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 <string> |
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6 | |
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7 | #include <wcs.h> |
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8 | |
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9 | #include <duchamp.hh> |
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10 | #include <param.hh> |
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11 | #include <Cubes/cubes.hh> |
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12 | #include <Detection/detection.hh> |
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13 | #include <Detection/columns.hh> |
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14 | #include <Utils/utils.hh> |
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15 | #include <Utils/mycpgplot.hh> |
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16 | #include <Utils/Statistics.hh> |
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17 | using std::endl; |
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18 | using namespace Column; |
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19 | using namespace mycpgplot; |
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20 | using namespace Statistics; |
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21 | |
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22 | /****************************************************************/ |
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23 | /////////////////////////////////////////////////// |
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24 | //// Functions for DataArray class: |
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25 | /////////////////////////////////////////////////// |
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26 | |
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27 | DataArray::DataArray(short int nDim, long size){ |
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28 | |
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29 | if(size<0) |
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30 | duchampError("DataArray(nDim,size)", |
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31 | "Negative size -- could not define DataArray"); |
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32 | else if(nDim<0) |
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33 | duchampError("DataArray(nDim,size)", |
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34 | "Negative number of dimensions: could not define DataArray"); |
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35 | else { |
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36 | if(size>0) this->array = new float[size]; |
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37 | this->numPixels = size; |
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38 | if(nDim>0) this->axisDim = new long[nDim]; |
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39 | this->numDim = nDim; |
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40 | } |
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41 | } |
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42 | //-------------------------------------------------------------------- |
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43 | |
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44 | DataArray::DataArray(short int nDim, long *dimensions){ |
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45 | if(nDim<0) |
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46 | duchampError("DataArray(nDim,dimArray)", |
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47 | "Negative number of dimensions: could not define DataArray"); |
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48 | else { |
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49 | int size = dimensions[0]; |
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50 | for(int i=1;i<nDim;i++) size *= dimensions[i]; |
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51 | if(size<0) |
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52 | duchampError("DataArray(nDim,dimArray)", |
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53 | "Negative size: could not define DataArray"); |
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54 | else{ |
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55 | this->numPixels = size; |
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56 | if(size>0){ |
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57 | this->array = new float[size]; |
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58 | } |
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59 | this->numDim=nDim; |
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60 | if(nDim>0) this->axisDim = new long[nDim]; |
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61 | for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i]; |
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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 | |
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67 | DataArray::~DataArray() |
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68 | { |
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69 | delete [] array; |
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70 | delete [] axisDim; |
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71 | objectList.clear(); |
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72 | } |
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73 | //-------------------------------------------------------------------- |
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74 | |
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75 | void DataArray::getDimArray(long *output){ |
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76 | for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i]; |
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77 | } |
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78 | //-------------------------------------------------------------------- |
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79 | |
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80 | void DataArray::getArray(float *output){ |
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81 | for(int i=0;i<this->numPixels;i++) output[i] = this->array[i]; |
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82 | } |
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83 | //-------------------------------------------------------------------- |
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84 | |
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85 | void DataArray::saveArray(float *input, long size){ |
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86 | if(size != this->numPixels) |
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87 | duchampError("DataArray::saveArray", |
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88 | "Input array different size to existing array. Cannot save."); |
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89 | else { |
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90 | if(this->numPixels>0) delete [] this->array; |
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91 | this->numPixels = size; |
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92 | this->array = new float[size]; |
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93 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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94 | } |
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95 | } |
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96 | //-------------------------------------------------------------------- |
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97 | |
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98 | void DataArray::getDim(long &x, long &y, long &z){ |
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99 | if(numDim>0) x=axisDim[0]; |
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100 | else x=0; |
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101 | if(numDim>1) y=axisDim[1]; |
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102 | else y=0; |
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103 | if(numDim>2) z=axisDim[2]; |
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104 | else z=0; |
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105 | } |
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106 | //-------------------------------------------------------------------- |
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107 | |
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108 | void DataArray::addObject(Detection object){ |
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109 | // adds a single detection to the object list |
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110 | // objectList is a vector, so just use push_back() |
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111 | this->objectList.push_back(object); |
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112 | } |
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113 | //-------------------------------------------------------------------- |
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114 | |
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115 | void DataArray::addObjectList(vector <Detection> newlist) { |
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116 | for(int i=0;i<newlist.size();i++) this->objectList.push_back(newlist[i]); |
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117 | } |
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118 | //-------------------------------------------------------------------- |
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119 | |
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120 | void DataArray::addObjectOffsets(){ |
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121 | for(int i=0;i<this->objectList.size();i++){ |
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122 | for(int p=0;p<this->objectList[i].getSize();p++){ |
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123 | this->objectList[i].setX(p,this->objectList[i].getX(p)+ |
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124 | this->par.getXOffset()); |
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125 | this->objectList[i].setY(p,this->objectList[i].getY(p)+ |
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126 | this->par.getYOffset()); |
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127 | this->objectList[i].setZ(p,this->objectList[i].getZ(p)+ |
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128 | this->par.getZOffset()); |
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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 | |
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134 | std::ostream& operator<< ( std::ostream& theStream, DataArray &array) |
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135 | { |
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136 | for(int i=0;i<array.numDim;i++){ |
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137 | if(i>0) theStream<<"x"; |
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138 | theStream<<array.axisDim[i]; |
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139 | } |
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140 | theStream<<endl; |
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141 | theStream<<array.objectList.size()<<" detections:"<<endl<<"--------------\n"; |
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142 | for(int i=0;i<array.objectList.size();i++){ |
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143 | theStream << "Detection #" << array.objectList[i].getID()<<endl; |
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144 | Detection *obj = new Detection; |
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145 | *obj = array.objectList[i]; |
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146 | for(int j=0;j<obj->getSize();j++){ |
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147 | obj->setX(j,obj->getX(j)+obj->getXOffset()); |
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148 | obj->setY(j,obj->getY(j)+obj->getYOffset()); |
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149 | obj->setZ(j,obj->getZ(j)+obj->getZOffset()); |
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150 | } |
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151 | theStream<<*obj; |
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152 | delete obj; |
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153 | } |
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154 | theStream<<"--------------\n"; |
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155 | } |
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156 | |
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157 | /****************************************************************/ |
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158 | ///////////////////////////////////////////////////////////// |
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159 | //// Functions for Image class |
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160 | ///////////////////////////////////////////////////////////// |
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161 | |
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162 | Image::Image(long size){ |
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163 | // need error handling in case size<0 !!! |
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164 | if(size<0) |
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165 | duchampError("Image(size)","Negative size -- could not define Image"); |
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166 | else{ |
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167 | if(size>0){ |
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168 | this->array = new float[size]; |
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169 | // this->pValue = new float[size]; |
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170 | // this->mask = new short int[size]; |
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171 | } |
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172 | this->numPixels = size; |
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173 | this->axisDim = new long[2]; |
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174 | this->numDim = 2; |
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175 | } |
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176 | } |
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177 | //-------------------------------------------------------------------- |
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178 | |
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179 | Image::Image(long *dimensions){ |
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180 | int size = dimensions[0] * dimensions[1]; |
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181 | if(size<0) |
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182 | duchampError("Image(dimArray)","Negative size -- could not define Image"); |
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183 | else{ |
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184 | this->numPixels = size; |
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185 | if(size>0){ |
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186 | this->array = new float[size]; |
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187 | // this->pValue = new float[size]; |
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188 | // this->mask = new short int[size]; |
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189 | } |
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190 | this->numDim=2; |
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191 | this->axisDim = new long[2]; |
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192 | for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i]; |
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193 | // for(int i=0;i<size;i++) this->mask[i] = 0; |
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194 | } |
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195 | } |
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196 | //-------------------------------------------------------------------- |
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197 | |
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198 | Image::~Image(){ |
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199 | if(this->numPixels > 0){ |
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200 | // delete [] this->pValue; |
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201 | // delete [] this->mask; |
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202 | } |
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203 | } |
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204 | //-------------------------------------------------------------------- |
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205 | |
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206 | void Image::saveArray(float *input, long size){ |
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207 | if(size != this->numPixels) |
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208 | duchampError("Image::saveArray", |
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209 | "Input array different size to existing array. Cannot save."); |
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210 | else { |
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211 | if(this->numPixels>0){ |
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212 | delete [] array; |
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213 | // delete [] pValue; |
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214 | // delete [] mask; |
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215 | } |
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216 | this->numPixels = size; |
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217 | if(this->numPixels>0){ |
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218 | this->array = new float[size]; |
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219 | // this->pValue = new float[size]; |
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220 | // this->mask = new short int[size]; |
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221 | } |
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222 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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223 | // for(int i=0;i<size;i++) this->mask[i] = 0; |
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224 | } |
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225 | } |
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226 | //-------------------------------------------------------------------- |
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227 | |
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228 | void Image::extractSpectrum(float *Array, long *dim, long pixel) |
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229 | { |
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230 | /** |
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231 | * Image::extractSpectrum(float *, long *, int) |
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232 | * A function to extract a 1-D spectrum from a 3-D array. |
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233 | * The array is assumed to be 3-D with the third dimension the spectral one. |
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234 | * The dimensions of the array are in the dim[] array. |
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235 | * The spectrum extracted is the one lying in the spatial pixel referenced |
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236 | * by the third argument. |
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237 | */ |
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238 | float *spec = new float[dim[2]]; |
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239 | for(int z=0;z<dim[2];z++) spec[z] = Array[z*dim[0]*dim[1] + pixel]; |
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240 | this->saveArray(spec,dim[2]); |
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241 | delete [] spec; |
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242 | } |
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243 | //-------------------------------------------------------------------- |
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244 | |
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245 | void Image::extractSpectrum(Cube &cube, long pixel) |
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246 | { |
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247 | /** |
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248 | * Image::extractSpectrum(Cube &, int) |
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249 | * A function to extract a 1-D spectrum from a Cube class |
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250 | * The spectrum extracted is the one lying in the spatial pixel referenced |
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251 | * by the second argument. |
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252 | */ |
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253 | long zdim = cube.getDimZ(); |
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254 | long spatSize = cube.getDimX()*cube.getDimY(); |
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255 | float *spec = new float[zdim]; |
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256 | for(int z=0;z<zdim;z++) spec[z] = cube.getPixValue(z*spatSize + pixel); |
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257 | this->saveArray(spec,zdim); |
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258 | delete [] spec; |
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259 | } |
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260 | //-------------------------------------------------------------------- |
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261 | |
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262 | void Image::extractImage(float *Array, long *dim, long channel) |
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263 | { |
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264 | /** |
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265 | * Image::extractImage(float *, long *, int) |
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266 | * A function to extract a 2-D image from a 3-D array. |
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267 | * The array is assumed to be 3-D with the third dimension the spectral one. |
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268 | * The dimensions of the array are in the dim[] array. |
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269 | * The image extracted is the one lying in the channel referenced |
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270 | * by the third argument. |
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271 | */ |
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272 | float *image = new float[dim[0]*dim[1]]; |
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273 | for(int npix=0; npix<dim[0]*dim[1]; npix++){ |
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274 | image[npix] = Array[channel*dim[0]*dim[1] + npix]; |
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275 | } |
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276 | this->saveArray(image,dim[0]*dim[1]); |
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277 | delete [] image; |
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278 | } |
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279 | //-------------------------------------------------------------------- |
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280 | |
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281 | void Image::extractImage(Cube &cube, long channel) |
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282 | { |
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283 | /** |
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284 | * Image::extractImage(Cube &, int) |
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285 | * A function to extract a 2-D image from Cube class. |
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286 | * The image extracted is the one lying in the channel referenced |
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287 | * by the second argument. |
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288 | */ |
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289 | long spatSize = cube.getDimX()*cube.getDimY(); |
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290 | float *image = new float[spatSize]; |
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291 | for(int npix=0; npix<spatSize; npix++) |
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292 | image[npix] = cube.getPixValue(channel*spatSize + npix); |
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293 | this->saveArray(image,spatSize); |
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294 | delete [] image; |
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295 | } |
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296 | //-------------------------------------------------------------------- |
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297 | |
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298 | void Image::removeMW() |
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299 | { |
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300 | /** |
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301 | * Image::removeMW() |
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302 | * A function to remove the Milky Way range of channels from a 1-D spectrum. |
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303 | * The array in this Image is assumed to be 1-D, with only the first axisDim |
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304 | * equal to 1. |
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305 | * The values of the MW channels are set to 0, unless they are BLANK. |
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306 | */ |
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307 | if(this->par.getFlagMW() && (this->axisDim[1]==1) ){ |
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308 | for(int z=0;z<this->axisDim[0];z++){ |
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309 | if(!this->isBlank(z) && this->par.isInMW(z)) this->array[z]=0.; |
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310 | } |
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311 | } |
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312 | } |
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313 | |
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314 | /****************************************************************/ |
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315 | ///////////////////////////////////////////////////////////// |
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316 | //// Functions for Cube class |
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317 | ///////////////////////////////////////////////////////////// |
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318 | |
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319 | Cube::Cube(long size){ |
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320 | // need error handling in case size<0 !!! |
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321 | if(size<0) |
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322 | duchampError("Cube(size)","Negative size -- could not define Cube"); |
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323 | else{ |
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324 | if(size>0){ |
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325 | this->array = new float[size]; |
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326 | this->recon = new float[size]; |
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327 | } |
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328 | this->numPixels = size; |
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329 | this->axisDim = new long[2]; |
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330 | this->numDim = 3; |
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331 | this->reconExists = false; |
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332 | } |
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333 | } |
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334 | //-------------------------------------------------------------------- |
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335 | |
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336 | Cube::Cube(long *dimensions){ |
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337 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
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338 | int imsize = dimensions[0] * dimensions[1]; |
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339 | if((size<0) || (imsize<0) ) |
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340 | duchampError("Cube(dimArray)","Negative size -- could not define Cube"); |
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341 | else{ |
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342 | this->numPixels = size; |
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343 | if(size>0){ |
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344 | this->array = new float[size]; |
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345 | this->detectMap = new short[imsize]; |
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346 | if(this->par.getFlagATrous()) |
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347 | this->recon = new float[size]; |
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348 | if(this->par.getFlagBaseline()) |
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349 | this->baseline = new float[size]; |
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350 | } |
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351 | this->numDim = 3; |
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352 | this->axisDim = new long[3]; |
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353 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
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354 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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355 | this->reconExists = false; |
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356 | } |
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357 | } |
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358 | //-------------------------------------------------------------------- |
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359 | |
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360 | Cube::~Cube() |
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361 | { |
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362 | delete [] detectMap; |
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363 | if(this->par.getFlagATrous()) delete [] recon; |
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364 | if(this->par.getFlagBaseline()) delete [] baseline; |
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365 | } |
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366 | //-------------------------------------------------------------------- |
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367 | |
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368 | void Cube::initialiseCube(long *dimensions) |
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369 | { |
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370 | /** |
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371 | * Cube::initialiseCube(long *dim) |
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372 | * A function that defines the sizes of all the necessary |
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373 | * arrays in the Cube class. |
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374 | * It also defines the values of the axis dimensions. |
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375 | * This is done with the WCS in the FitsHeader class, so the |
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376 | * WCS needs to be good and have three axes. |
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377 | */ |
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378 | |
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379 | int lng,lat,spc,size,imsize; |
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380 | |
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381 | if(this->head.isWCS() && (this->head.getWCS()->naxis>=3)){ |
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382 | // if there is a WCS and there is at least 3 axes |
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383 | lng = this->head.getWCS()->lng; |
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384 | lat = this->head.getWCS()->lat; |
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385 | spc = this->head.getWCS()->spec; |
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386 | } |
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387 | else{ |
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388 | // just take dimensions[] at face value |
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389 | lng = 0; |
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390 | lat = 1; |
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391 | spc = 2; |
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392 | } |
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393 | size = dimensions[lng] * dimensions[lat] * dimensions[spc]; |
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394 | imsize = dimensions[lng] * dimensions[lat]; |
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395 | |
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396 | |
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397 | if((size<0) || (imsize<0) ) |
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398 | duchampError("Cube::initialiseCube(dimArray)", |
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399 | "Negative size -- could not define Cube.\n"); |
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400 | else{ |
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401 | this->numPixels = size; |
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402 | if(size>0){ |
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403 | this->array = new float[size]; |
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404 | this->detectMap = new short[imsize]; |
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405 | if(this->par.getFlagATrous()) |
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406 | this->recon = new float[size]; |
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407 | if(this->par.getFlagBaseline()) |
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408 | this->baseline = new float[size]; |
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409 | } |
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410 | this->numDim = 3; |
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411 | this->axisDim = new long[3]; |
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412 | this->axisDim[0] = dimensions[lng]; |
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413 | this->axisDim[1] = dimensions[lat]; |
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414 | this->axisDim[2] = dimensions[spc]; |
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415 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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416 | this->reconExists = false; |
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417 | } |
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418 | } |
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419 | //-------------------------------------------------------------------- |
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420 | |
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421 | int Cube::getopts(int argc, char ** argv) |
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422 | { |
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423 | /** |
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424 | * Cube::getopt |
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425 | * A front-end to read in the command-line options, |
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426 | * and then read in the correct parameters to the cube->par |
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427 | */ |
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428 | |
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429 | int returnValue; |
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430 | if(argc==1){ |
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431 | std::cout << ERR_USAGE_MSG; |
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432 | returnValue = FAILURE; |
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433 | } |
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434 | else { |
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435 | string file; |
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436 | Param *par = new Param; |
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437 | char c; |
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438 | while( ( c = getopt(argc,argv,"p:f:hv") )!=-1){ |
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439 | switch(c) { |
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440 | case 'p': |
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441 | file = optarg; |
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442 | if(this->readParam(file)==FAILURE){ |
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443 | stringstream errmsg; |
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444 | errmsg << "Could not open parameter file " << file << ".\n"; |
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445 | duchampError("Duchamp",errmsg.str()); |
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446 | returnValue = FAILURE; |
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447 | } |
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448 | else returnValue = SUCCESS; |
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449 | break; |
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450 | case 'f': |
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451 | file = optarg; |
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452 | par->setImageFile(file); |
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453 | this->saveParam(*par); |
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454 | returnValue = SUCCESS; |
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455 | break; |
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456 | case 'v': |
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457 | std::cout << PROGNAME << " version " << VERSION << std::endl; |
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458 | returnValue = FAILURE; |
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459 | break; |
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460 | case 'h': |
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461 | default : |
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462 | std::cout << ERR_USAGE_MSG; |
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463 | returnValue = FAILURE; |
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464 | break; |
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465 | } |
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466 | } |
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467 | delete par; |
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468 | } |
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469 | return returnValue; |
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470 | } |
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471 | //-------------------------------------------------------------------- |
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472 | |
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473 | void Cube::saveArray(float *input, long size){ |
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474 | if(size != this->numPixels){ |
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475 | stringstream errmsg; |
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476 | errmsg << "Input array different size to existing array (" |
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477 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
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478 | duchampError("Cube::saveArray",errmsg.str()); |
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479 | } |
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480 | else { |
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481 | if(this->numPixels>0) delete [] array; |
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482 | this->numPixels = size; |
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483 | this->array = new float[size]; |
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484 | for(int i=0;i<size;i++) this->array[i] = input[i]; |
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485 | } |
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486 | } |
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487 | //-------------------------------------------------------------------- |
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488 | |
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489 | void Cube::saveRecon(float *input, long size){ |
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490 | if(size != this->numPixels){ |
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491 | stringstream errmsg; |
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492 | errmsg << "Input array different size to existing array (" |
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493 | << size << " cf. " << this->numPixels << "). Cannot save.\n"; |
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494 | duchampError("Cube::saveRecon",errmsg.str()); |
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495 | } |
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496 | else { |
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497 | if(this->numPixels>0) delete [] this->recon; |
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498 | this->numPixels = size; |
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499 | this->recon = new float[size]; |
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500 | for(int i=0;i<size;i++) this->recon[i] = input[i]; |
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501 | this->reconExists = true; |
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502 | } |
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503 | } |
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504 | //-------------------------------------------------------------------- |
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505 | |
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506 | void Cube::getRecon(float *output){ |
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507 | // Need check for change in number of pixels! |
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508 | long size = this->numPixels; |
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509 | for(int i=0;i<size;i++){ |
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510 | if(this->reconExists) output[i] = this->recon[i]; |
---|
511 | else output[i] = 0.; |
---|
512 | } |
---|
513 | } |
---|
514 | //-------------------------------------------------------------------- |
---|
515 | |
---|
516 | void Cube::removeMW() |
---|
517 | { |
---|
518 | if(this->par.getFlagMW()){ |
---|
519 | for(int pix=0;pix<this->axisDim[0]*this->axisDim[1];pix++){ |
---|
520 | for(int z=0;z<this->axisDim[2];z++){ |
---|
521 | int pos = z*this->axisDim[0]*this->axisDim[1] + pix; |
---|
522 | if(!this->isBlank(pos) && this->par.isInMW(z)) this->array[pos]=0.; |
---|
523 | } |
---|
524 | } |
---|
525 | } |
---|
526 | } |
---|
527 | //-------------------------------------------------------------------- |
---|
528 | |
---|
529 | void Cube::calcObjectWCSparams() |
---|
530 | { |
---|
531 | /** |
---|
532 | * Cube::calcObjectWCSparams() |
---|
533 | * A function that calculates the WCS parameters for each object in the |
---|
534 | * cube's list of detections. |
---|
535 | * Each object gets an ID number set (just the order in the list), and if |
---|
536 | * the WCS is good, the WCS paramters are calculated. |
---|
537 | */ |
---|
538 | |
---|
539 | for(int i=0; i<this->objectList.size();i++){ |
---|
540 | this->objectList[i].setID(i+1); |
---|
541 | this->objectList[i].calcWCSparams(this->head); |
---|
542 | this->objectList[i].setPeakSNR( (this->objectList[i].getPeakFlux() - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
543 | } |
---|
544 | |
---|
545 | |
---|
546 | } |
---|
547 | //-------------------------------------------------------------------- |
---|
548 | |
---|
549 | void Cube::sortDetections() |
---|
550 | { |
---|
551 | /** |
---|
552 | * Cube::sortDetections() |
---|
553 | * A front end to the sort-by functions. |
---|
554 | * If there is a good WCS, the detection list is sorted by velocity. |
---|
555 | * Otherwise, it is sorted by increasing z-pixel value. |
---|
556 | * The ID numbers are then re-calculated. |
---|
557 | */ |
---|
558 | |
---|
559 | if(this->head.isWCS()) SortByVel(this->objectList); |
---|
560 | else SortByZ(this->objectList); |
---|
561 | for(int i=0; i<this->objectList.size();i++) this->objectList[i].setID(i+1); |
---|
562 | |
---|
563 | } |
---|
564 | //-------------------------------------------------------------------- |
---|
565 | |
---|
566 | void Cube::updateDetectMap() |
---|
567 | { |
---|
568 | /** |
---|
569 | * Cube::updateDetectMap() |
---|
570 | * A function that, for each detected object in the cube's list, increments |
---|
571 | * the cube's detection map by the required amount at each pixel. |
---|
572 | */ |
---|
573 | |
---|
574 | for(int obj=0;obj<this->objectList.size();obj++){ |
---|
575 | for(int pix=0;pix<this->objectList[obj].getSize();pix++) { |
---|
576 | int spatialPos = this->objectList[obj].getX(pix)+ |
---|
577 | this->objectList[obj].getY(pix)*this->axisDim[0]; |
---|
578 | this->detectMap[spatialPos]++; |
---|
579 | } |
---|
580 | } |
---|
581 | } |
---|
582 | //-------------------------------------------------------------------- |
---|
583 | |
---|
584 | void Cube::updateDetectMap(Detection obj) |
---|
585 | { |
---|
586 | /** |
---|
587 | * Cube::updateDetectMap(Detection) |
---|
588 | * A function that, for the given object, increments the cube's |
---|
589 | * detection map by the required amount at each pixel. |
---|
590 | */ |
---|
591 | for(int pix=0;pix<obj.getSize();pix++) { |
---|
592 | int spatialPos = obj.getX(pix)+obj.getY(pix)*this->axisDim[0]; |
---|
593 | this->detectMap[spatialPos]++; |
---|
594 | } |
---|
595 | } |
---|
596 | //-------------------------------------------------------------------- |
---|
597 | |
---|
598 | void Cube::setCubeStats() |
---|
599 | { |
---|
600 | /** |
---|
601 | * Cube::setCubeStats() |
---|
602 | * Calculates the full statistics for the cube: |
---|
603 | * mean, rms, median, madfm |
---|
604 | * Only do this if the threshold has not been defined (ie. is still 0., |
---|
605 | * its default). |
---|
606 | * Also work out the threshold and store it in the par set. |
---|
607 | * |
---|
608 | * For stats calculations, ignore BLANKs and MW channels. |
---|
609 | */ |
---|
610 | |
---|
611 | // get number of good pixels; |
---|
612 | int goodSize = 0; |
---|
613 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
614 | for(int z=0;z<this->axisDim[2];z++){ |
---|
615 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
616 | if(!this->isBlank(vox) && !this->par.isInMW(z)) goodSize++; |
---|
617 | } |
---|
618 | } |
---|
619 | float *tempArray = new float[goodSize]; |
---|
620 | |
---|
621 | goodSize=0; |
---|
622 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
623 | for(int z=0;z<this->axisDim[2];z++){ |
---|
624 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
625 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
626 | tempArray[goodSize++] = this->array[vox]; |
---|
627 | } |
---|
628 | } |
---|
629 | if(!this->reconExists){ |
---|
630 | // if there's no recon array, calculate everything from orig array |
---|
631 | this->Stats.calculate(tempArray,goodSize); |
---|
632 | } |
---|
633 | else{ |
---|
634 | // just get mean & median from orig array, and rms & madfm from recon |
---|
635 | StatsContainer<float> origStats,reconStats; |
---|
636 | origStats.calculate(tempArray,goodSize); |
---|
637 | goodSize=0; |
---|
638 | for(int p=0;p<this->axisDim[0]*this->axisDim[1];p++){ |
---|
639 | for(int z=0;z<this->axisDim[2];z++){ |
---|
640 | int vox = z * this->axisDim[0] * this->axisDim[1] + p; |
---|
641 | if(!this->isBlank(vox) && !this->par.isInMW(z)) |
---|
642 | tempArray[goodSize++] = this->array[vox] - this->recon[vox]; |
---|
643 | } |
---|
644 | } |
---|
645 | reconStats.calculate(tempArray,goodSize); |
---|
646 | |
---|
647 | // Get the "middle" estimators from the original array. |
---|
648 | // Get the "spread" estimators from the residual (orig-recon) array |
---|
649 | this->Stats.setMean(origStats.getMean()); |
---|
650 | this->Stats.setMedian(origStats.getMedian()); |
---|
651 | this->Stats.setStddev(reconStats.getStddev()); |
---|
652 | this->Stats.setMadfm(reconStats.getMadfm()); |
---|
653 | } |
---|
654 | |
---|
655 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
656 | // If the FDR method has been requested |
---|
657 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
658 | else{ |
---|
659 | if(this->par.getFlagUserThreshold()){ |
---|
660 | // if the user has defined a threshold, set this in the StatsContainer |
---|
661 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
662 | } |
---|
663 | else{ |
---|
664 | // otherwise, calculate one based on the requested SNR cut level, and |
---|
665 | // then set the threshold parameter in the Par set. |
---|
666 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
667 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
668 | } |
---|
669 | // std::cout << "Median = " << this->Stats.getMedian() |
---|
670 | // << ", MADFM = " << this->Stats.getMadfm() |
---|
671 | // << ", Robust Threshold = " |
---|
672 | // << this->Stats.getMedian() + |
---|
673 | // this->par.getCut()*madfmToSigma(this->Stats.getMadfm()) << std::endl; |
---|
674 | // std::cout << "Mean = " << this->Stats.getMean() |
---|
675 | // << ", Sigma = " << this->Stats.getStddev() |
---|
676 | // << ", Threshold = " |
---|
677 | // << this->Stats.getMean() + |
---|
678 | // this->par.getCut()*this->Stats.getStddev() |
---|
679 | // << std::endl; |
---|
680 | } |
---|
681 | std::cout << "Using "; |
---|
682 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
683 | std::cout << "flux threshold of: "; |
---|
684 | float thresh = this->Stats.getThreshold(); |
---|
685 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
686 | std::cout << thresh << std::endl; |
---|
687 | |
---|
688 | } |
---|
689 | //-------------------------------------------------------------------- |
---|
690 | |
---|
691 | int Cube::setupFDR() |
---|
692 | { |
---|
693 | /** |
---|
694 | * Cube::setupFDR() |
---|
695 | * Determines the critical Prob value for the False Discovery Rate |
---|
696 | * detection routine. All pixels with Prob less than this value will |
---|
697 | * be considered detections. |
---|
698 | * The Prob here is the probability, assuming a Normal distribution, of |
---|
699 | * obtaining a value as high or higher than the pixel value (ie. only the |
---|
700 | * positive tail of the PDF) |
---|
701 | */ |
---|
702 | |
---|
703 | // first calculate p-value for each pixel -- assume Gaussian for now. |
---|
704 | |
---|
705 | float *orderedP = new float[this->numPixels]; |
---|
706 | int count = 0; |
---|
707 | float zStat; |
---|
708 | for(int pix=0; pix<this->numPixels; pix++){ |
---|
709 | |
---|
710 | if( !(this->par.isBlank(this->array[pix])) ){ |
---|
711 | // only look at non-blank pixels |
---|
712 | zStat = (this->array[pix] - this->Stats.getMiddle()) / |
---|
713 | this->Stats.getSpread(); |
---|
714 | |
---|
715 | orderedP[count++] = 0.5 * erfc(zStat/M_SQRT2); |
---|
716 | // Need the factor of 0.5 here, as we are only considering the positive |
---|
717 | // tail of the distribution. Don't care about negative detections. |
---|
718 | } |
---|
719 | } |
---|
720 | |
---|
721 | // now order them |
---|
722 | sort(orderedP,0,count); |
---|
723 | |
---|
724 | // now find the maximum P value. |
---|
725 | int max = 0; |
---|
726 | float cN = 0.; |
---|
727 | int psfCtr; |
---|
728 | int numVox = int(this->par.getBeamSize()) * 2; |
---|
729 | // why beamSize*2? we are doing this in 3D, so spectrally assume just the |
---|
730 | // neighbouring channels are correlated, but spatially all those within |
---|
731 | // the beam, so total number of voxels is 2*beamSize |
---|
732 | for(psfCtr=1;psfCtr<=numVox;(psfCtr)++) |
---|
733 | cN += 1./float(psfCtr); |
---|
734 | |
---|
735 | for(int loopCtr=0;loopCtr<count;loopCtr++) { |
---|
736 | if( orderedP[loopCtr] < |
---|
737 | (double(loopCtr+1)*this->par.getAlpha()/(cN * double(count))) ) { |
---|
738 | max = loopCtr; |
---|
739 | } |
---|
740 | } |
---|
741 | |
---|
742 | this->Stats.setPThreshold( orderedP[max] ); |
---|
743 | |
---|
744 | delete [] orderedP; |
---|
745 | |
---|
746 | // Find real value of the P threshold by finding the inverse of the |
---|
747 | // error function -- root finding with brute force technique |
---|
748 | // (relatively slow, but we only do it once). |
---|
749 | zStat = 0; |
---|
750 | float deltaZ = 0.1; |
---|
751 | float tolerance = 1.e-6; |
---|
752 | float zeroP = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
753 | do{ |
---|
754 | zStat+=deltaZ; |
---|
755 | if((zeroP * (erfc(zStat/M_SQRT2)-this->Stats.getPThreshold()))<0.){ |
---|
756 | zStat-=deltaZ; |
---|
757 | deltaZ/=2.; |
---|
758 | } |
---|
759 | }while(deltaZ>tolerance); |
---|
760 | this->Stats.setThreshold( zStat*this->Stats.getSpread() + |
---|
761 | this->Stats.getMiddle() ); |
---|
762 | |
---|
763 | } |
---|
764 | //-------------------------------------------------------------------- |
---|
765 | |
---|
766 | float Cube::enclosedFlux(Detection obj) |
---|
767 | { |
---|
768 | /** |
---|
769 | * float Cube::enclosedFlux(Detection obj) |
---|
770 | * A function to calculate the flux enclosed by the range |
---|
771 | * of pixels detected in the object obj (not necessarily all |
---|
772 | * pixels will have been detected). |
---|
773 | */ |
---|
774 | obj.calcParams(); |
---|
775 | int xsize = obj.getXmax()-obj.getXmin()+1; |
---|
776 | int ysize = obj.getYmax()-obj.getYmin()+1; |
---|
777 | int zsize = obj.getZmax()-obj.getZmin()+1; |
---|
778 | vector <float> fluxArray(xsize*ysize*zsize,0.); |
---|
779 | for(int x=0;x<xsize;x++){ |
---|
780 | for(int y=0;y<ysize;y++){ |
---|
781 | for(int z=0;z<zsize;z++){ |
---|
782 | fluxArray[x+y*xsize+z*ysize*xsize] = |
---|
783 | this->getPixValue(x+obj.getXmin(), |
---|
784 | y+obj.getYmin(), |
---|
785 | z+obj.getZmin()); |
---|
786 | if(this->par.getFlagNegative()) |
---|
787 | fluxArray[x+y*xsize+z*ysize*xsize] *= -1.; |
---|
788 | } |
---|
789 | } |
---|
790 | } |
---|
791 | float sum = 0.; |
---|
792 | for(int i=0;i<fluxArray.size();i++) |
---|
793 | if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i]; |
---|
794 | return sum; |
---|
795 | } |
---|
796 | //-------------------------------------------------------------------- |
---|
797 | |
---|
798 | void Cube::setupColumns() |
---|
799 | { |
---|
800 | /** |
---|
801 | * Cube::setupColumns() |
---|
802 | * A front-end to the two setup routines in columns.cc. |
---|
803 | */ |
---|
804 | this->calcObjectWCSparams(); |
---|
805 | // need this as the colSet functions use vel, RA, Dec, etc... |
---|
806 | |
---|
807 | this->fullCols.clear(); |
---|
808 | this->fullCols = getFullColSet(this->objectList, this->head); |
---|
809 | |
---|
810 | this->logCols.clear(); |
---|
811 | this->logCols = getLogColSet(this->objectList, this->head); |
---|
812 | |
---|
813 | int vel,fpeak,fint,pos,xyz,temp,snr; |
---|
814 | vel = fullCols[VEL].getPrecision(); |
---|
815 | fpeak = fullCols[FPEAK].getPrecision(); |
---|
816 | snr = fullCols[SNRPEAK].getPrecision(); |
---|
817 | xyz = fullCols[X].getPrecision(); |
---|
818 | if(temp=fullCols[Y].getPrecision() > xyz) xyz = temp; |
---|
819 | if(temp=fullCols[Z].getPrecision() > xyz) xyz = temp; |
---|
820 | if(this->head.isWCS()) fint = fullCols[FINT].getPrecision(); |
---|
821 | else fint = fullCols[FTOT].getPrecision(); |
---|
822 | pos = fullCols[WRA].getPrecision(); |
---|
823 | if(temp=fullCols[WDEC].getPrecision() > pos) pos = temp; |
---|
824 | |
---|
825 | for(int obj=0;obj<this->objectList.size();obj++){ |
---|
826 | this->objectList[obj].setVelPrec(vel); |
---|
827 | this->objectList[obj].setFpeakPrec(fpeak); |
---|
828 | this->objectList[obj].setXYZPrec(xyz); |
---|
829 | this->objectList[obj].setPosPrec(pos); |
---|
830 | this->objectList[obj].setFintPrec(fint); |
---|
831 | this->objectList[obj].setSNRPrec(snr); |
---|
832 | } |
---|
833 | |
---|
834 | } |
---|
835 | //-------------------------------------------------------------------- |
---|
836 | |
---|
837 | bool Cube::objAtSpatialEdge(Detection obj) |
---|
838 | { |
---|
839 | /** |
---|
840 | * bool Cube::objAtSpatialEdge() |
---|
841 | * A function to test whether the object obj |
---|
842 | * lies at the edge of the cube's spatial field -- |
---|
843 | * either at the boundary, or next to BLANKs |
---|
844 | */ |
---|
845 | |
---|
846 | bool atEdge = false; |
---|
847 | |
---|
848 | int pix = 0; |
---|
849 | while(!atEdge && pix<obj.getSize()){ |
---|
850 | // loop over each pixel in the object, until we find an edge pixel. |
---|
851 | Voxel vox = obj.getPixel(pix); |
---|
852 | for(int dx=-1;dx<=1;dx+=2){ |
---|
853 | if(((vox.getX()+dx)<0) || ((vox.getX()+dx)>=this->axisDim[0])) |
---|
854 | atEdge = true; |
---|
855 | else if(this->isBlank(vox.getX()+dx,vox.getY(),vox.getZ())) |
---|
856 | atEdge = true; |
---|
857 | } |
---|
858 | for(int dy=-1;dy<=1;dy+=2){ |
---|
859 | if(((vox.getY()+dy)<0) || ((vox.getY()+dy)>=this->axisDim[1])) |
---|
860 | atEdge = true; |
---|
861 | else if(this->isBlank(vox.getX(),vox.getY()+dy,vox.getZ())) |
---|
862 | atEdge = true; |
---|
863 | } |
---|
864 | pix++; |
---|
865 | } |
---|
866 | |
---|
867 | return atEdge; |
---|
868 | } |
---|
869 | //-------------------------------------------------------------------- |
---|
870 | |
---|
871 | bool Cube::objAtSpectralEdge(Detection obj) |
---|
872 | { |
---|
873 | /** |
---|
874 | * bool Cube::objAtSpectralEdge() |
---|
875 | * A function to test whether the object obj |
---|
876 | * lies at the edge of the cube's spectral extent -- |
---|
877 | * either at the boundary, or next to BLANKs |
---|
878 | */ |
---|
879 | |
---|
880 | bool atEdge = false; |
---|
881 | |
---|
882 | int pix = 0; |
---|
883 | while(!atEdge && pix<obj.getSize()){ |
---|
884 | // loop over each pixel in the object, until we find an edge pixel. |
---|
885 | Voxel vox = obj.getPixel(pix); |
---|
886 | for(int dz=-1;dz<=1;dz+=2){ |
---|
887 | if(((vox.getZ()+dz)<0) || ((vox.getZ()+dz)>=this->axisDim[2])) |
---|
888 | atEdge = true; |
---|
889 | else if(this->isBlank(vox.getX(),vox.getY(),vox.getZ()+dz)) |
---|
890 | atEdge = true; |
---|
891 | } |
---|
892 | pix++; |
---|
893 | } |
---|
894 | |
---|
895 | return atEdge; |
---|
896 | } |
---|
897 | //-------------------------------------------------------------------- |
---|
898 | |
---|
899 | void Cube::setObjectFlags() |
---|
900 | { |
---|
901 | /** |
---|
902 | * void Cube::setObjectFlags() |
---|
903 | * A function to set any warning flags for all the detected objects |
---|
904 | * associated with the cube. |
---|
905 | * Flags to be looked for: |
---|
906 | * * Negative enclosed flux (N) |
---|
907 | * * Object at edge of field (E) |
---|
908 | */ |
---|
909 | |
---|
910 | for(int i=0;i<this->objectList.size();i++){ |
---|
911 | |
---|
912 | if( this->enclosedFlux(this->objectList[i]) < 0. ) |
---|
913 | this->objectList[i].addToFlagText("N"); |
---|
914 | |
---|
915 | if( this->objAtSpatialEdge(this->objectList[i]) ) |
---|
916 | this->objectList[i].addToFlagText("E"); |
---|
917 | |
---|
918 | if( this->objAtSpectralEdge(this->objectList[i]) ) |
---|
919 | this->objectList[i].addToFlagText("S"); |
---|
920 | |
---|
921 | } |
---|
922 | |
---|
923 | } |
---|
924 | //-------------------------------------------------------------------- |
---|
925 | |
---|
926 | void Cube::plotBlankEdges() |
---|
927 | { |
---|
928 | if(this->par.drawBlankEdge()){ |
---|
929 | int colour; |
---|
930 | cpgqci(&colour); |
---|
931 | cpgsci(MAGENTA); |
---|
932 | drawBlankEdges(this->array,this->axisDim[0],this->axisDim[1],this->par); |
---|
933 | cpgsci(colour); |
---|
934 | } |
---|
935 | } |
---|