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(short int nDim, long size){ |
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29 | |
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30 | if(size<0) |
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31 | duchampError("DataArray(nDim,size)", |
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32 | "Negative size -- could not define DataArray"); |
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33 | else if(nDim<0) |
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34 | duchampError("DataArray(nDim,size)", |
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35 | "Negative number of dimensions: could not define DataArray"); |
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36 | else { |
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37 | if(size>0) this->array = new float[size]; |
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38 | this->numPixels = size; |
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39 | if(nDim>0) this->axisDim = new long[nDim]; |
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40 | this->numDim = nDim; |
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41 | } |
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42 | } |
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43 | //-------------------------------------------------------------------- |
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44 | |
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45 | DataArray::DataArray(short int nDim, long *dimensions){ |
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46 | if(nDim<0) |
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47 | duchampError("DataArray(nDim,dimArray)", |
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48 | "Negative number of dimensions: could not define DataArray"); |
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49 | else { |
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50 | int size = dimensions[0]; |
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51 | for(int i=1;i<nDim;i++) size *= dimensions[i]; |
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52 | if(size<0) |
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53 | duchampError("DataArray(nDim,dimArray)", |
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54 | "Negative size: could not define DataArray"); |
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55 | else{ |
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56 | this->numPixels = size; |
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57 | if(size>0) this->array = new float[size]; |
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58 | this->numDim=nDim; |
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59 | if(nDim>0) this->axisDim = new long[nDim]; |
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60 | for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i]; |
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61 | } |
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62 | } |
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63 | } |
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64 | //-------------------------------------------------------------------- |
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65 | |
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66 | DataArray::~DataArray() |
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67 | { |
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68 | delete [] this->array; |
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69 | delete [] this->axisDim; |
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70 | this->objectList.clear(); |
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71 | } |
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72 | //-------------------------------------------------------------------- |
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73 | |
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74 | void DataArray::getDimArray(long *output){ |
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75 | for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i]; |
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76 | } |
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77 | //-------------------------------------------------------------------- |
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78 | |
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79 | void DataArray::getArray(float *output){ |
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80 | for(int i=0;i<this->numPixels;i++) output[i] = this->array[i]; |
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81 | } |
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82 | //-------------------------------------------------------------------- |
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83 | |
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84 | void DataArray::saveArray(float *input, long size){ |
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85 | if(size != this->numPixels) |
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86 | duchampError("DataArray::saveArray", |
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87 | "Input array different size to existing array. Cannot save."); |
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88 | else { |
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89 | if(this->numPixels>0) delete [] this->array; |
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90 | this->numPixels = size; |
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91 | this->array = new float[size]; |
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92 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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93 | } |
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94 | } |
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95 | //-------------------------------------------------------------------- |
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96 | |
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97 | void DataArray::getDim(long &x, long &y, long &z){ |
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98 | if(numDim>0) x=axisDim[0]; |
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99 | else x=0; |
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100 | if(numDim>1) y=axisDim[1]; |
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101 | else y=0; |
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102 | if(numDim>2) z=axisDim[2]; |
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103 | else z=0; |
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104 | } |
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105 | //-------------------------------------------------------------------- |
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106 | |
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107 | void DataArray::addObject(Detection object){ |
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108 | // adds a single detection to the object list |
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109 | // objectList is a vector, so just use push_back() |
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110 | this->objectList.push_back(object); |
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111 | } |
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112 | //-------------------------------------------------------------------- |
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113 | |
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114 | void DataArray::addObjectList(vector <Detection> newlist) { |
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115 | for(int i=0;i<newlist.size();i++) this->objectList.push_back(newlist[i]); |
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116 | } |
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117 | //-------------------------------------------------------------------- |
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118 | |
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119 | void DataArray::addObjectOffsets(){ |
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120 | for(int i=0;i<this->objectList.size();i++){ |
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121 | for(int p=0;p<this->objectList[i].getSize();p++){ |
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122 | this->objectList[i].setX(p,this->objectList[i].getX(p)+ |
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123 | this->par.getXOffset()); |
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124 | this->objectList[i].setY(p,this->objectList[i].getY(p)+ |
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125 | this->par.getYOffset()); |
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126 | this->objectList[i].setZ(p,this->objectList[i].getZ(p)+ |
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127 | this->par.getZOffset()); |
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128 | } |
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129 | } |
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130 | } |
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131 | //-------------------------------------------------------------------- |
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132 | |
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133 | std::ostream& operator<< ( std::ostream& theStream, DataArray &array) |
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134 | { |
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135 | for(int i=0;i<array.numDim;i++){ |
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136 | if(i>0) theStream<<"x"; |
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137 | theStream<<array.axisDim[i]; |
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138 | } |
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139 | theStream<<std::endl; |
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140 | theStream<<array.objectList.size()<<" detections:\n--------------\n"; |
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141 | for(int i=0;i<array.objectList.size();i++){ |
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142 | theStream << "Detection #" << array.objectList[i].getID()<<std::endl; |
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143 | Detection *obj = new Detection; |
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144 | *obj = array.objectList[i]; |
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145 | for(int j=0;j<obj->getSize();j++){ |
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146 | obj->setX(j,obj->getX(j)+obj->getXOffset()); |
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147 | obj->setY(j,obj->getY(j)+obj->getYOffset()); |
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148 | obj->setZ(j,obj->getZ(j)+obj->getZOffset()); |
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149 | } |
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150 | theStream<<*obj; |
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151 | delete obj; |
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152 | } |
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153 | theStream<<"--------------\n"; |
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154 | } |
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155 | |
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156 | /****************************************************************/ |
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157 | ///////////////////////////////////////////////////////////// |
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158 | //// Functions for Image class |
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159 | ///////////////////////////////////////////////////////////// |
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160 | |
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161 | Image::Image(long size){ |
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162 | // need error handling in case size<0 !!! |
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163 | if(size<0) |
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164 | duchampError("Image(size)","Negative size -- could not define Image"); |
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165 | else{ |
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166 | if(size>0) this->array = new float[size]; |
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167 | this->numPixels = size; |
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168 | this->axisDim = new long[2]; |
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169 | this->numDim = 2; |
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170 | } |
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171 | } |
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172 | //-------------------------------------------------------------------- |
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173 | |
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174 | Image::Image(long *dimensions){ |
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175 | int size = dimensions[0] * dimensions[1]; |
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176 | if(size<0) |
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177 | duchampError("Image(dimArray)","Negative size -- could not define Image"); |
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178 | else{ |
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179 | this->numPixels = size; |
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180 | if(size>0) this->array = new float[size]; |
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181 | this->numDim=2; |
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182 | this->axisDim = new long[2]; |
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183 | for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i]; |
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184 | } |
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185 | } |
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186 | //-------------------------------------------------------------------- |
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187 | //-------------------------------------------------------------------- |
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188 | |
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189 | void Image::saveArray(float *input, long size){ |
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190 | if(size != this->numPixels) |
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191 | duchampError("Image::saveArray", |
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192 | "Input array different size to existing array. Cannot save."); |
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193 | else { |
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194 | if(this->numPixels>0) delete [] array; |
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195 | this->numPixels = size; |
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196 | if(this->numPixels>0) this->array = new float[size]; |
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197 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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198 | } |
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199 | } |
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200 | //-------------------------------------------------------------------- |
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201 | |
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202 | void Image::extractSpectrum(float *Array, long *dim, long pixel) |
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203 | { |
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204 | /** |
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205 | * Image::extractSpectrum(float *, long *, int) |
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206 | * A function to extract a 1-D spectrum from a 3-D array. |
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207 | * The array is assumed to be 3-D with the third dimension the spectral one. |
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208 | * The dimensions of the array are in the dim[] array. |
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209 | * The spectrum extracted is the one lying in the spatial pixel referenced |
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210 | * by the third argument. |
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211 | */ |
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212 | float *spec = new float[dim[2]]; |
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213 | for(int z=0;z<dim[2];z++) spec[z] = Array[z*dim[0]*dim[1] + pixel]; |
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214 | this->saveArray(spec,dim[2]); |
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215 | delete [] spec; |
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216 | } |
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217 | //-------------------------------------------------------------------- |
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218 | |
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219 | void Image::extractSpectrum(Cube &cube, long pixel) |
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220 | { |
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221 | /** |
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222 | * Image::extractSpectrum(Cube &, int) |
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223 | * A function to extract a 1-D spectrum from a Cube class |
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224 | * The spectrum extracted is the one lying in the spatial pixel referenced |
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225 | * by the second argument. |
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226 | */ |
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227 | long zdim = cube.getDimZ(); |
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228 | long spatSize = cube.getDimX()*cube.getDimY(); |
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229 | float *spec = new float[zdim]; |
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230 | for(int z=0;z<zdim;z++) spec[z] = cube.getPixValue(z*spatSize + pixel); |
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231 | this->saveArray(spec,zdim); |
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232 | delete [] spec; |
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233 | } |
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234 | //-------------------------------------------------------------------- |
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235 | |
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236 | void Image::extractImage(float *Array, long *dim, long channel) |
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237 | { |
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238 | /** |
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239 | * Image::extractImage(float *, long *, int) |
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240 | * A function to extract a 2-D image from a 3-D array. |
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241 | * The array is assumed to be 3-D with the third dimension the spectral one. |
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242 | * The dimensions of the array are in the dim[] array. |
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243 | * The image extracted is the one lying in the channel referenced |
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244 | * by the third argument. |
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245 | */ |
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246 | float *image = new float[dim[0]*dim[1]]; |
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247 | for(int npix=0; npix<dim[0]*dim[1]; npix++){ |
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248 | image[npix] = Array[channel*dim[0]*dim[1] + npix]; |
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249 | } |
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250 | this->saveArray(image,dim[0]*dim[1]); |
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251 | delete [] image; |
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252 | } |
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253 | //-------------------------------------------------------------------- |
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254 | |
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255 | void Image::extractImage(Cube &cube, long channel) |
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256 | { |
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257 | /** |
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258 | * Image::extractImage(Cube &, int) |
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259 | * A function to extract a 2-D image from Cube class. |
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260 | * The image extracted is the one lying in the channel referenced |
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261 | * by the second argument. |
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262 | */ |
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263 | long spatSize = cube.getDimX()*cube.getDimY(); |
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264 | float *image = new float[spatSize]; |
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265 | for(int npix=0; npix<spatSize; npix++) |
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266 | image[npix] = cube.getPixValue(channel*spatSize + npix); |
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267 | this->saveArray(image,spatSize); |
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268 | delete [] image; |
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269 | } |
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270 | //-------------------------------------------------------------------- |
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271 | |
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272 | void Image::removeMW() |
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273 | { |
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274 | /** |
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275 | * Image::removeMW() |
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276 | * A function to remove the Milky Way range of channels from a 1-D spectrum. |
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277 | * The array in this Image is assumed to be 1-D, with only the first axisDim |
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278 | * equal to 1. |
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279 | * The values of the MW channels are set to 0, unless they are BLANK. |
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280 | */ |
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281 | if(this->par.getFlagMW() && (this->axisDim[1]==1) ){ |
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282 | for(int z=0;z<this->axisDim[0];z++){ |
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283 | if(!this->isBlank(z) && this->par.isInMW(z)) this->array[z]=0.; |
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284 | } |
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285 | } |
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286 | } |
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287 | |
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288 | /****************************************************************/ |
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289 | ///////////////////////////////////////////////////////////// |
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290 | //// Functions for Cube class |
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291 | ///////////////////////////////////////////////////////////// |
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292 | |
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293 | Cube::Cube(long size){ |
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294 | // need error handling in case size<0 !!! |
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295 | this->reconAllocated = false; |
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296 | this->baselineAllocated = false; |
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297 | if(size<0) |
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298 | duchampError("Cube(size)","Negative size -- could not define Cube"); |
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299 | else{ |
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300 | if(size>0){ |
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301 | this->array = new float[size]; |
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302 | this->recon = new float[size]; |
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303 | this->reconAllocated = true; |
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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 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
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315 | int imsize = dimensions[0] * dimensions[1]; |
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316 | this->reconAllocated = false; |
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317 | this->baselineAllocated = false; |
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318 | if((size<0) || (imsize<0) ) |
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319 | duchampError("Cube(dimArray)","Negative size -- could not define Cube"); |
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320 | else{ |
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321 | this->numPixels = size; |
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322 | if(size>0){ |
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323 | this->array = new float[size]; |
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324 | this->detectMap = new short[imsize]; |
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325 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
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326 | this->recon = new float[size]; |
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327 | this->reconAllocated = true; |
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328 | } |
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329 | if(this->par.getFlagBaseline()){ |
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330 | this->baseline = new float[size]; |
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331 | this->baselineAllocated = true; |
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332 | } |
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333 | } |
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334 | this->numDim = 3; |
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335 | this->axisDim = new long[3]; |
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336 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
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337 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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338 | this->reconExists = false; |
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339 | } |
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340 | } |
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341 | //-------------------------------------------------------------------- |
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342 | |
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343 | Cube::~Cube() |
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344 | { |
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345 | // delete [] array; |
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346 | // delete [] axisDim; |
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347 | // objectList.clear(); |
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348 | |
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349 | delete [] this->detectMap; |
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350 | if(this->reconAllocated) delete [] this->recon; |
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351 | if(this->baselineAllocated) delete [] this->baseline; |
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352 | } |
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353 | //-------------------------------------------------------------------- |
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354 | |
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355 | void Cube::initialiseCube(long *dimensions) |
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356 | { |
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357 | /** |
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358 | * Cube::initialiseCube(long *dim) |
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359 | * A function that defines the sizes of all the necessary |
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360 | * arrays in the Cube class. |
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361 | * It also defines the values of the axis dimensions. |
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362 | * This is done with the WCS in the FitsHeader class, so the |
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363 | * WCS needs to be good and have three axes. |
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364 | */ |
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365 | |
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366 | int lng,lat,spc,size,imsize; |
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367 | |
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368 | if(this->head.isWCS() && (this->head.getWCS()->naxis>=3)){ |
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369 | // if there is a WCS and there is at least 3 axes |
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370 | lng = this->head.getWCS()->lng; |
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371 | lat = this->head.getWCS()->lat; |
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372 | spc = this->head.getWCS()->spec; |
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373 | } |
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374 | else{ |
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375 | // just take dimensions[] at face value |
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376 | lng = 0; |
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377 | lat = 1; |
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378 | spc = 2; |
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379 | } |
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380 | size = dimensions[lng] * dimensions[lat] * dimensions[spc]; |
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381 | imsize = dimensions[lng] * dimensions[lat]; |
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382 | |
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383 | this->reconAllocated = false; |
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384 | this->baselineAllocated = false; |
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385 | |
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386 | if((size<0) || (imsize<0) ) |
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387 | duchampError("Cube::initialiseCube(dimArray)", |
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388 | "Negative size -- could not define Cube.\n"); |
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389 | else{ |
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390 | this->numPixels = size; |
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391 | if(size>0){ |
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392 | this->array = new float[size]; |
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393 | this->detectMap = new short[imsize]; |
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394 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()){ |
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395 | this->recon = new float[size]; |
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396 | this->reconAllocated = true; |
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397 | } |
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398 | if(this->par.getFlagBaseline()){ |
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399 | this->baseline = new float[size]; |
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400 | this->baselineAllocated = true; |
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401 | } |
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402 | } |
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403 | this->numDim = 3; |
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404 | this->axisDim = new long[3]; |
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405 | this->axisDim[0] = dimensions[lng]; |
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406 | this->axisDim[1] = dimensions[lat]; |
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407 | this->axisDim[2] = dimensions[spc]; |
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408 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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409 | this->reconExists = false; |
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410 | } |
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411 | } |
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412 | //-------------------------------------------------------------------- |
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413 | |
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414 | int Cube::getopts(int argc, char ** argv) |
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415 | { |
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416 | /** |
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417 | * Cube::getopt |
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418 | * A front-end to read in the command-line options, |
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419 | * and then read in the correct parameters to the cube->par |
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420 | */ |
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421 | |
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422 | int returnValue; |
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423 | if(argc==1){ |
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424 | std::cout << ERR_USAGE_MSG; |
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425 | returnValue = FAILURE; |
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426 | } |
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427 | else { |
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428 | string file; |
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429 | Param *par = new Param; |
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430 | char c; |
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431 | while( ( c = getopt(argc,argv,"p:f:hv") )!=-1){ |
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432 | switch(c) { |
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433 | case 'p': |
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434 | file = optarg; |
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435 | if(this->readParam(file)==FAILURE){ |
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436 | stringstream errmsg; |
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437 | errmsg << "Could not open parameter file " << file << ".\n"; |
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438 | duchampError("Duchamp",errmsg.str()); |
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439 | returnValue = FAILURE; |
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440 | } |
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441 | else returnValue = SUCCESS; |
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442 | break; |
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443 | case 'f': |
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444 | file = optarg; |
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445 | par->setImageFile(file); |
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446 | this->saveParam(*par); |
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447 | returnValue = SUCCESS; |
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448 | break; |
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449 | case 'v': |
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450 | std::cout << PROGNAME << " version " << VERSION << std::endl; |
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451 | returnValue = FAILURE; |
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452 | break; |
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453 | case 'h': |
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454 | default : |
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455 | std::cout << ERR_USAGE_MSG; |
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456 | returnValue = FAILURE; |
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457 | break; |
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458 | } |
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459 | } |
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460 | delete par; |
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461 | } |
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462 | return returnValue; |
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463 | } |
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464 | //-------------------------------------------------------------------- |
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465 | |
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466 | void Cube::readSavedArrays() |
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467 | { |
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468 | // If the reconstructed array is to be read in from disk |
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469 | if( this->par.getFlagReconExists() && this->par.getFlagATrous() ){ |
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470 | std::cout << "Reading reconstructed array: "<<std::endl; |
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471 | if( this->readReconCube() == FAILURE){ |
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472 | std::stringstream errmsg; |
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473 | errmsg <<"Could not read in existing reconstructed array.\n" |
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474 | <<"Will perform reconstruction using assigned parameters.\n"; |
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475 | duchampWarning("Duchamp", errmsg.str()); |
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476 | this->par.setFlagReconExists(false); |
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477 | } |
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478 | else std::cout << "Reconstructed array available.\n"; |
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479 | } |
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480 | |
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481 | if( this->par.getFlagSmoothExists() && this->par.getFlagSmooth() ){ |
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482 | std::cout << "Reading Hanning-smoothed array: "<<std::endl; |
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483 | if( this->readSmoothCube() == FAILURE){ |
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484 | std::stringstream errmsg; |
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485 | errmsg <<"Could not read in existing smoothed array.\n" |
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486 | <<"Will smooth the cube using assigned parameters.\n"; |
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487 | duchampWarning("Duchamp", errmsg.str()); |
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488 | this->par.setFlagSmoothExists(false); |
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489 | } |
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490 | else std::cout << "Smoothed array available.\n"; |
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491 | } |
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492 | |
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493 | } |
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494 | |
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495 | //-------------------------------------------------------------------- |
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496 | |
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497 | void Cube::saveArray(float *input, long size){ |
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498 | if(size != this->numPixels){ |
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499 | stringstream errmsg; |
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500 | errmsg << "Input array different size to existing array (" |
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501 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
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502 | duchampError("Cube::saveArray",errmsg.str()); |
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503 | } |
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504 | else { |
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505 | if(this->numPixels>0) delete [] array; |
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506 | this->numPixels = size; |
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507 | this->array = new float[size]; |
---|
508 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
---|
509 | } |
---|
510 | } |
---|
511 | //-------------------------------------------------------------------- |
---|
512 | |
---|
513 | void Cube::saveRecon(float *input, long size){ |
---|
514 | if(size != this->numPixels){ |
---|
515 | stringstream errmsg; |
---|
516 | errmsg << "Input array different size to existing array (" |
---|
517 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
---|
518 | duchampError("Cube::saveRecon",errmsg.str()); |
---|
519 | } |
---|
520 | else { |
---|
521 | if(this->numPixels>0){ |
---|
522 | if(this->reconAllocated) delete [] this->recon; |
---|
523 | this->numPixels = size; |
---|
524 | this->recon = new float[size]; |
---|
525 | this->reconAllocated = true; |
---|
526 | for(int i=0;i<size;i++) this->recon[i] = input[i]; |
---|
527 | this->reconExists = true; |
---|
528 | } |
---|
529 | } |
---|
530 | } |
---|
531 | //-------------------------------------------------------------------- |
---|
532 | |
---|
533 | void Cube::getRecon(float *output){ |
---|
534 | // Need check for change in number of pixels! |
---|
535 | for(int i=0;i<this->numPixels;i++){ |
---|
536 | if(this->reconExists) output[i] = this->recon[i]; |
---|
537 | else output[i] = 0.; |
---|
538 | } |
---|
539 | } |
---|
540 | //-------------------------------------------------------------------- |
---|
541 | |
---|
542 | void Cube::removeMW() |
---|
543 | { |
---|
544 | if(this->par.getFlagMW()){ |
---|
545 | for(int pix=0;pix<this->axisDim[0]*this->axisDim[1];pix++){ |
---|
546 | for(int z=0;z<this->axisDim[2];z++){ |
---|
547 | int pos = z*this->axisDim[0]*this->axisDim[1] + pix; |
---|
548 | if(!this->isBlank(pos) && this->par.isInMW(z)) this->array[pos]=0.; |
---|
549 | } |
---|
550 | } |
---|
551 | } |
---|
552 | } |
---|
553 | //-------------------------------------------------------------------- |
---|
554 | |
---|
555 | void Cube::calcObjectWCSparams() |
---|
556 | { |
---|
557 | /** |
---|
558 | * Cube::calcObjectWCSparams() |
---|
559 | * A function that calculates the WCS parameters for each object in the |
---|
560 | * cube's list of detections. |
---|
561 | * Each object gets an ID number set (just the order in the list), and if |
---|
562 | * the WCS is good, the WCS paramters are calculated. |
---|
563 | */ |
---|
564 | |
---|
565 | for(int i=0; i<this->objectList.size();i++){ |
---|
566 | this->objectList[i].setID(i+1); |
---|
567 | this->objectList[i].calcWCSparams(this->head); |
---|
568 | this->objectList[i].setPeakSNR( (this->objectList[i].getPeakFlux() - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
569 | } |
---|
570 | |
---|
571 | |
---|
572 | } |
---|
573 | //-------------------------------------------------------------------- |
---|
574 | |
---|
575 | void Cube::sortDetections() |
---|
576 | { |
---|
577 | /** |
---|
578 | * Cube::sortDetections() |
---|
579 | * A front end to the sort-by functions. |
---|
580 | * If there is a good WCS, the detection list is sorted by velocity. |
---|
581 | * Otherwise, it is sorted by increasing z-pixel value. |
---|
582 | * The ID numbers are then re-calculated. |
---|
583 | */ |
---|
584 | |
---|
585 | if(this->head.isWCS()) SortByVel(this->objectList); |
---|
586 | else SortByZ(this->objectList); |
---|
587 | for(int i=0; i<this->objectList.size();i++) this->objectList[i].setID(i+1); |
---|
588 | |
---|
589 | } |
---|
590 | //-------------------------------------------------------------------- |
---|
591 | |
---|
592 | void Cube::updateDetectMap() |
---|
593 | { |
---|
594 | /** |
---|
595 | * Cube::updateDetectMap() |
---|
596 | * A function that, for each detected object in the cube's list, increments |
---|
597 | * the cube's detection map by the required amount at each pixel. |
---|
598 | */ |
---|
599 | |
---|
600 | for(int obj=0;obj<this->objectList.size();obj++){ |
---|
601 | for(int pix=0;pix<this->objectList[obj].getSize();pix++) { |
---|
602 | int spatialPos = this->objectList[obj].getX(pix)+ |
---|
603 | this->objectList[obj].getY(pix)*this->axisDim[0]; |
---|
604 | this->detectMap[spatialPos]++; |
---|
605 | } |
---|
606 | } |
---|
607 | } |
---|
608 | //-------------------------------------------------------------------- |
---|
609 | |
---|
610 | void Cube::updateDetectMap(Detection obj) |
---|
611 | { |
---|
612 | /** |
---|
613 | * Cube::updateDetectMap(Detection) |
---|
614 | * A function that, for the given object, increments the cube's |
---|
615 | * detection map by the required amount at each pixel. |
---|
616 | */ |
---|
617 | for(int pix=0;pix<obj.getSize();pix++) { |
---|
618 | int spatialPos = obj.getX(pix)+obj.getY(pix)*this->axisDim[0]; |
---|
619 | this->detectMap[spatialPos]++; |
---|
620 | } |
---|
621 | } |
---|
622 | //-------------------------------------------------------------------- |
---|
623 | |
---|
624 | void Cube::setCubeStatsOld() |
---|
625 | { |
---|
626 | /** |
---|
627 | * Cube::setCubeStatsOld() |
---|
628 | * Calculates the full statistics for the cube: |
---|
629 | * mean, rms, median, madfm |
---|
630 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
631 | * its default). |
---|
632 | * Also work out the threshold and store it in the par set. |
---|
633 | * |
---|
634 | * For stats calculations, ignore BLANKs and MW channels. |
---|
635 | */ |
---|
636 | |
---|
637 | if(!this->par.getFlagFDR() && this->par.getFlagUserThreshold() ){ |
---|
638 | // if the user has defined a threshold, set this in the StatsContainer |
---|
639 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
640 | } |
---|
641 | else{ |
---|
642 | // only work out the mean etc if we need to. |
---|
643 | // the only reason we don't is if the user has specified a threshold. |
---|
644 | |
---|
645 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
646 | |
---|
647 | // get number of good pixels; |
---|
648 | int goodSize = 0; |
---|
649 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
650 | for(int z=0;z<this->axisDim[2];z++){ |
---|
651 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
652 | if(!this->isBlank(vox) && !this->par.isInMW(z)) goodSize++; |
---|
653 | } |
---|
654 | } |
---|
655 | |
---|
656 | float *tempArray = new float[goodSize]; |
---|
657 | |
---|
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]; |
---|
664 | } |
---|
665 | } |
---|
666 | if(!this->reconExists){ |
---|
667 | // if there's no recon array, calculate everything from orig array |
---|
668 | this->Stats.calculate(tempArray,goodSize); |
---|
669 | } |
---|
670 | else{ |
---|
671 | // just get mean & median from orig array, and rms & madfm from recon |
---|
672 | StatsContainer<float> origStats,reconStats; |
---|
673 | origStats.calculate(tempArray,goodSize); |
---|
674 | goodSize=0; |
---|
675 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
676 | for(int z=0;z<this->axisDim[2];z++){ |
---|
677 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
678 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
679 | tempArray[goodSize++] = this->array[vox] - this->recon[vox]; |
---|
680 | } |
---|
681 | } |
---|
682 | reconStats.calculate(tempArray,goodSize); |
---|
683 | |
---|
684 | // Get the "middle" estimators from the original array. |
---|
685 | // Get the "spread" estimators from the residual (orig-recon) array |
---|
686 | this->Stats.setMean(origStats.getMean()); |
---|
687 | this->Stats.setMedian(origStats.getMedian()); |
---|
688 | this->Stats.setStddev(reconStats.getStddev()); |
---|
689 | this->Stats.setMadfm(reconStats.getMadfm()); |
---|
690 | } |
---|
691 | |
---|
692 | delete [] tempArray; |
---|
693 | |
---|
694 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
695 | // If the FDR method has been requested |
---|
696 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
697 | else{ |
---|
698 | // otherwise, calculate one based on the requested SNR cut level, and |
---|
699 | // then set the threshold parameter in the Par set. |
---|
700 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
701 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
702 | } |
---|
703 | |
---|
704 | |
---|
705 | } |
---|
706 | std::cout << "Using "; |
---|
707 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
708 | std::cout << "flux threshold of: "; |
---|
709 | float thresh = this->Stats.getThreshold(); |
---|
710 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
711 | std::cout << thresh << std::endl; |
---|
712 | |
---|
713 | } |
---|
714 | //-------------------------------------------------------------------- |
---|
715 | |
---|
716 | void Cube::setCubeStats() |
---|
717 | { |
---|
718 | /** |
---|
719 | * Cube::setCubeStats() |
---|
720 | * Calculates the full statistics for the cube: |
---|
721 | * mean, rms, median, madfm |
---|
722 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
723 | * its default). |
---|
724 | * Also work out the threshold and store it in the par set. |
---|
725 | * |
---|
726 | * Different from setCubeStatsOld as it doesn't use the getStats functions |
---|
727 | * but has own versions of them hardcoded to ignore BLANKs and |
---|
728 | * MW channels. |
---|
729 | */ |
---|
730 | |
---|
731 | if(!this->par.getFlagFDR() && this->par.getFlagUserThreshold() ){ |
---|
732 | // if the user has defined a threshold, set this in the StatsContainer |
---|
733 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
734 | } |
---|
735 | else{ |
---|
736 | // only work out the mean etc if we need to. |
---|
737 | // the only reason we don't is if the user has specified a threshold. |
---|
738 | |
---|
739 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
740 | |
---|
741 | long xysize = this->axisDim[0]*this->axisDim[1]; |
---|
742 | |
---|
743 | // get number of good pixels; |
---|
744 | int vox,goodSize = 0; |
---|
745 | for(int p=0;p<xysize;p++){ |
---|
746 | for(int z=0;z<this->axisDim[2];z++){ |
---|
747 | vox = z*xysize+p; |
---|
748 | if(!this->isBlank(vox) && !this->par.isInMW(z)) goodSize++; |
---|
749 | } |
---|
750 | } |
---|
751 | |
---|
752 | float *tempArray = new float[goodSize]; |
---|
753 | |
---|
754 | goodSize=0; |
---|
755 | for(int p=0;p<xysize;p++){ |
---|
756 | for(int z=0;z<this->axisDim[2];z++){ |
---|
757 | vox = z * xysize + p; |
---|
758 | if(!this->isBlank(vox) && !this->par.isInMW(z)){ |
---|
759 | tempArray[goodSize] = this->array[vox]; |
---|
760 | goodSize++; |
---|
761 | } |
---|
762 | } |
---|
763 | } |
---|
764 | |
---|
765 | float mean,median,stddev,madfm; |
---|
766 | mean = tempArray[0]; |
---|
767 | for(int i=1;i<goodSize;i++) mean += tempArray[i]; |
---|
768 | mean /= float(goodSize); |
---|
769 | mean = findMean(tempArray,goodSize); |
---|
770 | this->Stats.setMean(mean); |
---|
771 | |
---|
772 | std::sort(tempArray,tempArray+goodSize); |
---|
773 | if((goodSize%2)==0) |
---|
774 | median = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
775 | else median = tempArray[goodSize/2]; |
---|
776 | this->Stats.setMedian(median); |
---|
777 | |
---|
778 | |
---|
779 | if(!this->reconExists){ |
---|
780 | // if there's no recon array, calculate everything from orig array |
---|
781 | stddev = (tempArray[0]-mean) * (tempArray[0]-mean); |
---|
782 | for(int i=1;i<goodSize;i++) |
---|
783 | stddev += (tempArray[i]-mean)*(tempArray[i]-mean); |
---|
784 | stddev = sqrt(stddev/float(goodSize-1)); |
---|
785 | this->Stats.setStddev(stddev); |
---|
786 | |
---|
787 | for(int i=0;i<goodSize;i++)// tempArray[i] = absval(tempArray[i]-median); |
---|
788 | { |
---|
789 | if(tempArray[i]>median) tempArray[i] -= median; |
---|
790 | else tempArray[i] = median - tempArray[i]; |
---|
791 | } |
---|
792 | std::sort(tempArray,tempArray+goodSize); |
---|
793 | if((goodSize%2)==0) |
---|
794 | madfm = (tempArray[goodSize/2-1]+tempArray[goodSize/2])/2; |
---|
795 | else madfm = tempArray[goodSize/2]; |
---|
796 | this->Stats.setMadfm(madfm); |
---|
797 | } |
---|
798 | else{ |
---|
799 | // just get mean & median from orig array, and rms & madfm from residual |
---|
800 | // recompute array values to be residuals & then find stddev & madfm |
---|
801 | goodSize = 0; |
---|
802 | for(int p=0;p<xysize;p++){ |
---|
803 | for(int z=0;z<this->axisDim[2];z++){ |
---|
804 | vox = z * xysize + p; |
---|
805 | if(!this->isBlank(vox) && !this->par.isInMW(z)){ |
---|
806 | tempArray[goodSize] = this->array[vox] - this->recon[vox]; |
---|
807 | goodSize++; |
---|
808 | } |
---|
809 | } |
---|
810 | } |
---|
811 | mean = tempArray[0]; |
---|
812 | for(int i=1;i<goodSize;i++) mean += tempArray[i]; |
---|
813 | mean /= float(goodSize); |
---|
814 | stddev = (tempArray[0]-mean) * (tempArray[0]-mean); |
---|
815 | for(int i=1;i<goodSize;i++) |
---|
816 | stddev += (tempArray[i]-mean)*(tempArray[i]-mean); |
---|
817 | stddev = sqrt(stddev/float(goodSize-1)); |
---|
818 | this->Stats.setStddev(stddev); |
---|
819 | |
---|
820 | std::sort(tempArray,tempArray+goodSize); |
---|
821 | if((goodSize%2)==0) |
---|
822 | median = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
823 | else median = tempArray[goodSize/2]; |
---|
824 | for(int i=0;i<goodSize;i++){ |
---|
825 | if(tempArray[i]>median) tempArray[i] = tempArray[i]-median; |
---|
826 | else tempArray[i] = median - tempArray[i]; |
---|
827 | } |
---|
828 | std::sort(tempArray,tempArray+goodSize); |
---|
829 | if((goodSize%2)==0) |
---|
830 | madfm = (tempArray[goodSize/2-1] + tempArray[goodSize/2])/2; |
---|
831 | else madfm = tempArray[goodSize/2]; |
---|
832 | this->Stats.setMadfm(madfm); |
---|
833 | } |
---|
834 | |
---|
835 | delete [] tempArray; |
---|
836 | |
---|
837 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
838 | // If the FDR method has been requested |
---|
839 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
840 | else{ |
---|
841 | // otherwise, calculate threshold based on the requested SNR cut level, |
---|
842 | // and then set the threshold parameter in the Par set. |
---|
843 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
844 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
845 | } |
---|
846 | |
---|
847 | } |
---|
848 | |
---|
849 | std::cout << "Using "; |
---|
850 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
851 | std::cout << "flux threshold of: "; |
---|
852 | float thresh = this->Stats.getThreshold(); |
---|
853 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
854 | std::cout << thresh << std::endl; |
---|
855 | |
---|
856 | } |
---|
857 | //-------------------------------------------------------------------- |
---|
858 | |
---|
859 | int Cube::setupFDR() |
---|
860 | { |
---|
861 | /** |
---|
862 | * Cube::setupFDR() |
---|
863 | * Determines the critical Prob value for the False Discovery Rate |
---|
864 | * detection routine. All pixels with Prob less than this value will |
---|
865 | * be considered detections. |
---|
866 | * The Prob here is the probability, assuming a Normal distribution, of |
---|
867 | * obtaining a value as high or higher than the pixel value (ie. only the |
---|
868 | * positive tail of the PDF) |
---|
869 | */ |
---|
870 | |
---|
871 | // first calculate p-value for each pixel -- assume Gaussian for now. |
---|
872 | |
---|
873 | float *orderedP = new float[this->numPixels]; |
---|
874 | int count = 0; |
---|
875 | float zStat; |
---|
876 | for(int pix=0; pix<this->numPixels; pix++){ |
---|
877 | |
---|
878 | if( !(this->par.isBlank(this->array[pix])) ){ |
---|
879 | // only look at non-blank pixels |
---|
880 | zStat = (this->array[pix] - this->Stats.getMiddle()) / |
---|
881 | this->Stats.getSpread(); |
---|
882 | |
---|
883 | orderedP[count++] = 0.5 * erfc(zStat/M_SQRT2); |
---|
884 | // Need the factor of 0.5 here, as we are only considering the positive |
---|
885 | // tail of the distribution. Don't care about negative detections. |
---|
886 | } |
---|
887 | } |
---|
888 | |
---|
889 | // now order them |
---|
890 | std::sort(orderedP,orderedP+count); |
---|
891 | |
---|
892 | // now find the maximum P value. |
---|
893 | int max = 0; |
---|
894 | float cN = 0.; |
---|
895 | int psfCtr; |
---|
896 | int numVox = int(this->par.getBeamSize()) * 2; |
---|
897 | // why beamSize*2? we are doing this in 3D, so spectrally assume just the |
---|
898 | // neighbouring channels are correlated, but spatially all those within |
---|
899 | // the beam, so total number of voxels is 2*beamSize |
---|
900 | for(psfCtr=1;psfCtr<=numVox;(psfCtr)++) |
---|
901 | cN += 1./float(psfCtr); |
---|
902 | |
---|
903 | for(int loopCtr=0;loopCtr<count;loopCtr++) { |
---|
904 | if( orderedP[loopCtr] < |
---|
905 | (double(loopCtr+1)*this->par.getAlpha()/(cN * double(count))) ) { |
---|
906 | max = loopCtr; |
---|
907 | } |
---|
908 | } |
---|
909 | |
---|
910 | this->Stats.setPThreshold( orderedP[max] ); |
---|
911 | |
---|
912 | delete [] orderedP; |
---|
913 | |
---|
914 | // Find real value of the P threshold by finding the inverse of the |
---|
915 | // error function -- root finding with brute force technique |
---|
916 | // (relatively slow, but we only do it once). |
---|
917 | zStat = 0; |
---|
918 | float deltaZ = 0.1; |
---|
919 | float tolerance = 1.e-6; |
---|
920 | float zeroP = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
921 | do{ |
---|
922 | zStat+=deltaZ; |
---|
923 | if((zeroP * (erfc(zStat/M_SQRT2)-this->Stats.getPThreshold()))<0.){ |
---|
924 | zStat-=deltaZ; |
---|
925 | deltaZ/=2.; |
---|
926 | } |
---|
927 | }while(deltaZ>tolerance); |
---|
928 | this->Stats.setThreshold( zStat*this->Stats.getSpread() + |
---|
929 | this->Stats.getMiddle() ); |
---|
930 | |
---|
931 | } |
---|
932 | //-------------------------------------------------------------------- |
---|
933 | |
---|
934 | float Cube::enclosedFlux(Detection obj) |
---|
935 | { |
---|
936 | /** |
---|
937 | * float Cube::enclosedFlux(Detection obj) |
---|
938 | * A function to calculate the flux enclosed by the range |
---|
939 | * of pixels detected in the object obj (not necessarily all |
---|
940 | * pixels will have been detected). |
---|
941 | */ |
---|
942 | obj.calcParams(); |
---|
943 | int xsize = obj.getXmax()-obj.getXmin()+1; |
---|
944 | int ysize = obj.getYmax()-obj.getYmin()+1; |
---|
945 | int zsize = obj.getZmax()-obj.getZmin()+1; |
---|
946 | vector <float> fluxArray(xsize*ysize*zsize,0.); |
---|
947 | for(int x=0;x<xsize;x++){ |
---|
948 | for(int y=0;y<ysize;y++){ |
---|
949 | for(int z=0;z<zsize;z++){ |
---|
950 | fluxArray[x+y*xsize+z*ysize*xsize] = |
---|
951 | this->getPixValue(x+obj.getXmin(), |
---|
952 | y+obj.getYmin(), |
---|
953 | z+obj.getZmin()); |
---|
954 | if(this->par.getFlagNegative()) |
---|
955 | fluxArray[x+y*xsize+z*ysize*xsize] *= -1.; |
---|
956 | } |
---|
957 | } |
---|
958 | } |
---|
959 | float sum = 0.; |
---|
960 | for(int i=0;i<fluxArray.size();i++) |
---|
961 | if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i]; |
---|
962 | return sum; |
---|
963 | } |
---|
964 | //-------------------------------------------------------------------- |
---|
965 | |
---|
966 | void Cube::setupColumns() |
---|
967 | { |
---|
968 | /** |
---|
969 | * Cube::setupColumns() |
---|
970 | * A front-end to the two setup routines in columns.cc. |
---|
971 | */ |
---|
972 | this->calcObjectWCSparams(); |
---|
973 | // need this as the colSet functions use vel, RA, Dec, etc... |
---|
974 | |
---|
975 | this->fullCols.clear(); |
---|
976 | this->fullCols = getFullColSet(this->objectList, this->head); |
---|
977 | |
---|
978 | this->logCols.clear(); |
---|
979 | this->logCols = getLogColSet(this->objectList, this->head); |
---|
980 | |
---|
981 | int vel,fpeak,fint,pos,xyz,temp,snr; |
---|
982 | vel = fullCols[VEL].getPrecision(); |
---|
983 | fpeak = fullCols[FPEAK].getPrecision(); |
---|
984 | snr = fullCols[SNRPEAK].getPrecision(); |
---|
985 | xyz = fullCols[X].getPrecision(); |
---|
986 | if(temp=fullCols[Y].getPrecision() > xyz) xyz = temp; |
---|
987 | if(temp=fullCols[Z].getPrecision() > xyz) xyz = temp; |
---|
988 | if(this->head.isWCS()) fint = fullCols[FINT].getPrecision(); |
---|
989 | else fint = fullCols[FTOT].getPrecision(); |
---|
990 | pos = fullCols[WRA].getPrecision(); |
---|
991 | if(temp=fullCols[WDEC].getPrecision() > pos) pos = temp; |
---|
992 | |
---|
993 | for(int obj=0;obj<this->objectList.size();obj++){ |
---|
994 | this->objectList[obj].setVelPrec(vel); |
---|
995 | this->objectList[obj].setFpeakPrec(fpeak); |
---|
996 | this->objectList[obj].setXYZPrec(xyz); |
---|
997 | this->objectList[obj].setPosPrec(pos); |
---|
998 | this->objectList[obj].setFintPrec(fint); |
---|
999 | this->objectList[obj].setSNRPrec(snr); |
---|
1000 | } |
---|
1001 | |
---|
1002 | } |
---|
1003 | //-------------------------------------------------------------------- |
---|
1004 | |
---|
1005 | bool Cube::objAtSpatialEdge(Detection obj) |
---|
1006 | { |
---|
1007 | /** |
---|
1008 | * bool Cube::objAtSpatialEdge() |
---|
1009 | * A function to test whether the object obj |
---|
1010 | * lies at the edge of the cube's spatial field -- |
---|
1011 | * either at the boundary, or next to BLANKs |
---|
1012 | */ |
---|
1013 | |
---|
1014 | bool atEdge = false; |
---|
1015 | |
---|
1016 | int pix = 0; |
---|
1017 | while(!atEdge && pix<obj.getSize()){ |
---|
1018 | // loop over each pixel in the object, until we find an edge pixel. |
---|
1019 | Voxel vox = obj.getPixel(pix); |
---|
1020 | for(int dx=-1;dx<=1;dx+=2){ |
---|
1021 | if(((vox.getX()+dx)<0) || ((vox.getX()+dx)>=this->axisDim[0])) |
---|
1022 | atEdge = true; |
---|
1023 | else if(this->isBlank(vox.getX()+dx,vox.getY(),vox.getZ())) |
---|
1024 | atEdge = true; |
---|
1025 | } |
---|
1026 | for(int dy=-1;dy<=1;dy+=2){ |
---|
1027 | if(((vox.getY()+dy)<0) || ((vox.getY()+dy)>=this->axisDim[1])) |
---|
1028 | atEdge = true; |
---|
1029 | else if(this->isBlank(vox.getX(),vox.getY()+dy,vox.getZ())) |
---|
1030 | atEdge = true; |
---|
1031 | } |
---|
1032 | pix++; |
---|
1033 | } |
---|
1034 | |
---|
1035 | return atEdge; |
---|
1036 | } |
---|
1037 | //-------------------------------------------------------------------- |
---|
1038 | |
---|
1039 | bool Cube::objAtSpectralEdge(Detection obj) |
---|
1040 | { |
---|
1041 | /** |
---|
1042 | * bool Cube::objAtSpectralEdge() |
---|
1043 | * A function to test whether the object obj |
---|
1044 | * lies at the edge of the cube's spectral extent -- |
---|
1045 | * either at the boundary, or next to BLANKs |
---|
1046 | */ |
---|
1047 | |
---|
1048 | bool atEdge = false; |
---|
1049 | |
---|
1050 | int pix = 0; |
---|
1051 | while(!atEdge && pix<obj.getSize()){ |
---|
1052 | // loop over each pixel in the object, until we find an edge pixel. |
---|
1053 | Voxel vox = obj.getPixel(pix); |
---|
1054 | for(int dz=-1;dz<=1;dz+=2){ |
---|
1055 | if(((vox.getZ()+dz)<0) || ((vox.getZ()+dz)>=this->axisDim[2])) |
---|
1056 | atEdge = true; |
---|
1057 | else if(this->isBlank(vox.getX(),vox.getY(),vox.getZ()+dz)) |
---|
1058 | atEdge = true; |
---|
1059 | } |
---|
1060 | pix++; |
---|
1061 | } |
---|
1062 | |
---|
1063 | return atEdge; |
---|
1064 | } |
---|
1065 | //-------------------------------------------------------------------- |
---|
1066 | |
---|
1067 | void Cube::setObjectFlags() |
---|
1068 | { |
---|
1069 | /** |
---|
1070 | * void Cube::setObjectFlags() |
---|
1071 | * A function to set any warning flags for all the detected objects |
---|
1072 | * associated with the cube. |
---|
1073 | * Flags to be looked for: |
---|
1074 | * * Negative enclosed flux (N) |
---|
1075 | * * Object at edge of field (E) |
---|
1076 | */ |
---|
1077 | |
---|
1078 | for(int i=0;i<this->objectList.size();i++){ |
---|
1079 | |
---|
1080 | if( this->enclosedFlux(this->objectList[i]) < 0. ) |
---|
1081 | this->objectList[i].addToFlagText("N"); |
---|
1082 | |
---|
1083 | if( this->objAtSpatialEdge(this->objectList[i]) ) |
---|
1084 | this->objectList[i].addToFlagText("E"); |
---|
1085 | |
---|
1086 | if( this->objAtSpectralEdge(this->objectList[i]) ) |
---|
1087 | this->objectList[i].addToFlagText("S"); |
---|
1088 | |
---|
1089 | } |
---|
1090 | |
---|
1091 | } |
---|
1092 | //-------------------------------------------------------------------- |
---|
1093 | |
---|
1094 | void Cube::plotBlankEdges() |
---|
1095 | { |
---|
1096 | if(this->par.drawBlankEdge()){ |
---|
1097 | int colour; |
---|
1098 | cpgqci(&colour); |
---|
1099 | cpgsci(MAGENTA); |
---|
1100 | drawBlankEdges(this->array,this->axisDim[0],this->axisDim[1],this->par); |
---|
1101 | cpgsci(colour); |
---|
1102 | } |
---|
1103 | } |
---|