions of the array are in the dim[] array. |
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| 157 | * The spectrum extracted is the one lying in the spatial pixel referenced |
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| 158 | * by the third argument. |
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| 159 | */ |
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| 160 | float *spec = new float[dim[2]]; |
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| 161 | for(int z=0;z<dim[2];z++) spec[z] = Array[z*dim[0]*dim[1] + pixel]; |
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| 162 | this->saveArray(spec,dim[2]); |
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| 163 | delete [] spec; |
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[3] | 164 | } |
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| 165 | |
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[53] | 166 | void Image::extractImage(float *Array, long *dim, long channel) |
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| 167 | { |
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| 168 | /** |
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| 169 | * Image::extractImage(float *, int) |
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| 170 | * A function to extract a 2-D image from a 3-D array. |
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| 171 | * The array is assumed to be 3-D with the third dimension the spectral one. |
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| 172 | * The dimensions of the array are in the dim[] array. |
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| 173 | * The image extracted is the one lying in the channel referenced |
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| 174 | * by the third argument. |
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| 175 | */ |
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| 176 | float *image = new float[dim[0]*dim[1]]; |
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| 177 | for(int npix=0; npix<dim[0]*dim[1]; npix++){ |
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| 178 | image[npix] = Array[channel*dim[0]*dim[1] + npix]; |
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| 179 | } |
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| 180 | this->saveArray(image,dim[0]*dim[1]); |
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| 181 | delete [] image; |
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| 182 | } |
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| 183 | |
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[96] | 184 | void Image::removeMW() |
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| 185 | { |
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| 186 | /** |
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| 187 | * Image::removeMW() |
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| 188 | * A function to remove the Milky Way range of channels from a 1-D spectrum. |
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| 189 | * The array in this Image is assumed to be 1-D, with only the first axisDim |
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| 190 | * equal to 1. |
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| 191 | * The values of the MW channels are set to 0, unless they are BLANK. |
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| 192 | */ |
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| 193 | int maxMW = this->par.getMaxMW(); |
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| 194 | int minMW = this->par.getMinMW(); |
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| 195 | if(this->par.getFlagMW() && (this->axisDim[1]==1)){ |
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| 196 | for(int z=0;z<this->axisDim[0];z++){ |
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| 197 | if(!this->isBlank(z) && this->par.isInMW(z)) this->array[z]=0.; |
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| 198 | } |
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| 199 | } |
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| 200 | } |
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| 201 | |
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[53] | 202 | void Image::findStats(int code) |
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| 203 | { |
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| 204 | /** |
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| 205 | * Image::findStats(int code) |
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| 206 | * Front-end to function to find the stats (mean/median & sigma/madfm) and |
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| 207 | * store them in the "mean" and "sigma" members of Image. |
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| 208 | * The choice of normal(mean & sigma) or robust (median & madfm) is made via the |
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| 209 | * code parameter. This is stored as a decimal number, with 0s representing |
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| 210 | * normal stats, and 1s representing robust. |
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| 211 | * The 10s column is the mean, the 1s column the sigma. |
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| 212 | * Eg: 00 -- meanσ 01 -- mean&madfm; 10 -- medianσ 11 -- median&madfm |
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| 213 | * If calculated, the madfm value is corrected to sigma units. |
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| 214 | * The Image member "cut" is also assigned using the parameter in Image's par |
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| 215 | * (needs to be defined first -- also for the blank pixel determination). |
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| 216 | */ |
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| 217 | float *tempArray = new float[this->numPixels]; |
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| 218 | int goodSize=0; |
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| 219 | for(int i=0; i<this->numPixels; i++) |
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| 220 | if(!this->isBlank(i)) tempArray[goodSize++] = this->array[i]; |
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| 221 | float tempMean,tempSigma,tempMedian,tempMADFM; |
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| 222 | if(code != 0) findMedianStats(tempArray,goodSize,tempMedian,tempMADFM); |
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| 223 | if(code != 11) findNormalStats(tempArray,goodSize,tempMean,tempSigma); |
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| 224 | switch(code) |
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| 225 | { |
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| 226 | case 0: |
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| 227 | findNormalStats(tempArray,goodSize,tempMean,tempSigma); |
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| 228 | this->mean = tempMean; |
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| 229 | this->sigma = tempSigma; |
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| 230 | break; |
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| 231 | case 10: |
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[78] | 232 | this->mean = findMedian(tempArray,goodSize);; |
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| 233 | this->sigma = findStddev(tempArray,goodSize); |
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[53] | 234 | break; |
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| 235 | case 1: |
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[78] | 236 | this->mean = findMean(tempArray,goodSize); |
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[53] | 237 | this->sigma = findMADFM(tempArray,goodSize)/correctionFactor; |
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| 238 | break; |
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| 239 | case 11: |
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| 240 | default: |
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| 241 | if(code!=11) std::cerr << |
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| 242 | "Invalid code ("<<code<<") in findStats. Using robust method.\n"; |
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| 243 | findMedianStats(tempArray,goodSize,tempMedian,tempMADFM); |
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| 244 | this->mean = tempMedian; |
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| 245 | this->sigma = tempMADFM/correctionFactor; |
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| 246 | break; |
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| 247 | } |
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| 248 | this->cutLevel = this->par.getCut(); |
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| 249 | delete [] tempArray; |
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| 250 | } |
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| 251 | |
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[3] | 252 | /****************************************************************/ |
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| 253 | ///////////////////////////////////////////////////////////// |
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| 254 | //// Functions for Cube class |
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| 255 | ///////////////////////////////////////////////////////////// |
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| 256 | |
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| 257 | Cube::Cube(long size){ |
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| 258 | // need error handling in case size<0 !!! |
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| 259 | if(size>0){ |
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| 260 | this->array = new float[size]; |
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| 261 | this->recon = new float[size]; |
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| 262 | } |
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| 263 | this->numPixels = size; |
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| 264 | this->axisDim = new long[2]; |
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| 265 | this->numDim = 3; |
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| 266 | this->reconExists = false; |
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[90] | 267 | // flagWCS = false; |
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[3] | 268 | } |
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| 269 | |
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| 270 | Cube::Cube(long *dimensions){ |
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| 271 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
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| 272 | int imsize = dimensions[0] * dimensions[1]; |
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| 273 | this->numPixels = size; |
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| 274 | if(size>0){ |
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| 275 | this->array = new float[size]; |
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| 276 | this->detectMap = new short[imsize]; |
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| 277 | if(this->par.getFlagATrous()) |
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| 278 | this->recon = new float[size]; |
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| 279 | if(this->par.getFlagBaseline()) |
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| 280 | this->baseline = new float[size]; |
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| 281 | } |
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| 282 | this->numDim = 3; |
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| 283 | this->axisDim = new long[3]; |
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| 284 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
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| 285 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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[90] | 286 | // this->wcs = new wcsprm; |
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| 287 | // this->wcs->flag=-1; |
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| 288 | // wcsini(true,3,this->wcs); |
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| 289 | // flagWCS = false; |
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[3] | 290 | } |
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| 291 | |
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| 292 | void Cube::initialiseCube(long *dimensions){ |
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| 293 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
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| 294 | int imsize = dimensions[0] * dimensions[1]; |
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| 295 | this->numPixels = size; |
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| 296 | if(size>0){ |
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| 297 | this->array = new float[size]; |
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| 298 | this->detectMap = new short[imsize]; |
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| 299 | this->specMean = new float[imsize]; |
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| 300 | this->specSigma = new float[imsize]; |
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| 301 | this->chanMean = new float[dimensions[2]]; |
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| 302 | this->chanSigma = new float[dimensions[2]]; |
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[76] | 303 | if(this->par.getFlagATrous()) |
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[3] | 304 | this->recon = new float[size]; |
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| 305 | if(this->par.getFlagBaseline()) |
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| 306 | this->baseline = new float[size]; |
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| 307 | } |
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| 308 | this->numDim = 3; |
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| 309 | this->axisDim = new long[3]; |
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| 310 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
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| 311 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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[90] | 312 | // this->wcs = new wcsprm; |
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| 313 | // this->wcs->flag=-1; |
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| 314 | // wcsini(true,3,this->wcs); |
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[3] | 315 | } |
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| 316 | |
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| 317 | void Cube::saveArray(float *input, long size){ |
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| 318 | // Need check for change in number of pixels! |
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| 319 | if(this->numPixels>0) delete [] array; |
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| 320 | this->numPixels = size; |
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| 321 | this->array = new float[size]; |
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| 322 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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| 323 | } |
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| 324 | |
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| 325 | void Cube::saveRecon(float *input, long size){ |
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| 326 | // Need check for change in number of pixels! |
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[71] | 327 | if(this->numPixels>0) delete [] this->recon; |
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[3] | 328 | this->numPixels = size; |
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| 329 | this->recon = new float[size]; |
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| 330 | for(int i=0;i<size;i++) this->recon[i] = input[i]; |
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| 331 | this->reconExists = true; |
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| 332 | } |
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| 333 | |
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| 334 | void Cube::getRecon(float *output){ |
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| 335 | // Need check for change in number of pixels! |
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| 336 | long size = this->numPixels; |
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| 337 | for(int i=0;i<size;i++){ |
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| 338 | if(this->reconExists) output[i] = this->recon[i]; |
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| 339 | else output[i] = 0.; |
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| 340 | } |
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| 341 | } |
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| 342 | |
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[86] | 343 | void Cube::removeMW() |
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| 344 | { |
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[96] | 345 | if(this->par.getFlagMW()){ |
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| 346 | for(int pix=0;pix<this->axisDim[0]*this->axisDim[1];pix++){ |
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| 347 | for(int z=0;z<this->axisDim[2];z++){ |
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| 348 | int pos = z*this->axisDim[0]*this->axisDim[1] + pix; |
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| 349 | if(!this->isBlank(pos) && this->par.isInMW(z)) this->array[pos]=0.; |
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| 350 | } |
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[86] | 351 | } |
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| 352 | } |
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| 353 | } |
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| 354 | |
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[3] | 355 | ////////// WCS-related functions |
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| 356 | |
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[90] | 357 | // void Cube::setWCS(wcsprm *w) |
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| 358 | // { |
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| 359 | // /** |
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| 360 | // * Cube::setWCS(wcsprm *) |
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| 361 | // * A function that assigns the cube's wcs parameters, and runs |
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| 362 | // * wcsset to set it up correctly. |
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| 363 | // * Performs a check to see if the WCS is good (by looking at |
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| 364 | // * the lng and lat wcsprm parameters), and sets the flagWCS accordingly. |
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| 365 | // */ |
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[3] | 366 | |
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[90] | 367 | // wcscopy(true,w,this->wcs); |
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| 368 | // wcsset(this->wcs); |
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| 369 | // if( (w->lng!=-1) && (w->lat!=-1) ) this->flagWCS = true; |
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| 370 | // } |
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[3] | 371 | |
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[90] | 372 | // wcsprm *Cube::getWCS() |
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| 373 | // { |
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| 374 | // /** |
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| 375 | // * Cube::getWCS() |
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| 376 | // * A function that returns a wcsprm object corresponding to the cube's WCS. |
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| 377 | // */ |
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[3] | 378 | |
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[90] | 379 | // wcsprm *wNew = new wcsprm; |
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| 380 | // wNew->flag=-1; |
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| 381 | // wcsini(true,this->wcs->naxis,wNew); |
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| 382 | // wcscopy(true,this->wcs,wNew); |
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| 383 | // return wNew; |
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| 384 | // } |
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[3] | 385 | |
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| 386 | void Cube::calcObjectWCSparams() |
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| 387 | { |
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| 388 | /** |
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| 389 | * Cube::calcObjectWCSparams() |
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| 390 | * A function that calculates the WCS parameters for each object in the |
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| 391 | * cube's list of detections. |
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| 392 | * Each object gets an ID number set (just the order in the list), and if the |
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| 393 | * WCS is good, the WCS paramters are calculated. |
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| 394 | */ |
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| 395 | |
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| 396 | for(int i=0; i<this->objectList.size();i++){ |
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| 397 | this->objectList[i].setID(i+1); |
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[90] | 398 | // if(this->flagWCS) this->objectList[i].calcWCSparams(this->wcs); |
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| 399 | this->objectList[i].calcWCSparams(this->head); |
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| 400 | // this->objectList[i].setIntegFlux( this->objectList[i].getIntegFlux()/this->par.getBeamSize() ); |
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[86] | 401 | // this corrects the integrated flux for the beam size. |
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[3] | 402 | } |
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| 403 | |
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| 404 | |
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| 405 | } |
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| 406 | |
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| 407 | void Cube::sortDetections() |
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| 408 | { |
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| 409 | /** |
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| 410 | * Cube::sortDetections() |
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| 411 | * A front end to the sort-by functions. |
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| 412 | * If there is a good WCS, the detection list is sorted by velocity. |
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| 413 | * Otherwise, it is sorted by increasing z-pixel value. |
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| 414 | * The ID numbers are then re-calculated. |
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| 415 | */ |
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| 416 | |
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[90] | 417 | if(this->head.isWCS()) SortByVel(this->objectList); |
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[3] | 418 | else SortByZ(this->objectList); |
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| 419 | for(int i=0; i<this->objectList.size();i++) this->objectList[i].setID(i+1); |
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| 420 | |
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| 421 | } |
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| 422 | |
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| 423 | void Cube::updateDetectMap() |
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| 424 | { |
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| 425 | /** |
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| 426 | * Cube::updateDetectMap() |
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| 427 | * A function that, for each detected object in the cube's list, increments the |
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| 428 | * cube's detection map by the required amount at each pixel. |
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| 429 | */ |
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| 430 | |
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| 431 | for(int obj=0;obj<this->objectList.size();obj++) |
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| 432 | for(int pix=0;pix<this->objectList[obj].getSize();pix++) |
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| 433 | this->detectMap[this->objectList[obj].getX(pix)+this->objectList[obj].getY(pix)*this->axisDim[0]]++; |
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| 434 | } |
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| 435 | |
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| 436 | void Cube::updateDetectMap(Detection obj) |
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| 437 | { |
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| 438 | /** |
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| 439 | * Cube::updateDetectMap(Detection) |
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| 440 | * A function that, for the given object, increments the cube's |
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| 441 | * detection map by the required amount at each pixel. |
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| 442 | */ |
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| 443 | for(int pix=0;pix<obj.getSize();pix++) |
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| 444 | this->detectMap[obj.getX(pix)+obj.getY(pix)*this->axisDim[0]]++; |
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| 445 | } |
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| 446 | |
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| 447 | void Cube::setCubeStats() |
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| 448 | { |
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| 449 | // First set the stats for each spectrum (ie. each spatial pixel) |
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| 450 | long xySize = this->axisDim[0]*this->axisDim[1]; |
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| 451 | float *spec = new float[this->axisDim[2]]; |
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| 452 | for(int i=0;i<xySize;i++){ |
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| 453 | for(int z=0;z<this->axisDim[2];z++){ |
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| 454 | //Two cases: i) have reconstructed -- use residuals |
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| 455 | // ii) otherwise -- use original array |
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| 456 | if(this->reconExists) spec[z] = this->array[z*xySize+i] - this->recon[z*xySize+1]; |
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| 457 | else spec[z] = this->array[z*xySize+i]; |
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| 458 | } |
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| 459 | findMedianStats(spec,this->axisDim[2],this->specMean[i],this->specSigma[i]); |
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| 460 | } |
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| 461 | delete spec; |
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| 462 | // Then set the stats for each channel map |
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| 463 | float *im = new float[xySize]; |
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| 464 | for(int z=0;z<this->axisDim[2];z++){ |
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| 465 | for(int i=0;i<xySize;i++){ |
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| 466 | if(this->reconExists) im[i] = this->array[z*xySize+i] - this->recon[z*xySize+1]; |
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| 467 | else im[i] = this->array[z*xySize+i]; |
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| 468 | |
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| 469 | } |
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| 470 | findMedianStats(im,this->axisDim[2],this->chanMean[z],this->chanSigma[z]); |
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| 471 | this->chanSigma[z] /= correctionFactor; |
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| 472 | } |
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| 473 | delete im; |
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| 474 | |
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| 475 | } |
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[87] | 476 | |
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| 477 | float Cube::enclosedFlux(Detection obj) |
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| 478 | { |
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| 479 | /** |
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| 480 | * float Cube::enclosedFlux(Detection obj) |
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| 481 | * A function to calculate the flux enclosed by the range |
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| 482 | * of pixels detected in the object obj (not necessarily all |
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| 483 | * pixels will have been detected). |
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| 484 | */ |
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| 485 | obj.calcParams(); |
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| 486 | int xsize = obj.getXmax()-obj.getXmin()+1; |
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| 487 | int ysize = obj.getYmax()-obj.getYmin()+1; |
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| 488 | int zsize = obj.getZmax()-obj.getZmin()+1; |
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| 489 | vector <float> fluxArray(xsize*ysize*zsize,0.); |
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| 490 | for(int x=0;x<xsize;x++){ |
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| 491 | for(int y=0;y<ysize;y++){ |
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| 492 | for(int z=0;z<zsize;z++){ |
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| 493 | fluxArray[x+y*xsize+z*ysize*xsize] = |
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| 494 | this->getPixValue(x+obj.getXmin(),y+obj.getYmin(),z+obj.getZmin()); |
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[100] | 495 | if(this->par.getFlagNegative()) fluxArray[x+y*xsize+z*ysize*xsize] *= -1.; |
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[87] | 496 | } |
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| 497 | } |
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| 498 | } |
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| 499 | float sum = 0.; |
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| 500 | for(int i=0;i<fluxArray.size();i++) |
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| 501 | if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i]; |
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| 502 | return sum; |
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| 503 | } |
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| 504 | |
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| 505 | bool Cube::objAtEdge(Detection obj) |
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| 506 | { |
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| 507 | /** |
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| 508 | * bool Cube::objAtEdge() |
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| 509 | * A function to test whether the object obj |
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| 510 | * lies at the edge of the cube's field -- |
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| 511 | * either at the boundary, or next to BLANKs |
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| 512 | */ |
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| 513 | |
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| 514 | bool atEdge = false; |
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| 515 | |
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| 516 | int pix = 0; |
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| 517 | while(!atEdge && pix<obj.getSize()){ |
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| 518 | // loop over each pixel in the object, until we find an edge pixel. |
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| 519 | Voxel vox = obj.getPixel(pix); |
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| 520 | for(int dx=-1;dx<=1;dx+=2){ |
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[94] | 521 | if(((vox.getX()+dx)<0) || ((vox.getX()+dx)>=this->axisDim[0])) atEdge = true; |
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[87] | 522 | else if(this->isBlank(vox.getX()+dx,vox.getY(),vox.getZ())) atEdge = true; |
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| 523 | } |
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| 524 | for(int dy=-1;dy<=1;dy+=2){ |
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[94] | 525 | if(((vox.getY()+dy)<0) || ((vox.getY()+dy)>=this->axisDim[1])) atEdge = true; |
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[87] | 526 | else if(this->isBlank(vox.getX(),vox.getY()+dy,vox.getZ())) atEdge = true; |
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| 527 | } |
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| 528 | for(int dz=-1;dz<=1;dz+=2){ |
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[94] | 529 | if(((vox.getZ()+dz)<0) || ((vox.getZ()+dz)>=this->axisDim[2])) atEdge = true; |
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[87] | 530 | else if(this->isBlank(vox.getX(),vox.getY(),vox.getZ()+dz)) atEdge = true; |
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| 531 | } |
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| 532 | pix++; |
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| 533 | } |
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| 534 | |
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| 535 | return atEdge; |
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| 536 | } |
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| 537 | |
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| 538 | void Cube::setObjectFlags() |
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| 539 | { |
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| 540 | /** |
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| 541 | * void Cube::setObjectFlags() |
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| 542 | * A function to set any warning flags for all the detected objects |
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| 543 | * associated with the cube. |
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| 544 | * Flags to be looked for: |
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| 545 | * * Negative enclosed flux (N) |
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| 546 | * * Object at edge of field (E) |
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| 547 | */ |
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| 548 | |
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| 549 | for(int i=0;i<this->objectList.size();i++){ |
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| 550 | |
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| 551 | if( this->enclosedFlux(this->objectList[i]) < 0. ) |
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| 552 | this->objectList[i].addToFlagText("N"); |
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| 553 | |
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| 554 | if( this->objAtEdge(this->objectList[i]) ) |
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| 555 | this->objectList[i].addToFlagText("E"); |
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| 556 | |
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| 557 | } |
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| 558 | |
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| 559 | } |
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