1 | #include <unistd.h> |
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2 | #include <iostream> |
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3 | #include <iomanip> |
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4 | #include <vector> |
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5 | #include <algorithm> |
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6 | #include <string> |
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7 | #include <math.h> |
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8 | |
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9 | #include <wcs.h> |
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10 | |
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11 | #include <duchamp.hh> |
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12 | #include <param.hh> |
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13 | #include <Cubes/cubes.hh> |
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14 | #include <Detection/detection.hh> |
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15 | #include <Detection/columns.hh> |
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16 | #include <Utils/utils.hh> |
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17 | #include <Utils/mycpgplot.hh> |
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18 | #include <Utils/Statistics.hh> |
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19 | using namespace Column; |
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20 | using namespace mycpgplot; |
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21 | using namespace Statistics; |
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22 | |
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23 | /****************************************************************/ |
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24 | /////////////////////////////////////////////////// |
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25 | //// Functions for DataArray class: |
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26 | /////////////////////////////////////////////////// |
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27 | |
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28 | DataArray::DataArray(){ |
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29 | /** |
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30 | * Fundamental constructor for DataArray. |
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31 | * Number of dimensions and pixels are set to 0. Nothing else allocated. |
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32 | */ |
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33 | this->numDim=0; |
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34 | this->numPixels=0; |
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35 | }; |
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36 | //-------------------------------------------------------------------- |
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37 | |
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38 | DataArray::DataArray(short int nDim){ |
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39 | /** |
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40 | * N-dimensional constructor for DataArray. |
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41 | * Number of dimensions defined, and dimension array allocated. |
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42 | * Number of pixels are set to 0. |
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43 | * \param nDim Number of dimensions. |
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44 | */ |
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45 | if(nDim>0) this->axisDim = new long[nDim]; |
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46 | this->numDim=nDim; |
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47 | this->numPixels=0; |
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48 | }; |
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49 | //-------------------------------------------------------------------- |
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50 | |
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51 | DataArray::DataArray(short int nDim, long size){ |
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52 | /** |
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53 | * N-dimensional constructor for DataArray. |
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54 | * Number of dimensions and number of pixels defined. |
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55 | * Arrays allocated based on these values. |
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56 | * \param nDim Number of dimensions. |
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57 | * \param size Number of pixels. |
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58 | * |
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59 | * Note that we can assign values to the dimension array. |
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60 | */ |
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61 | |
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62 | if(size<0) |
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63 | duchampError("DataArray(nDim,size)", |
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64 | "Negative size -- could not define DataArray"); |
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65 | else if(nDim<0) |
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66 | duchampError("DataArray(nDim,size)", |
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67 | "Negative number of dimensions: could not define DataArray"); |
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68 | else { |
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69 | if(size>0) this->array = new float[size]; |
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70 | this->numPixels = size; |
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71 | if(nDim>0) this->axisDim = new long[nDim]; |
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72 | this->numDim = nDim; |
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73 | } |
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74 | } |
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75 | //-------------------------------------------------------------------- |
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76 | |
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77 | DataArray::DataArray(short int nDim, long *dimensions) |
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78 | { |
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79 | /** |
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80 | * Most robust constructor for DataArray. |
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81 | * Number and sizes of dimensions are defined, and hence the number of |
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82 | * pixels. Arrays allocated based on these values. |
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83 | * \param nDim Number of dimensions. |
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84 | * \param dimensions Array giving sizes of dimensions. |
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85 | */ |
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86 | if(nDim<0) |
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87 | duchampError("DataArray(nDim,dimArray)", |
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88 | "Negative number of dimensions: could not define DataArray"); |
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89 | else { |
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90 | int size = dimensions[0]; |
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91 | for(int i=1;i<nDim;i++) size *= dimensions[i]; |
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92 | if(size<0) |
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93 | duchampError("DataArray(nDim,dimArray)", |
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94 | "Negative size: could not define DataArray"); |
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95 | else{ |
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96 | this->numPixels = size; |
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97 | if(size>0) this->array = new float[size]; |
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98 | this->numDim=nDim; |
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99 | if(nDim>0) this->axisDim = new long[nDim]; |
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100 | for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i]; |
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101 | } |
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102 | } |
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103 | } |
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104 | //-------------------------------------------------------------------- |
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105 | |
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106 | DataArray::~DataArray() |
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107 | { |
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108 | /** |
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109 | * Destructor -- arrays deleted if they have been allocated, and the |
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110 | * object list is cleared. |
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111 | */ |
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112 | if(this->numPixels>0) delete [] this->array; |
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113 | if(this->numDim>0) delete [] this->axisDim; |
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114 | this->objectList.clear(); |
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115 | } |
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116 | //-------------------------------------------------------------------- |
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117 | //-------------------------------------------------------------------- |
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118 | |
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119 | void DataArray::getDim(long &x, long &y, long &z){ |
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120 | /** |
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121 | * The sizes of the first three dimensions (if they exist) are returned. |
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122 | * \param x The first dimension. Defaults to 0 if numDim \f$\le\f$ 0. |
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123 | * \param y The second dimension. Defaults to 1 if numDim \f$\le\f$ 1. |
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124 | * \param z The third dimension. Defaults to 1 if numDim \f$\le\f$ 2. |
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125 | */ |
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126 | if(this->numDim>0) x=this->axisDim[0]; |
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127 | else x=0; |
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128 | if(this->numDim>1) y=this->axisDim[1]; |
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129 | else y=1; |
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130 | if(this->numDim>2) z=this->axisDim[2]; |
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131 | else z=1; |
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132 | } |
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133 | //-------------------------------------------------------------------- |
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134 | |
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135 | void DataArray::getDimArray(long *output){ |
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136 | /** |
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137 | * The axisDim array is written to output. This needs to be defined |
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138 | * beforehand: no checking is done on the memory. |
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139 | * \param output The array that is written to. |
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140 | */ |
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141 | for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i]; |
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142 | } |
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143 | //-------------------------------------------------------------------- |
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144 | |
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145 | void DataArray::getArray(float *output){ |
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146 | /** |
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147 | * The pixel value array is written to output. This needs to be defined |
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148 | * beforehand: no checking is done on the memory. |
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149 | * \param output The array that is written to. |
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150 | */ |
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151 | for(int i=0;i<this->numPixels;i++) output[i] = this->array[i]; |
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152 | } |
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153 | //-------------------------------------------------------------------- |
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154 | |
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155 | void DataArray::saveArray(float *input, long size){ |
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156 | /** |
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157 | * Saves the array in input to the pixel array DataArray::array. |
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158 | * The size of the array given must be the same as the current number of |
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159 | * pixels, else an error message is returned and nothing is done. |
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160 | * \param input The array of values to be saved. |
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161 | * \param size The size of input. |
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162 | */ |
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163 | if(size != this->numPixels) |
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164 | duchampError("DataArray::saveArray", |
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165 | "Input array different size to existing array. Cannot save."); |
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166 | else { |
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167 | if(this->numPixels>0) delete [] this->array; |
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168 | this->numPixels = size; |
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169 | this->array = new float[size]; |
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170 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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171 | } |
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172 | } |
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173 | //-------------------------------------------------------------------- |
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174 | |
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175 | void DataArray::addObject(Detection object){ |
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176 | /** |
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177 | * \param object The object to be added to the object list. |
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178 | */ |
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179 | // objectList is a vector, so just use push_back() |
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180 | this->objectList.push_back(object); |
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181 | } |
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182 | //-------------------------------------------------------------------- |
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183 | |
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184 | void DataArray::addObjectList(vector <Detection> newlist) { |
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185 | /** |
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186 | * \param newlist The list of objects to be added to the object list. |
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187 | */ |
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188 | for(int i=0;i<newlist.size();i++) this->objectList.push_back(newlist[i]); |
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189 | } |
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190 | //-------------------------------------------------------------------- |
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191 | |
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192 | void DataArray::addObjectOffsets(){ |
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193 | /** |
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194 | * Add the pixel offsets (that is, offsets from the corner of the cube to the |
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195 | * corner of the utilised part) that are stored in the Param set to the |
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196 | * coordinate values of each object in the object list. |
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197 | */ |
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198 | for(int i=0;i<this->objectList.size();i++){ |
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199 | for(int p=0;p<this->objectList[i].getSize();p++){ |
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200 | this->objectList[i].setX(p,this->objectList[i].getX(p)+ |
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201 | this->par.getXOffset()); |
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202 | this->objectList[i].setY(p,this->objectList[i].getY(p)+ |
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203 | this->par.getYOffset()); |
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204 | this->objectList[i].setZ(p,this->objectList[i].getZ(p)+ |
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205 | this->par.getZOffset()); |
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206 | } |
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207 | } |
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208 | } |
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209 | //-------------------------------------------------------------------- |
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210 | |
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211 | bool DataArray::isDetection(float value){ |
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212 | /** |
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213 | * Is a given value a detection, based on the statistics in the |
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214 | * DataArray's StatsContainer? |
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215 | * \param value The pixel value to test. |
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216 | */ |
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217 | if(par.isBlank(value)) return false; |
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218 | else return Stats.isDetection(value); |
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219 | }; |
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220 | //-------------------------------------------------------------------- |
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221 | |
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222 | bool DataArray::isDetection(long voxel){ |
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223 | /** |
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224 | * Is a given pixel a detection, based on the statistics in the |
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225 | * DataArray's StatsContainer? |
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226 | * If the pixel lies outside the valid range for the data array, return false. |
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227 | * \param voxel Location of the DataArray's pixel to be tested. |
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228 | */ |
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229 | if((voxel<0)||(voxel>this->numPixels)) return false; |
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230 | else if(par.isBlank(this->array[voxel])) return false; |
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231 | else return Stats.isDetection(this->array[voxel]); |
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232 | }; |
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233 | //-------------------------------------------------------------------- |
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234 | |
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235 | std::ostream& operator<< ( std::ostream& theStream, DataArray &array) |
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236 | { |
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237 | /** |
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238 | * A way to print out the pixel coordinates & flux values of the |
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239 | * list of detected objects belonging to the DataArray. |
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240 | * These are formatted nicely according to the << operator for Detection, |
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241 | * with a line indicating the number of detections at the start. |
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242 | * \param theStream The ostream object to which the output should be sent. |
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243 | * \param array The DataArray containing the list of objects. |
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244 | */ |
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245 | for(int i=0;i<array.numDim;i++){ |
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246 | if(i>0) theStream<<"x"; |
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247 | theStream<<array.axisDim[i]; |
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248 | } |
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249 | theStream<<std::endl; |
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250 | theStream<<array.objectList.size()<<" detections:\n--------------\n"; |
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251 | for(int i=0;i<array.objectList.size();i++){ |
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252 | theStream << "Detection #" << array.objectList[i].getID()<<std::endl; |
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253 | Detection *obj = new Detection; |
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254 | *obj = array.objectList[i]; |
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255 | for(int j=0;j<obj->getSize();j++){ |
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256 | obj->setX(j,obj->getX(j)+obj->getXOffset()); |
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257 | obj->setY(j,obj->getY(j)+obj->getYOffset()); |
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258 | obj->setZ(j,obj->getZ(j)+obj->getZOffset()); |
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259 | } |
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260 | theStream<<*obj; |
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261 | delete obj; |
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262 | } |
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263 | theStream<<"--------------\n"; |
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264 | } |
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265 | |
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266 | /****************************************************************/ |
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267 | ///////////////////////////////////////////////////////////// |
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268 | //// Functions for Cube class |
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269 | ///////////////////////////////////////////////////////////// |
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270 | |
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271 | Cube::Cube(){ |
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272 | /** |
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273 | * Basic Constructor for Cube class. |
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274 | * numDim set to 3, but numPixels to 0 and all bool flags to false. |
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275 | * No allocation done. |
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276 | */ |
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277 | numPixels=0; numDim=3; |
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278 | reconExists = false; reconAllocated = false; baselineAllocated = false; |
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279 | }; |
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280 | //-------------------------------------------------------------------- |
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281 | |
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282 | Cube::Cube(long size){ |
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283 | /** |
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284 | * Alternative Cube constructor, where size is given but not individual |
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285 | * dimensions. Arrays are allocated as appropriate (according to the |
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286 | * relevant flags in Param set), but the Cube::axisDim array is not. |
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287 | */ |
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288 | this->reconAllocated = false; |
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289 | this->baselineAllocated = false; |
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290 | this->numPixels = this->numDim = 0; |
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291 | if(size<0) |
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292 | duchampError("Cube(size)","Negative size -- could not define Cube"); |
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293 | else{ |
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294 | if(size>0){ |
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295 | this->array = new float[size]; |
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296 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
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297 | this->recon = new float[size]; |
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298 | this->reconAllocated = true; |
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299 | } |
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300 | if(this->par.getFlagBaseline()){ |
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301 | this->baseline = new float[size]; |
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302 | this->baselineAllocated = true; |
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303 | } |
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304 | } |
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305 | this->numPixels = size; |
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306 | this->axisDim = new long[2]; |
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307 | this->numDim = 3; |
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308 | this->reconExists = false; |
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309 | } |
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310 | } |
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311 | //-------------------------------------------------------------------- |
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312 | |
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313 | Cube::Cube(long *dimensions){ |
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314 | /** |
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315 | * Alternative Cube constructor, where sizes of dimensions are given. |
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316 | * Arrays are allocated as appropriate (according to the |
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317 | * relevant flags in Param set), as is the Cube::axisDim array. |
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318 | */ |
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319 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
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320 | int imsize = dimensions[0] * dimensions[1]; |
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321 | this->reconAllocated = false; |
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322 | this->baselineAllocated = false; |
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323 | this->numPixels = this->numDim = 0; |
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324 | if((size<0) || (imsize<0) ) |
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325 | duchampError("Cube(dimArray)","Negative size -- could not define Cube"); |
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326 | else{ |
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327 | this->numPixels = size; |
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328 | if(size>0){ |
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329 | this->array = new float[size]; |
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330 | this->detectMap = new short[imsize]; |
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331 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
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332 | this->recon = new float[size]; |
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333 | this->reconAllocated = true; |
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334 | } |
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335 | if(this->par.getFlagBaseline()){ |
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336 | this->baseline = new float[size]; |
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337 | this->baselineAllocated = true; |
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338 | } |
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339 | } |
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340 | this->numDim = 3; |
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341 | this->axisDim = new long[3]; |
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342 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
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343 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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344 | this->reconExists = false; |
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345 | } |
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346 | } |
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347 | //-------------------------------------------------------------------- |
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348 | |
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349 | Cube::~Cube() |
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350 | { |
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351 | /** |
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352 | * The destructor deletes the memory allocated for Cube::detectMap, and, |
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353 | * if these have been allocated, Cube::recon and Cube::baseline. |
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354 | */ |
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355 | delete [] this->detectMap; |
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356 | if(this->reconAllocated) delete [] this->recon; |
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357 | if(this->baselineAllocated) delete [] this->baseline; |
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358 | } |
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359 | //-------------------------------------------------------------------- |
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360 | |
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361 | void Cube::initialiseCube(long *dimensions) |
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362 | { |
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363 | /** |
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364 | * This function will set the sizes of all arrays that will be used by Cube. |
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365 | * It will also define the values of the axis dimensions: this will be done |
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366 | * using the WCS in the FitsHeader class, so the WCS needs to be good and |
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367 | * have three axes. If this is not the case, the axes are assumed to be |
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368 | * ordered in the sense of lng,lat,spc. |
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369 | * |
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370 | * \param dimensions An array of values giving the dimensions (sizes) for |
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371 | * all axes. |
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372 | */ |
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373 | |
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374 | int lng,lat,spc,size,imsize; |
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375 | |
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376 | if(this->head.isWCS() && (this->head.getWCS()->naxis>=3)){ |
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377 | // if there is a WCS and there is at least 3 axes |
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378 | lng = this->head.getWCS()->lng; |
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379 | lat = this->head.getWCS()->lat; |
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380 | spc = this->head.getWCS()->spec; |
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381 | } |
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382 | else{ |
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383 | // just take dimensions[] at face value |
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384 | lng = 0; |
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385 | lat = 1; |
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386 | spc = 2; |
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387 | } |
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388 | size = dimensions[lng] * dimensions[lat] * dimensions[spc]; |
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389 | imsize = dimensions[lng] * dimensions[lat]; |
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390 | |
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391 | this->reconAllocated = false; |
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392 | this->baselineAllocated = false; |
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393 | |
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394 | if((size<0) || (imsize<0) ) |
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395 | duchampError("Cube::initialiseCube(dimArray)", |
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396 | "Negative size -- could not define Cube.\n"); |
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397 | else{ |
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398 | this->numPixels = size; |
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399 | if(size>0){ |
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400 | this->array = new float[size]; |
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401 | this->detectMap = new short[imsize]; |
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402 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()){ |
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403 | this->recon = new float[size]; |
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404 | this->reconAllocated = true; |
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405 | } |
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406 | if(this->par.getFlagBaseline()){ |
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407 | this->baseline = new float[size]; |
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408 | this->baselineAllocated = true; |
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409 | } |
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410 | } |
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411 | this->numDim = 3; |
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412 | this->axisDim = new long[3]; |
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413 | this->axisDim[0] = dimensions[lng]; |
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414 | this->axisDim[1] = dimensions[lat]; |
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415 | this->axisDim[2] = dimensions[spc]; |
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416 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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417 | this->reconExists = false; |
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418 | } |
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419 | } |
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420 | //-------------------------------------------------------------------- |
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421 | |
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422 | int Cube::getCube(){ |
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423 | /** |
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424 | * A front-end to the Cube::getCube() function, that does |
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425 | * subsection checks. |
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426 | * Assumes the Param is set up properly. |
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427 | */ |
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428 | string fname = par.getImageFile(); |
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429 | if(par.getFlagSubsection()) fname+=par.getSubsection(); |
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430 | return getCube(fname); |
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431 | }; |
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432 | //-------------------------------------------------------------------- |
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433 | |
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434 | int Cube::getopts(int argc, char ** argv) |
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435 | { |
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436 | /** |
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437 | * A function that reads in the command-line options, in a manner |
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438 | * tailored for use with the main Duchamp program. |
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439 | * Based on the options given, the appropriate Param set will be read |
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440 | * in to the Cube class. |
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441 | * |
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442 | * \param argc The number of command line arguments. |
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443 | * \param argv The array of command line arguments. |
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444 | */ |
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445 | |
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446 | int returnValue; |
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447 | if(argc==1){ |
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448 | std::cout << ERR_USAGE_MSG; |
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449 | returnValue = FAILURE; |
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450 | } |
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451 | else { |
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452 | string file; |
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453 | Param *par = new Param; |
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454 | char c; |
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455 | while( ( c = getopt(argc,argv,"p:f:hv") )!=-1){ |
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456 | switch(c) { |
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457 | case 'p': |
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458 | file = optarg; |
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459 | if(this->readParam(file)==FAILURE){ |
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460 | stringstream errmsg; |
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461 | errmsg << "Could not open parameter file " << file << ".\n"; |
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462 | duchampError("Duchamp",errmsg.str()); |
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463 | returnValue = FAILURE; |
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464 | } |
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465 | else returnValue = SUCCESS; |
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466 | break; |
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467 | case 'f': |
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468 | file = optarg; |
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469 | par->setImageFile(file); |
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470 | this->saveParam(*par); |
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471 | returnValue = SUCCESS; |
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472 | break; |
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473 | case 'v': |
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474 | std::cout << PROGNAME << " version " << VERSION << std::endl; |
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475 | returnValue = FAILURE; |
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476 | break; |
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477 | case 'h': |
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478 | default : |
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479 | std::cout << ERR_USAGE_MSG; |
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480 | returnValue = FAILURE; |
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481 | break; |
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482 | } |
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483 | } |
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484 | delete par; |
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485 | } |
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486 | return returnValue; |
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487 | } |
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488 | //-------------------------------------------------------------------- |
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489 | |
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490 | void Cube::readSavedArrays() |
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491 | { |
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492 | /** |
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493 | * This function reads in reconstructed and/or smoothed arrays that have |
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494 | * been saved on disk in FITS files. |
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495 | * To do this it calls the functions Cube::readReconCube() and |
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496 | * Cube::readSmoothCube(). |
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497 | * The Param set is consulted to determine which of these arrays are needed. |
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498 | */ |
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499 | |
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500 | // If the reconstructed array is to be read in from disk |
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501 | if( this->par.getFlagReconExists() && this->par.getFlagATrous() ){ |
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502 | std::cout << "Reading reconstructed array: "<<std::endl; |
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503 | if( this->readReconCube() == FAILURE){ |
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504 | std::stringstream errmsg; |
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505 | errmsg <<"Could not read in existing reconstructed array.\n" |
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506 | <<"Will perform reconstruction using assigned parameters.\n"; |
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507 | duchampWarning("Duchamp", errmsg.str()); |
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508 | this->par.setFlagReconExists(false); |
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509 | } |
---|
510 | else std::cout << "Reconstructed array available.\n"; |
---|
511 | } |
---|
512 | |
---|
513 | if( this->par.getFlagSmoothExists() && this->par.getFlagSmooth() ){ |
---|
514 | std::cout << "Reading Hanning-smoothed array: "<<std::endl; |
---|
515 | if( this->readSmoothCube() == FAILURE){ |
---|
516 | std::stringstream errmsg; |
---|
517 | errmsg <<"Could not read in existing smoothed array.\n" |
---|
518 | <<"Will smooth the cube using assigned parameters.\n"; |
---|
519 | duchampWarning("Duchamp", errmsg.str()); |
---|
520 | this->par.setFlagSmoothExists(false); |
---|
521 | } |
---|
522 | else std::cout << "Smoothed array available.\n"; |
---|
523 | } |
---|
524 | |
---|
525 | } |
---|
526 | |
---|
527 | //-------------------------------------------------------------------- |
---|
528 | |
---|
529 | void Cube::saveArray(float *input, long size){ |
---|
530 | if(size != this->numPixels){ |
---|
531 | stringstream errmsg; |
---|
532 | errmsg << "Input array different size to existing array (" |
---|
533 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
---|
534 | duchampError("Cube::saveArray",errmsg.str()); |
---|
535 | } |
---|
536 | else { |
---|
537 | if(this->numPixels>0) delete [] array; |
---|
538 | this->numPixels = size; |
---|
539 | this->array = new float[size]; |
---|
540 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
---|
541 | } |
---|
542 | } |
---|
543 | //-------------------------------------------------------------------- |
---|
544 | |
---|
545 | void Cube::saveRecon(float *input, long size){ |
---|
546 | /** |
---|
547 | * Saves the array in input to the reconstructed array Cube::recon |
---|
548 | * The size of the array given must be the same as the current number of |
---|
549 | * pixels, else an error message is returned and nothing is done. |
---|
550 | * If the recon array has already been allocated, it is deleted first, and |
---|
551 | * then the space is allocated. |
---|
552 | * Afterwards, the appropriate flags are set. |
---|
553 | * \param input The array of values to be saved. |
---|
554 | * \param size The size of input. |
---|
555 | */ |
---|
556 | if(size != this->numPixels){ |
---|
557 | stringstream errmsg; |
---|
558 | errmsg << "Input array different size to existing array (" |
---|
559 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
---|
560 | duchampError("Cube::saveRecon",errmsg.str()); |
---|
561 | } |
---|
562 | else { |
---|
563 | if(this->numPixels>0){ |
---|
564 | if(this->reconAllocated) delete [] this->recon; |
---|
565 | this->numPixels = size; |
---|
566 | this->recon = new float[size]; |
---|
567 | this->reconAllocated = true; |
---|
568 | for(int i=0;i<size;i++) this->recon[i] = input[i]; |
---|
569 | this->reconExists = true; |
---|
570 | } |
---|
571 | } |
---|
572 | } |
---|
573 | //-------------------------------------------------------------------- |
---|
574 | |
---|
575 | void Cube::getRecon(float *output){ |
---|
576 | /** |
---|
577 | * The reconstructed array is written to output. The output array needs to |
---|
578 | * be defined beforehand: no checking is done on the memory. |
---|
579 | * \param output The array that is written to. |
---|
580 | */ |
---|
581 | // Need check for change in number of pixels! |
---|
582 | for(int i=0;i<this->numPixels;i++){ |
---|
583 | if(this->reconExists) output[i] = this->recon[i]; |
---|
584 | else output[i] = 0.; |
---|
585 | } |
---|
586 | } |
---|
587 | //-------------------------------------------------------------------- |
---|
588 | |
---|
589 | void Cube::removeMW() |
---|
590 | { |
---|
591 | /** |
---|
592 | * The channels corresponding to the Milky Way range (as given by the Param |
---|
593 | * set) are all set to 0 in the pixel array. |
---|
594 | * Only done if the appropriate flag is set, and the pixels are not BLANK. |
---|
595 | * \deprecated |
---|
596 | */ |
---|
597 | if(this->par.getFlagMW()){ |
---|
598 | for(int pix=0;pix<this->axisDim[0]*this->axisDim[1];pix++){ |
---|
599 | for(int z=0;z<this->axisDim[2];z++){ |
---|
600 | int pos = z*this->axisDim[0]*this->axisDim[1] + pix; |
---|
601 | if(!this->isBlank(pos) && this->par.isInMW(z)) this->array[pos]=0.; |
---|
602 | } |
---|
603 | } |
---|
604 | } |
---|
605 | } |
---|
606 | //-------------------------------------------------------------------- |
---|
607 | |
---|
608 | void Cube::setCubeStatsOld() |
---|
609 | { |
---|
610 | /** |
---|
611 | * \deprecated |
---|
612 | * |
---|
613 | * Calculates the full statistics for the cube: mean, rms, median, madfm. |
---|
614 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
615 | * its default). |
---|
616 | * Also work out the threshold and store it in the Param set. |
---|
617 | * |
---|
618 | * For the stats calculations, we ignore BLANKs and MW channels. |
---|
619 | */ |
---|
620 | |
---|
621 | if(!this->par.getFlagFDR() && this->par.getFlagUserThreshold() ){ |
---|
622 | // if the user has defined a threshold, set this in the StatsContainer |
---|
623 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
624 | } |
---|
625 | else{ |
---|
626 | // only work out the mean etc if we need to. |
---|
627 | // the only reason we don't is if the user has specified a threshold. |
---|
628 | |
---|
629 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
630 | |
---|
631 | // get number of good pixels; |
---|
632 | int goodSize = 0; |
---|
633 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
634 | for(int z=0;z<this->axisDim[2];z++){ |
---|
635 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
636 | if(!this->isBlank(vox) && !this->par.isInMW(z)) goodSize++; |
---|
637 | } |
---|
638 | } |
---|
639 | |
---|
640 | float *tempArray = new float[goodSize]; |
---|
641 | |
---|
642 | goodSize=0; |
---|
643 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
644 | for(int z=0;z<this->axisDim[2];z++){ |
---|
645 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
646 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
647 | tempArray[goodSize++] = this->array[vox]; |
---|
648 | } |
---|
649 | } |
---|
650 | if(!this->reconExists){ |
---|
651 | // if there's no recon array, calculate everything from orig array |
---|
652 | this->Stats.calculate(tempArray,goodSize); |
---|
653 | } |
---|
654 | else{ |
---|
655 | // just get mean & median from orig array, and rms & madfm from recon |
---|
656 | StatsContainer<float> origStats,reconStats; |
---|
657 | origStats.calculate(tempArray,goodSize); |
---|
658 | goodSize=0; |
---|
659 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
660 | for(int z=0;z<this->axisDim[2];z++){ |
---|
661 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
662 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
663 | tempArray[goodSize++] = this->array[vox] - this->recon[vox]; |
---|
664 | } |
---|
665 | } |
---|
666 | reconStats.calculate(tempArray,goodSize); |
---|
667 | |
---|
668 | // Get the "middle" estimators from the original array. |
---|
669 | this->Stats.setMean(origStats.getMean()); |
---|
670 | this->Stats.setMedian(origStats.getMedian()); |
---|
671 | // Get the "spread" estimators from the residual (orig-recon) array |
---|
672 | this->Stats.setStddev(reconStats.getStddev()); |
---|
673 | this->Stats.setMadfm(reconStats.getMadfm()); |
---|
674 | } |
---|
675 | |
---|
676 | delete [] tempArray; |
---|
677 | |
---|
678 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
679 | // If the FDR method has been requested |
---|
680 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
681 | else{ |
---|
682 | // otherwise, calculate one based on the requested SNR cut level, and |
---|
683 | // then set the threshold parameter in the Par set. |
---|
684 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
685 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
686 | } |
---|
687 | |
---|
688 | |
---|
689 | } |
---|
690 | std::cout << "Using "; |
---|
691 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
692 | std::cout << "flux threshold of: "; |
---|
693 | float thresh = this->Stats.getThreshold(); |
---|
694 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
695 | std::cout << thresh << std::endl; |
---|
696 | |
---|
697 | } |
---|
698 | //-------------------------------------------------------------------- |
---|
699 | |
---|
700 | void Cube::setCubeStats() |
---|
701 | { |
---|
702 | /** |
---|
703 | * Calculates the full statistics for the cube: |
---|
704 | * mean, rms, median, madfm |
---|
705 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
706 | * its default). |
---|
707 | * Also work out the threshold and store it in the par set. |
---|
708 | * |
---|
709 | * Different from Cube::setCubeStatsOld() as it doesn't use the |
---|
710 | * getStats functions but has own versions of them hardcoded to |
---|
711 | * ignore BLANKs and MW channels. This saves on memory usage -- necessary |
---|
712 | * for dealing with very big files. |
---|
713 | */ |
---|
714 | |
---|
715 | if(!this->par.getFlagFDR() && this->par.getFlagUserThreshold() ){ |
---|
716 | // if the user has defined a threshold, set this in the StatsContainer |
---|
717 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
718 | } |
---|
719 | else{ |
---|
720 | // only work out the mean etc if we need to. |
---|
721 | // the only reason we don't is if the user has specified a threshold. |
---|
722 | |
---|
723 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
724 | |
---|
725 | long xysize = this->axisDim[0]*this->axisDim[1]; |
---|
726 | |
---|
727 | // get number of good pixels; |
---|
728 | int vox,goodSize = 0; |
---|
729 | for(int p=0;p<xysize;p++){ |
---|
730 | for(int z=0;z<this->axisDim[2];z++){ |
---|
731 | vox = z*xysize+p; |
---|
732 | if(!this->isBlank(vox) && !this->par.isInMW(z)) goodSize++; |
---|
733 | } |
---|
734 | } |
---|
735 | |
---|
736 | float *tempArray = new float[goodSize]; |
---|
737 | |
---|
738 | goodSize=0; |
---|
739 | for(int p=0;p<xysize;p++){ |
---|
740 | for(int z=0;z<this->axisDim[2];z++){ |
---|
741 | vox = z * xysize + p; |
---|
742 | if(!this->isBlank(vox) && !this->par.isInMW(z)){ |
---|
743 | tempArray[goodSize] = this->array[vox]; |
---|
744 | goodSize++; |
---|
745 | } |
---|
746 | } |
---|
747 | } |
---|
748 | |
---|
749 | float mean,median,stddev,madfm; |
---|
750 | mean = tempArray[0]; |
---|
751 | for(int i=1;i<goodSize;i++) mean += tempArray[i]; |
---|
752 | mean /= float(goodSize); |
---|
753 | mean = findMean(tempArray,goodSize); |
---|
754 | this->Stats.setMean(mean); |
---|
755 | |
---|
756 | std::sort(tempArray,tempArray+goodSize); |
---|
757 | if((goodSize%2)==0) |
---|
758 | median = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
759 | else median = tempArray[goodSize/2]; |
---|
760 | this->Stats.setMedian(median); |
---|
761 | |
---|
762 | |
---|
763 | if(!this->reconExists){ |
---|
764 | // if there's no recon array, calculate everything from orig array |
---|
765 | stddev = (tempArray[0]-mean) * (tempArray[0]-mean); |
---|
766 | for(int i=1;i<goodSize;i++) |
---|
767 | stddev += (tempArray[i]-mean)*(tempArray[i]-mean); |
---|
768 | stddev = sqrt(stddev/float(goodSize-1)); |
---|
769 | this->Stats.setStddev(stddev); |
---|
770 | |
---|
771 | for(int i=0;i<goodSize;i++)// tempArray[i] = absval(tempArray[i]-median); |
---|
772 | { |
---|
773 | if(tempArray[i]>median) tempArray[i] -= median; |
---|
774 | else tempArray[i] = median - tempArray[i]; |
---|
775 | } |
---|
776 | std::sort(tempArray,tempArray+goodSize); |
---|
777 | if((goodSize%2)==0) |
---|
778 | madfm = (tempArray[goodSize/2-1]+tempArray[goodSize/2])/2; |
---|
779 | else madfm = tempArray[goodSize/2]; |
---|
780 | this->Stats.setMadfm(madfm); |
---|
781 | } |
---|
782 | else{ |
---|
783 | // just get mean & median from orig array, and rms & madfm from residual |
---|
784 | // recompute array values to be residuals & then find stddev & madfm |
---|
785 | goodSize = 0; |
---|
786 | for(int p=0;p<xysize;p++){ |
---|
787 | for(int z=0;z<this->axisDim[2];z++){ |
---|
788 | vox = z * xysize + p; |
---|
789 | if(!this->isBlank(vox) && !this->par.isInMW(z)){ |
---|
790 | tempArray[goodSize] = this->array[vox] - this->recon[vox]; |
---|
791 | goodSize++; |
---|
792 | } |
---|
793 | } |
---|
794 | } |
---|
795 | mean = tempArray[0]; |
---|
796 | for(int i=1;i<goodSize;i++) mean += tempArray[i]; |
---|
797 | mean /= float(goodSize); |
---|
798 | stddev = (tempArray[0]-mean) * (tempArray[0]-mean); |
---|
799 | for(int i=1;i<goodSize;i++) |
---|
800 | stddev += (tempArray[i]-mean)*(tempArray[i]-mean); |
---|
801 | stddev = sqrt(stddev/float(goodSize-1)); |
---|
802 | this->Stats.setStddev(stddev); |
---|
803 | |
---|
804 | std::sort(tempArray,tempArray+goodSize); |
---|
805 | if((goodSize%2)==0) |
---|
806 | median = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
807 | else median = tempArray[goodSize/2]; |
---|
808 | for(int i=0;i<goodSize;i++){ |
---|
809 | if(tempArray[i]>median) tempArray[i] = tempArray[i]-median; |
---|
810 | else tempArray[i] = median - tempArray[i]; |
---|
811 | } |
---|
812 | std::sort(tempArray,tempArray+goodSize); |
---|
813 | if((goodSize%2)==0) |
---|
814 | madfm = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
815 | else madfm = tempArray[goodSize/2]; |
---|
816 | this->Stats.setMadfm(madfm); |
---|
817 | } |
---|
818 | |
---|
819 | delete [] tempArray; |
---|
820 | |
---|
821 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
822 | // If the FDR method has been requested |
---|
823 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
824 | else{ |
---|
825 | // otherwise, calculate threshold based on the requested SNR cut level, |
---|
826 | // and then set the threshold parameter in the Par set. |
---|
827 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
828 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
829 | } |
---|
830 | |
---|
831 | } |
---|
832 | |
---|
833 | std::cout << "Using "; |
---|
834 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
835 | std::cout << "flux threshold of: "; |
---|
836 | float thresh = this->Stats.getThreshold(); |
---|
837 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
838 | std::cout << thresh << std::endl; |
---|
839 | |
---|
840 | } |
---|
841 | //-------------------------------------------------------------------- |
---|
842 | |
---|
843 | int Cube::setupFDR() |
---|
844 | { |
---|
845 | /** |
---|
846 | * Determines the critical Probability value for the False Discovery Rate |
---|
847 | * detection routine. All pixels with Prob less than this value will |
---|
848 | * be considered detections. |
---|
849 | * |
---|
850 | * The Prob here is the probability, assuming a Normal distribution, of |
---|
851 | * obtaining a value as high or higher than the pixel value (ie. only the |
---|
852 | * positive tail of the PDF) |
---|
853 | */ |
---|
854 | |
---|
855 | // first calculate p-value for each pixel -- assume Gaussian for now. |
---|
856 | |
---|
857 | float *orderedP = new float[this->numPixels]; |
---|
858 | int count = 0; |
---|
859 | float zStat; |
---|
860 | for(int pix=0; pix<this->numPixels; pix++){ |
---|
861 | |
---|
862 | if( !(this->par.isBlank(this->array[pix])) ){ |
---|
863 | // only look at non-blank pixels |
---|
864 | zStat = (this->array[pix] - this->Stats.getMiddle()) / |
---|
865 | this->Stats.getSpread(); |
---|
866 | |
---|
867 | orderedP[count++] = 0.5 * erfc(zStat/M_SQRT2); |
---|
868 | // Need the factor of 0.5 here, as we are only considering the positive |
---|
869 | // tail of the distribution. Don't care about negative detections. |
---|
870 | } |
---|
871 | } |
---|
872 | |
---|
873 | // now order them |
---|
874 | std::sort(orderedP,orderedP+count); |
---|
875 | |
---|
876 | // now find the maximum P value. |
---|
877 | int max = 0; |
---|
878 | float cN = 0.; |
---|
879 | int psfCtr; |
---|
880 | int numVox = int(this->par.getBeamSize()) * 2; |
---|
881 | // why beamSize*2? we are doing this in 3D, so spectrally assume just the |
---|
882 | // neighbouring channels are correlated, but spatially all those within |
---|
883 | // the beam, so total number of voxels is 2*beamSize |
---|
884 | for(psfCtr=1;psfCtr<=numVox;(psfCtr)++) |
---|
885 | cN += 1./float(psfCtr); |
---|
886 | |
---|
887 | for(int loopCtr=0;loopCtr<count;loopCtr++) { |
---|
888 | if( orderedP[loopCtr] < |
---|
889 | (double(loopCtr+1)*this->par.getAlpha()/(cN * double(count))) ) { |
---|
890 | max = loopCtr; |
---|
891 | } |
---|
892 | } |
---|
893 | |
---|
894 | this->Stats.setPThreshold( orderedP[max] ); |
---|
895 | |
---|
896 | delete [] orderedP; |
---|
897 | |
---|
898 | // Find real value of the P threshold by finding the inverse of the |
---|
899 | // error function -- root finding with brute force technique |
---|
900 | // (relatively slow, but we only do it once). |
---|
901 | zStat = 0; |
---|
902 | float deltaZ = 0.1; |
---|
903 | float tolerance = 1.e-6; |
---|
904 | float zeroP = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
905 | do{ |
---|
906 | zStat+=deltaZ; |
---|
907 | if((zeroP * (erfc(zStat/M_SQRT2)-this->Stats.getPThreshold()))<0.){ |
---|
908 | zStat-=deltaZ; |
---|
909 | deltaZ/=2.; |
---|
910 | } |
---|
911 | }while(deltaZ>tolerance); |
---|
912 | this->Stats.setThreshold( zStat*this->Stats.getSpread() + |
---|
913 | this->Stats.getMiddle() ); |
---|
914 | |
---|
915 | } |
---|
916 | //-------------------------------------------------------------------- |
---|
917 | |
---|
918 | bool Cube::isDetection(long x, long y, long z) |
---|
919 | { |
---|
920 | /** |
---|
921 | * Is a given voxel at position (x,y,z) a detection, based on the statistics |
---|
922 | * in the Cube's StatsContainer? |
---|
923 | * If the pixel lies outside the valid range for the data array, return false. |
---|
924 | * \param x X-value of the Cube's voxel to be tested. |
---|
925 | * \param y Y-value of the Cube's voxel to be tested. |
---|
926 | * \param z Z-value of the Cube's voxel to be tested. |
---|
927 | */ |
---|
928 | long voxel = z*axisDim[0]*axisDim[1] + y*axisDim[0] + x; |
---|
929 | return DataArray::isDetection(array[voxel]); |
---|
930 | }; |
---|
931 | //-------------------------------------------------------------------- |
---|
932 | |
---|
933 | void Cube::calcObjectWCSparams() |
---|
934 | { |
---|
935 | /** |
---|
936 | * A function that calculates the WCS parameters for each object in the |
---|
937 | * Cube's list of detections. |
---|
938 | * Each object gets an ID number assigned to it (which is simply its order |
---|
939 | * in the list), and if the WCS is good, the WCS paramters are calculated. |
---|
940 | */ |
---|
941 | |
---|
942 | for(int i=0;i<this->objectList.size();i++){ |
---|
943 | this->objectList[i].setID(i+1); |
---|
944 | this->objectList[i].calcWCSparams(this->head); |
---|
945 | this->objectList[i].setPeakSNR( (this->objectList[i].getPeakFlux() - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
946 | } |
---|
947 | |
---|
948 | if(!this->head.isWCS()){ |
---|
949 | // if the WCS is bad, set the object names to Obj01 etc |
---|
950 | int numspaces = int(log10(this->objectList.size())) + 1; |
---|
951 | stringstream ss; |
---|
952 | for(int i=0;i<this->objectList.size();i++){ |
---|
953 | ss.str(""); |
---|
954 | ss << "Obj" << std::setfill('0') << std::setw(numspaces) << i+1; |
---|
955 | this->objectList[i].setName(ss.str()); |
---|
956 | } |
---|
957 | } |
---|
958 | |
---|
959 | } |
---|
960 | //-------------------------------------------------------------------- |
---|
961 | |
---|
962 | void Cube::sortDetections() |
---|
963 | { |
---|
964 | /** |
---|
965 | * A front end to the sort-by functions. |
---|
966 | * If there is a good WCS, the detection list is sorted by velocity. |
---|
967 | * Otherwise, it is sorted by increasing z-pixel value. |
---|
968 | * The ID numbers are then re-calculated. |
---|
969 | */ |
---|
970 | |
---|
971 | if(this->head.isWCS()) SortByVel(this->objectList); |
---|
972 | else SortByZ(this->objectList); |
---|
973 | for(int i=0; i<this->objectList.size();i++) this->objectList[i].setID(i+1); |
---|
974 | |
---|
975 | } |
---|
976 | //-------------------------------------------------------------------- |
---|
977 | |
---|
978 | void Cube::updateDetectMap() |
---|
979 | { |
---|
980 | /** |
---|
981 | * A function that, for each detected object in the cube's list, increments |
---|
982 | * the cube's detection map by the required amount at each pixel. |
---|
983 | */ |
---|
984 | |
---|
985 | for(int obj=0;obj<this->objectList.size();obj++){ |
---|
986 | for(int pix=0;pix<this->objectList[obj].getSize();pix++) { |
---|
987 | int spatialPos = this->objectList[obj].getX(pix)+ |
---|
988 | this->objectList[obj].getY(pix)*this->axisDim[0]; |
---|
989 | this->detectMap[spatialPos]++; |
---|
990 | } |
---|
991 | } |
---|
992 | } |
---|
993 | //-------------------------------------------------------------------- |
---|
994 | |
---|
995 | void Cube::updateDetectMap(Detection obj) |
---|
996 | { |
---|
997 | /** |
---|
998 | * A function that, for the given object, increments the cube's |
---|
999 | * detection map by the required amount at each pixel. |
---|
1000 | * |
---|
1001 | * \param obj A Detection object that is being incorporated into the map. |
---|
1002 | */ |
---|
1003 | for(int pix=0;pix<obj.getSize();pix++) { |
---|
1004 | int spatialPos = obj.getX(pix)+obj.getY(pix)*this->axisDim[0]; |
---|
1005 | this->detectMap[spatialPos]++; |
---|
1006 | } |
---|
1007 | } |
---|
1008 | //-------------------------------------------------------------------- |
---|
1009 | |
---|
1010 | float Cube::enclosedFlux(Detection obj) |
---|
1011 | { |
---|
1012 | /** |
---|
1013 | * A function to calculate the flux enclosed by the range |
---|
1014 | * of pixels detected in the object obj (not necessarily all |
---|
1015 | * pixels will have been detected). |
---|
1016 | * |
---|
1017 | * \param obj The Detection under consideration. |
---|
1018 | */ |
---|
1019 | obj.calcParams(); |
---|
1020 | int xsize = obj.getXmax()-obj.getXmin()+1; |
---|
1021 | int ysize = obj.getYmax()-obj.getYmin()+1; |
---|
1022 | int zsize = obj.getZmax()-obj.getZmin()+1; |
---|
1023 | vector <float> fluxArray(xsize*ysize*zsize,0.); |
---|
1024 | for(int x=0;x<xsize;x++){ |
---|
1025 | for(int y=0;y<ysize;y++){ |
---|
1026 | for(int z=0;z<zsize;z++){ |
---|
1027 | fluxArray[x+y*xsize+z*ysize*xsize] = |
---|
1028 | this->getPixValue(x+obj.getXmin(), |
---|
1029 | y+obj.getYmin(), |
---|
1030 | z+obj.getZmin()); |
---|
1031 | if(this->par.getFlagNegative()) |
---|
1032 | fluxArray[x+y*xsize+z*ysize*xsize] *= -1.; |
---|
1033 | } |
---|
1034 | } |
---|
1035 | } |
---|
1036 | float sum = 0.; |
---|
1037 | for(int i=0;i<fluxArray.size();i++) |
---|
1038 | if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i]; |
---|
1039 | return sum; |
---|
1040 | } |
---|
1041 | //-------------------------------------------------------------------- |
---|
1042 | |
---|
1043 | void Cube::setupColumns() |
---|
1044 | { |
---|
1045 | /** |
---|
1046 | * A front-end to the two setup routines in columns.cc. |
---|
1047 | * This first calculates the WCS parameters for all objects, then |
---|
1048 | * sets up the columns (calculates their widths and precisions and so on). |
---|
1049 | * The precisions are also stored in each Detection object. |
---|
1050 | */ |
---|
1051 | this->calcObjectWCSparams(); |
---|
1052 | // need this as the colSet functions use vel, RA, Dec, etc... |
---|
1053 | |
---|
1054 | this->fullCols.clear(); |
---|
1055 | this->fullCols = getFullColSet(this->objectList, this->head); |
---|
1056 | |
---|
1057 | this->logCols.clear(); |
---|
1058 | this->logCols = getLogColSet(this->objectList, this->head); |
---|
1059 | |
---|
1060 | int vel,fpeak,fint,pos,xyz,temp,snr; |
---|
1061 | vel = fullCols[VEL].getPrecision(); |
---|
1062 | fpeak = fullCols[FPEAK].getPrecision(); |
---|
1063 | snr = fullCols[SNRPEAK].getPrecision(); |
---|
1064 | xyz = fullCols[X].getPrecision(); |
---|
1065 | if(temp=fullCols[Y].getPrecision() > xyz) xyz = temp; |
---|
1066 | if(temp=fullCols[Z].getPrecision() > xyz) xyz = temp; |
---|
1067 | if(this->head.isWCS()) fint = fullCols[FINT].getPrecision(); |
---|
1068 | else fint = fullCols[FTOT].getPrecision(); |
---|
1069 | pos = fullCols[WRA].getPrecision(); |
---|
1070 | if(temp=fullCols[WDEC].getPrecision() > pos) pos = temp; |
---|
1071 | |
---|
1072 | for(int obj=0;obj<this->objectList.size();obj++){ |
---|
1073 | this->objectList[obj].setVelPrec(vel); |
---|
1074 | this->objectList[obj].setFpeakPrec(fpeak); |
---|
1075 | this->objectList[obj].setXYZPrec(xyz); |
---|
1076 | this->objectList[obj].setPosPrec(pos); |
---|
1077 | this->objectList[obj].setFintPrec(fint); |
---|
1078 | this->objectList[obj].setSNRPrec(snr); |
---|
1079 | } |
---|
1080 | |
---|
1081 | } |
---|
1082 | //-------------------------------------------------------------------- |
---|
1083 | |
---|
1084 | bool Cube::objAtSpatialEdge(Detection obj) |
---|
1085 | { |
---|
1086 | /** |
---|
1087 | * A function to test whether the object obj |
---|
1088 | * lies at the edge of the cube's spatial field -- |
---|
1089 | * either at the boundary, or next to BLANKs. |
---|
1090 | * |
---|
1091 | * /param obj The Detection under consideration. |
---|
1092 | */ |
---|
1093 | |
---|
1094 | bool atEdge = false; |
---|
1095 | |
---|
1096 | int pix = 0; |
---|
1097 | while(!atEdge && pix<obj.getSize()){ |
---|
1098 | // loop over each pixel in the object, until we find an edge pixel. |
---|
1099 | Voxel vox = obj.getPixel(pix); |
---|
1100 | for(int dx=-1;dx<=1;dx+=2){ |
---|
1101 | if(((vox.getX()+dx)<0) || ((vox.getX()+dx)>=this->axisDim[0])) |
---|
1102 | atEdge = true; |
---|
1103 | else if(this->isBlank(vox.getX()+dx,vox.getY(),vox.getZ())) |
---|
1104 | atEdge = true; |
---|
1105 | } |
---|
1106 | for(int dy=-1;dy<=1;dy+=2){ |
---|
1107 | if(((vox.getY()+dy)<0) || ((vox.getY()+dy)>=this->axisDim[1])) |
---|
1108 | atEdge = true; |
---|
1109 | else if(this->isBlank(vox.getX(),vox.getY()+dy,vox.getZ())) |
---|
1110 | atEdge = true; |
---|
1111 | } |
---|
1112 | pix++; |
---|
1113 | } |
---|
1114 | |
---|
1115 | return atEdge; |
---|
1116 | } |
---|
1117 | //-------------------------------------------------------------------- |
---|
1118 | |
---|
1119 | bool Cube::objAtSpectralEdge(Detection obj) |
---|
1120 | { |
---|
1121 | /** |
---|
1122 | * A function to test whether the object obj |
---|
1123 | * lies at the edge of the cube's spectral extent -- |
---|
1124 | * either at the boundary, or next to BLANKs. |
---|
1125 | * |
---|
1126 | * /param obj The Detection under consideration. |
---|
1127 | */ |
---|
1128 | |
---|
1129 | bool atEdge = false; |
---|
1130 | |
---|
1131 | int pix = 0; |
---|
1132 | while(!atEdge && pix<obj.getSize()){ |
---|
1133 | // loop over each pixel in the object, until we find an edge pixel. |
---|
1134 | Voxel vox = obj.getPixel(pix); |
---|
1135 | for(int dz=-1;dz<=1;dz+=2){ |
---|
1136 | if(((vox.getZ()+dz)<0) || ((vox.getZ()+dz)>=this->axisDim[2])) |
---|
1137 | atEdge = true; |
---|
1138 | else if(this->isBlank(vox.getX(),vox.getY(),vox.getZ()+dz)) |
---|
1139 | atEdge = true; |
---|
1140 | } |
---|
1141 | pix++; |
---|
1142 | } |
---|
1143 | |
---|
1144 | return atEdge; |
---|
1145 | } |
---|
1146 | //-------------------------------------------------------------------- |
---|
1147 | |
---|
1148 | void Cube::setObjectFlags() |
---|
1149 | { |
---|
1150 | /** |
---|
1151 | * A function to set any warning flags for all the detected objects |
---|
1152 | * associated with the cube. |
---|
1153 | * Flags to be looked for: |
---|
1154 | * <ul><li> Negative enclosed flux (N) |
---|
1155 | * <li> Detection at edge of field (spatially) (E) |
---|
1156 | * <li> Detection at edge of spectral region (S) |
---|
1157 | * </ul> |
---|
1158 | */ |
---|
1159 | |
---|
1160 | for(int i=0;i<this->objectList.size();i++){ |
---|
1161 | |
---|
1162 | if( this->enclosedFlux(this->objectList[i]) < 0. ) |
---|
1163 | this->objectList[i].addToFlagText("N"); |
---|
1164 | |
---|
1165 | if( this->objAtSpatialEdge(this->objectList[i]) ) |
---|
1166 | this->objectList[i].addToFlagText("E"); |
---|
1167 | |
---|
1168 | if( this->objAtSpectralEdge(this->objectList[i]) ) |
---|
1169 | this->objectList[i].addToFlagText("S"); |
---|
1170 | |
---|
1171 | } |
---|
1172 | |
---|
1173 | } |
---|
1174 | //-------------------------------------------------------------------- |
---|
1175 | |
---|
1176 | void Cube::plotBlankEdges() |
---|
1177 | { |
---|
1178 | /** |
---|
1179 | * A front end to the drawBlankEdges() function. This draws the lines |
---|
1180 | * indicating the extent of the non-BLANK region of the cube in the |
---|
1181 | * PGPLOT colour MAGENTA (from the namespace mycpgplot), using the Cube's |
---|
1182 | * arrays and dimensions. |
---|
1183 | * |
---|
1184 | * Note that a PGPLOT device needs to be open. This is only done if the |
---|
1185 | * appropriate Param parameter is set. |
---|
1186 | */ |
---|
1187 | if(this->par.drawBlankEdge()){ |
---|
1188 | int colour; |
---|
1189 | cpgqci(&colour); |
---|
1190 | cpgsci(MAGENTA); |
---|
1191 | drawBlankEdges(this->array,this->axisDim[0],this->axisDim[1],this->par); |
---|
1192 | cpgsci(colour); |
---|
1193 | } |
---|
1194 | } |
---|
1195 | //-------------------------------------------------------------------- |
---|
1196 | |
---|
1197 | |
---|
1198 | |
---|
1199 | /****************************************************************/ |
---|
1200 | ///////////////////////////////////////////////////////////// |
---|
1201 | //// Functions for Image class |
---|
1202 | ///////////////////////////////////////////////////////////// |
---|
1203 | |
---|
1204 | Image::Image(long size){ |
---|
1205 | // need error handling in case size<0 !!! |
---|
1206 | this->numPixels = this->numDim = 0; |
---|
1207 | if(size<0) |
---|
1208 | duchampError("Image(size)","Negative size -- could not define Image"); |
---|
1209 | else{ |
---|
1210 | if(size>0) this->array = new float[size]; |
---|
1211 | this->numPixels = size; |
---|
1212 | this->axisDim = new long[2]; |
---|
1213 | this->numDim = 2; |
---|
1214 | } |
---|
1215 | } |
---|
1216 | //-------------------------------------------------------------------- |
---|
1217 | |
---|
1218 | Image::Image(long *dimensions){ |
---|
1219 | this->numPixels = this->numDim = 0; |
---|
1220 | int size = dimensions[0] * dimensions[1]; |
---|
1221 | if(size<0) |
---|
1222 | duchampError("Image(dimArray)","Negative size -- could not define Image"); |
---|
1223 | else{ |
---|
1224 | this->numPixels = size; |
---|
1225 | if(size>0) this->array = new float[size]; |
---|
1226 | this->numDim=2; |
---|
1227 | this->axisDim = new long[2]; |
---|
1228 | for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i]; |
---|
1229 | } |
---|
1230 | } |
---|
1231 | //-------------------------------------------------------------------- |
---|
1232 | //-------------------------------------------------------------------- |
---|
1233 | |
---|
1234 | void Image::saveArray(float *input, long size){ |
---|
1235 | if(size != this->numPixels) |
---|
1236 | duchampError("Image::saveArray", |
---|
1237 | "Input array different size to existing array. Cannot save."); |
---|
1238 | else { |
---|
1239 | if(this->numPixels>0) delete [] array; |
---|
1240 | this->numPixels = size; |
---|
1241 | if(this->numPixels>0) this->array = new float[size]; |
---|
1242 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
---|
1243 | } |
---|
1244 | } |
---|
1245 | //-------------------------------------------------------------------- |
---|
1246 | |
---|
1247 | void Image::extractSpectrum(float *Array, long *dim, long pixel) |
---|
1248 | { |
---|
1249 | /** |
---|
1250 | * Image::extractSpectrum(float *, long *, int) |
---|
1251 | * A function to extract a 1-D spectrum from a 3-D array. |
---|
1252 | * The array is assumed to be 3-D with the third dimension the spectral one. |
---|
1253 | * The dimensions of the array are in the dim[] array. |
---|
1254 | * The spectrum extracted is the one lying in the spatial pixel referenced |
---|
1255 | * by the third argument. |
---|
1256 | */ |
---|
1257 | float *spec = new float[dim[2]]; |
---|
1258 | for(int z=0;z<dim[2];z++) spec[z] = Array[z*dim[0]*dim[1] + pixel]; |
---|
1259 | this->saveArray(spec,dim[2]); |
---|
1260 | delete [] spec; |
---|
1261 | } |
---|
1262 | //-------------------------------------------------------------------- |
---|
1263 | |
---|
1264 | void Image::extractSpectrum(Cube &cube, long pixel) |
---|
1265 | { |
---|
1266 | /** |
---|
1267 | * Image::extractSpectrum(Cube &, int) |
---|
1268 | * A function to extract a 1-D spectrum from a Cube class |
---|
1269 | * The spectrum extracted is the one lying in the spatial pixel referenced |
---|
1270 | * by the second argument. |
---|
1271 | */ |
---|
1272 | long zdim = cube.getDimZ(); |
---|
1273 | long spatSize = cube.getDimX()*cube.getDimY(); |
---|
1274 | float *spec = new float[zdim]; |
---|
1275 | for(int z=0;z<zdim;z++) spec[z] = cube.getPixValue(z*spatSize + pixel); |
---|
1276 | this->saveArray(spec,zdim); |
---|
1277 | delete [] spec; |
---|
1278 | } |
---|
1279 | //-------------------------------------------------------------------- |
---|
1280 | |
---|
1281 | void Image::extractImage(float *Array, long *dim, long channel) |
---|
1282 | { |
---|
1283 | /** |
---|
1284 | * Image::extractImage(float *, long *, int) |
---|
1285 | * A function to extract a 2-D image from a 3-D array. |
---|
1286 | * The array is assumed to be 3-D with the third dimension the spectral one. |
---|
1287 | * The dimensions of the array are in the dim[] array. |
---|
1288 | * The image extracted is the one lying in the channel referenced |
---|
1289 | * by the third argument. |
---|
1290 | */ |
---|
1291 | float *image = new float[dim[0]*dim[1]]; |
---|
1292 | for(int npix=0; npix<dim[0]*dim[1]; npix++){ |
---|
1293 | image[npix] = Array[channel*dim[0]*dim[1] + npix]; |
---|
1294 | } |
---|
1295 | this->saveArray(image,dim[0]*dim[1]); |
---|
1296 | delete [] image; |
---|
1297 | } |
---|
1298 | //-------------------------------------------------------------------- |
---|
1299 | |
---|
1300 | void Image::extractImage(Cube &cube, long channel) |
---|
1301 | { |
---|
1302 | /** |
---|
1303 | * Image::extractImage(Cube &, int) |
---|
1304 | * A function to extract a 2-D image from Cube class. |
---|
1305 | * The image extracted is the one lying in the channel referenced |
---|
1306 | * by the second argument. |
---|
1307 | */ |
---|
1308 | long spatSize = cube.getDimX()*cube.getDimY(); |
---|
1309 | float *image = new float[spatSize]; |
---|
1310 | for(int npix=0; npix<spatSize; npix++) |
---|
1311 | image[npix] = cube.getPixValue(channel*spatSize + npix); |
---|
1312 | this->saveArray(image,spatSize); |
---|
1313 | delete [] image; |
---|
1314 | } |
---|
1315 | //-------------------------------------------------------------------- |
---|
1316 | |
---|
1317 | void Image::removeMW() |
---|
1318 | { |
---|
1319 | /** |
---|
1320 | * Image::removeMW() |
---|
1321 | * A function to remove the Milky Way range of channels from a 1-D spectrum. |
---|
1322 | * The array in this Image is assumed to be 1-D, with only the first axisDim |
---|
1323 | * equal to 1. |
---|
1324 | * The values of the MW channels are set to 0, unless they are BLANK. |
---|
1325 | */ |
---|
1326 | if(this->par.getFlagMW() && (this->axisDim[1]==1) ){ |
---|
1327 | for(int z=0;z<this->axisDim[0];z++){ |
---|
1328 | if(!this->isBlank(z) && this->par.isInMW(z)) this->array[z]=0.; |
---|
1329 | } |
---|
1330 | } |
---|
1331 | } |
---|
1332 | |
---|