1 | // ----------------------------------------------------------------------- |
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2 | // cubes.cc: Member functions for the DataArray, Cube and Image classes. |
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3 | // ----------------------------------------------------------------------- |
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4 | // Copyright (C) 2006, Matthew Whiting, ATNF |
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5 | // |
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6 | // This program is free software; you can redistribute it and/or modify it |
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7 | // under the terms of the GNU General Public License as published by the |
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8 | // Free Software Foundation; either version 2 of the License, or (at your |
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9 | // option) any later version. |
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10 | // |
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11 | // Duchamp is distributed in the hope that it will be useful, but WITHOUT |
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12 | // ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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13 | // FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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14 | // for more details. |
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15 | // |
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16 | // You should have received a copy of the GNU General Public License |
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17 | // along with Duchamp; if not, write to the Free Software Foundation, |
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18 | // Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA |
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19 | // |
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20 | // Correspondence concerning Duchamp may be directed to: |
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21 | // Internet email: Matthew.Whiting [at] atnf.csiro.au |
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22 | // Postal address: Dr. Matthew Whiting |
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23 | // Australia Telescope National Facility, CSIRO |
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24 | // PO Box 76 |
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25 | // Epping NSW 1710 |
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26 | // AUSTRALIA |
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27 | // ----------------------------------------------------------------------- |
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28 | #include <unistd.h> |
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29 | #include <iostream> |
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30 | #include <iomanip> |
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31 | #include <vector> |
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32 | #include <algorithm> |
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33 | #include <string> |
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34 | #include <math.h> |
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35 | |
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36 | #include <wcslib/wcs.h> |
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37 | |
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38 | #include <duchamp/pgheader.hh> |
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39 | |
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40 | #include <duchamp/duchamp.hh> |
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41 | #include <duchamp/param.hh> |
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42 | #include <duchamp/fitsHeader.hh> |
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43 | #include <duchamp/Cubes/cubes.hh> |
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44 | #include <duchamp/PixelMap/Voxel.hh> |
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45 | #include <duchamp/PixelMap/Object3D.hh> |
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46 | #include <duchamp/Detection/detection.hh> |
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47 | #include <duchamp/Outputs/columns.hh> |
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48 | #include <duchamp/Detection/finders.hh> |
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49 | #include <duchamp/Utils/utils.hh> |
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50 | #include <duchamp/Utils/feedback.hh> |
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51 | #include <duchamp/Utils/mycpgplot.hh> |
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52 | #include <duchamp/Utils/Statistics.hh> |
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53 | #include <duchamp/FitsIO/DuchampBeam.hh> |
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54 | #include <duchamp/FitsIO/WriteReconArray.hh> |
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55 | #include <duchamp/FitsIO/WriteSmoothArray.hh> |
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56 | #include <duchamp/FitsIO/WriteMaskArray.hh> |
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57 | #include <duchamp/FitsIO/WriteMomentMapArray.hh> |
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58 | #include <duchamp/FitsIO/WriteMomentMaskArray.hh> |
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59 | #include <duchamp/FitsIO/WriteBaselineArray.hh> |
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60 | |
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61 | using namespace mycpgplot; |
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62 | using namespace Statistics; |
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63 | using namespace PixelInfo; |
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64 | |
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65 | #ifdef TEST_DEBUG |
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66 | const bool TESTING=true; |
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67 | #else |
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68 | const bool TESTING=false; |
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69 | #endif |
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70 | |
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71 | namespace duchamp |
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72 | { |
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73 | |
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74 | using namespace Catalogues; |
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75 | |
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76 | /****************************************************************/ |
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77 | /////////////////////////////////////////////////// |
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78 | //// Functions for DataArray class: |
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79 | /////////////////////////////////////////////////// |
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80 | |
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81 | DataArray::DataArray(): |
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82 | numDim(0),axisDimAllocated(false),numPixels(0),array(0),arrayAllocated(false) |
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83 | { |
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84 | /// Fundamental constructor for DataArray. |
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85 | /// Number of dimensions and pixels are set to 0. Nothing else allocated. |
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86 | |
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87 | // this->numDim=0; |
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88 | // this->numPixels=0; |
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89 | this->objectList = new std::vector<Detection>; |
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90 | // this->axisDimAllocated = false; |
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91 | // this->arrayAllocated = false; |
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92 | } |
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93 | //-------------------------------------------------------------------- |
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94 | |
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95 | DataArray::DataArray(const DataArray &d){ |
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96 | operator=(d); |
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97 | } |
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98 | |
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99 | DataArray& DataArray::operator=(const DataArray &d){ |
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100 | if(this==&d) return *this; |
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101 | this->numDim = d.numDim; |
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102 | if(this->axisDimAllocated) delete [] this->axisDim; |
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103 | this->axisDimAllocated = d.axisDimAllocated; |
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104 | if(this->axisDimAllocated){ |
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105 | this->axisDim = new size_t[this->numDim]; |
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106 | for(size_t i=0;i<size_t(this->numDim);i++) this->axisDim[i] = d.axisDim[i]; |
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107 | } |
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108 | this->numPixels = d.numPixels; |
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109 | if(this->arrayAllocated) delete [] this->array; |
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110 | this->arrayAllocated = d.arrayAllocated; |
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111 | if(this->arrayAllocated) { |
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112 | this->array = new float[this->numPixels]; |
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113 | for(size_t i=0;i<size_t(this->numPixels);i++) this->array[i] = d.array[i]; |
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114 | } |
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115 | this->objectList = d.objectList; |
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116 | this->par = d.par; |
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117 | this->Stats = d.Stats; |
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118 | return *this; |
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119 | } |
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120 | |
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121 | |
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122 | DataArray::DataArray(short int nDim){ |
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123 | /// @details |
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124 | /// N-dimensional constructor for DataArray. |
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125 | /// Number of dimensions defined, and dimension array allocated. |
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126 | /// Number of pixels are set to 0. |
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127 | /// \param nDim Number of dimensions. |
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128 | |
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129 | this->axisDimAllocated = false; |
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130 | this->arrayAllocated = false; |
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131 | if(nDim>0){ |
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132 | this->axisDim = new size_t[nDim]; |
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133 | this->axisDimAllocated = true; |
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134 | } |
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135 | this->numDim=nDim; |
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136 | this->numPixels=0; |
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137 | this->objectList = new std::vector<Detection>; |
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138 | } |
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139 | //-------------------------------------------------------------------- |
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140 | |
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141 | DataArray::DataArray(short int nDim, size_t size){ |
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142 | /// @details |
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143 | /// N-dimensional constructor for DataArray. |
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144 | /// Number of dimensions and number of pixels defined. |
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145 | /// Arrays allocated based on these values. |
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146 | /// \param nDim Number of dimensions. |
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147 | /// \param size Number of pixels. |
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148 | /// |
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149 | /// Note that we can assign values to the dimension array. |
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150 | |
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151 | this->axisDimAllocated = false; |
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152 | this->arrayAllocated = false; |
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153 | if(nDim<0){ |
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154 | DUCHAMPERROR("DataArray(nDim,size)", "Negative number of dimensions: could not define DataArray"); |
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155 | } |
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156 | else { |
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157 | this->array = new float[size]; |
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158 | this->arrayAllocated = true; |
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159 | this->numPixels = size; |
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160 | if(nDim>0){ |
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161 | this->axisDim = new size_t[nDim]; |
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162 | this->axisDimAllocated = true; |
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163 | } |
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164 | this->numDim = nDim; |
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165 | } |
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166 | this->objectList = new std::vector<Detection>; |
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167 | } |
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168 | //-------------------------------------------------------------------- |
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169 | |
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170 | DataArray::DataArray(short int nDim, size_t *dimensions) |
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171 | { |
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172 | /// @details |
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173 | /// Most robust constructor for DataArray. |
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174 | /// Number and sizes of dimensions are defined, and hence the number of |
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175 | /// pixels. Arrays allocated based on these values. |
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176 | /// \param nDim Number of dimensions. |
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177 | /// \param dimensions Array giving sizes of dimensions. |
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178 | |
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179 | this->axisDimAllocated = false; |
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180 | this->arrayAllocated = false; |
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181 | if(nDim<0){ |
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182 | DUCHAMPERROR("DataArray(nDim,dimArray)", "Negative number of dimensions: could not define DataArray"); |
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183 | } |
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184 | else { |
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185 | int size = dimensions[0]; |
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186 | for(int i=1;i<nDim;i++) size *= dimensions[i]; |
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187 | if(size<0){ |
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188 | DUCHAMPERROR("DataArray(nDim,dimArray)", "Negative size: could not define DataArray"); |
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189 | } |
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190 | else{ |
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191 | this->numPixels = size; |
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192 | if(size>0){ |
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193 | this->array = new float[size]; |
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194 | this->arrayAllocated = true; |
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195 | } |
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196 | this->numDim=nDim; |
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197 | if(nDim>0){ |
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198 | this->axisDim = new size_t[nDim]; |
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199 | this->axisDimAllocated = true; |
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200 | } |
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201 | for(int i=0;i<nDim;i++) this->axisDim[i] = dimensions[i]; |
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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 | |
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207 | DataArray::~DataArray() |
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208 | { |
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209 | /// @details |
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210 | /// Destructor -- arrays deleted if they have been allocated, and the |
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211 | /// object list is deleted. |
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212 | |
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213 | if(this->numPixels>0 && this->arrayAllocated){ |
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214 | delete [] this->array; |
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215 | this->arrayAllocated = false; |
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216 | } |
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217 | if(this->numDim>0 && this->axisDimAllocated){ |
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218 | delete [] this->axisDim; |
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219 | this->axisDimAllocated = false; |
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220 | } |
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221 | delete this->objectList; |
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222 | } |
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223 | //-------------------------------------------------------------------- |
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224 | //-------------------------------------------------------------------- |
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225 | |
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226 | void DataArray::getDim(size_t &x, size_t &y, size_t &z) |
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227 | { |
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228 | /// @details |
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229 | /// The sizes of the first three dimensions (if they exist) are returned. |
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230 | /// \param x The first dimension. Defaults to 0 if numDim \f$\le\f$ 0. |
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231 | /// \param y The second dimension. Defaults to 1 if numDim \f$\le\f$ 1. |
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232 | /// \param z The third dimension. Defaults to 1 if numDim \f$\le\f$ 2. |
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233 | |
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234 | if(this->numDim>0) x=this->axisDim[0]; |
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235 | else x=0; |
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236 | if(this->numDim>1) y=this->axisDim[1]; |
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237 | else y=1; |
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238 | if(this->numDim>2) z=this->axisDim[2]; |
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239 | else z=1; |
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240 | } |
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241 | //-------------------------------------------------------------------- |
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242 | |
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243 | void DataArray::getDimArray(size_t *output) |
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244 | { |
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245 | /// @details |
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246 | /// The axisDim array is written to output. This needs to be defined |
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247 | /// beforehand: no checking is done on the memory. |
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248 | /// \param output The array that is written to. |
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249 | |
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250 | for(int i=0;i<this->numDim;i++) output[i] = this->axisDim[i]; |
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251 | } |
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252 | //-------------------------------------------------------------------- |
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253 | |
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254 | void DataArray::getArray(float *output) |
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255 | { |
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256 | /// @details |
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257 | /// The pixel value array is written to output. This needs to be defined |
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258 | /// beforehand: no checking is done on the memory. |
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259 | /// \param output The array that is written to. |
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260 | |
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261 | for(size_t i=0;i<this->numPixels;i++) output[i] = this->array[i]; |
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262 | } |
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263 | //-------------------------------------------------------------------- |
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264 | |
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265 | void DataArray::saveArray(float *input, size_t size) |
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266 | { |
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267 | /// @details |
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268 | /// Saves the array in input to the pixel array DataArray::array. |
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269 | /// The size of the array given must be the same as the current number of |
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270 | /// pixels, else an error message is returned and nothing is done. |
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271 | /// \param input The array of values to be saved. |
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272 | /// \param size The size of input. |
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273 | |
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274 | if(size != this->numPixels){ |
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275 | DUCHAMPERROR("DataArray::saveArray", "Input array different size to existing array. Cannot save."); |
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276 | } |
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277 | else { |
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278 | if(this->numPixels>0 && this->arrayAllocated) delete [] this->array; |
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279 | this->numPixels = size; |
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280 | this->array = new float[size]; |
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281 | this->arrayAllocated = true; |
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282 | for(size_t i=0;i<size;i++) this->array[i] = input[i]; |
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283 | } |
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284 | } |
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285 | //-------------------------------------------------------------------- |
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286 | |
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287 | void DataArray::addObject(Detection &object) |
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288 | { |
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289 | /// \param object The object to be added to the object list. |
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290 | |
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291 | // objectList is a vector, so just use push_back() |
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292 | this->objectList->push_back(object); |
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293 | } |
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294 | //-------------------------------------------------------------------- |
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295 | |
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296 | void DataArray::addObjectList(std::vector <Detection> &newlist) |
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297 | { |
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298 | /// \param newlist The list of objects to be added to the object list. |
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299 | |
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300 | std::vector<Detection>::iterator obj; |
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301 | for(obj=newlist.begin();obj<newlist.end();obj++) this->objectList->push_back(*obj); |
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302 | } |
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303 | //-------------------------------------------------------------------- |
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304 | |
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305 | void DataArray::mergeIntoList(Detection &object) |
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306 | { |
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307 | /// \param object The object to be merged into the list. If the |
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308 | /// object is judged to be near to another already in the list, it |
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309 | /// is merged to that object. If not, it is added. |
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310 | |
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311 | duchamp::mergeIntoList(object, *this->objectList, this->par); |
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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 | bool DataArray::isDetection(float value) |
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317 | { |
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318 | /// @details |
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319 | /// Is a given value a detection, based on the statistics in the |
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320 | /// DataArray's StatsContainer? |
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321 | /// \param value The pixel value to test. |
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322 | |
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323 | if(par.isBlank(value)) return false; |
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324 | else return Stats.isDetection(value); |
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325 | } |
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326 | //-------------------------------------------------------------------- |
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327 | |
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328 | bool DataArray::isDetection(size_t voxel) |
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329 | { |
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330 | /// @details |
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331 | /// Is a given pixel a detection, based on the statistics in the |
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332 | /// DataArray's StatsContainer? |
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333 | /// If the pixel lies outside the valid range for the data array, return false. |
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334 | /// \param voxel Location of the DataArray's pixel to be tested. |
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335 | |
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336 | if(voxel>this->numPixels) return false; |
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337 | else if(par.isBlank(this->array[voxel])) return false; |
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338 | else return Stats.isDetection(this->array[voxel]); |
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339 | } |
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340 | //-------------------------------------------------------------------- |
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341 | |
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342 | std::ostream& operator<< ( std::ostream& theStream, DataArray &array) |
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343 | { |
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344 | /// @details |
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345 | /// A way to print out the pixel coordinates & flux values of the |
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346 | /// list of detected objects belonging to the DataArray. |
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347 | /// These are formatted nicely according to the << operator for Detection, |
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348 | /// with a line indicating the number of detections at the start. |
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349 | /// \param theStream The ostream object to which the output should be sent. |
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350 | /// \param array The DataArray containing the list of objects. |
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351 | |
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352 | for(int i=0;i<array.numDim;i++){ |
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353 | if(i>0) theStream<<"x"; |
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354 | theStream<<array.axisDim[i]; |
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355 | } |
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356 | theStream<<std::endl; |
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357 | |
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358 | theStream<<"Threshold\tmiddle\tspread\trobust\n" << array.stats().getThreshold() << "\t"; |
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359 | if(array.pars().getFlagUserThreshold()) |
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360 | theStream << "0.0000\t" << array.stats().getThreshold() << "\t"; |
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361 | else |
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362 | theStream << array.stats().getMiddle() << " " << array.stats().getSpread() << "\t"; |
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363 | theStream << array.stats().getRobust()<<"\n"; |
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364 | |
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365 | theStream<<array.objectList->size()<<" detections:\n--------------\n"; |
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366 | std::vector<Detection>::iterator obj; |
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367 | for(obj=array.objectList->begin();obj<array.objectList->end();obj++){ |
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368 | theStream << "Detection #" << obj->getID()<<std::endl; |
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369 | Detection *newobj = new Detection; |
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370 | *newobj = *obj; |
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371 | newobj->addOffsets(); |
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372 | theStream<<*newobj; |
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373 | delete newobj; |
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374 | } |
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375 | theStream<<"--------------\n"; |
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376 | return theStream; |
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377 | } |
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378 | |
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379 | /****************************************************************/ |
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380 | ///////////////////////////////////////////////////////////// |
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381 | //// Functions for Cube class |
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382 | ///////////////////////////////////////////////////////////// |
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383 | |
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384 | Cube::Cube(): |
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385 | DataArray(), recon(0), reconExists(false), detectMap(0), baseline(0), reconAllocated(false), baselineAllocated(false) |
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386 | { |
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387 | /// @details |
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388 | /// Basic Constructor for Cube class. |
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389 | /// numDim set to 3, but numPixels to 0 and all bool flags to false. |
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390 | /// No allocation done. |
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391 | |
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392 | numDim=3; |
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393 | } |
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394 | //-------------------------------------------------------------------- |
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395 | |
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396 | Cube::Cube(size_t size) |
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397 | { |
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398 | /// @details |
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399 | /// Alternative Cube constructor, where size is given but not individual |
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400 | /// dimensions. Arrays are allocated as appropriate (according to the |
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401 | /// relevant flags in Param set), but the Cube::axisDim array is not. |
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402 | |
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403 | this->reconAllocated = false; |
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404 | this->baselineAllocated = false; |
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405 | this->axisDimAllocated = false; |
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406 | this->arrayAllocated = false; |
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407 | this->numPixels = this->numDim = 0; |
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408 | this->array = new float[size]; |
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409 | this->arrayAllocated = true; |
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410 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
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411 | this->recon = new float[size]; |
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412 | this->reconAllocated = true; |
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413 | } |
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414 | if(this->par.getFlagBaseline()){ |
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415 | this->baseline = new float[size]; |
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416 | this->baselineAllocated = true; |
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417 | } |
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418 | this->numPixels = size; |
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419 | this->axisDim = new size_t[3]; |
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420 | this->axisDimAllocated = true; |
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421 | this->numDim = 3; |
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422 | this->reconExists = false; |
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423 | } |
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424 | //-------------------------------------------------------------------- |
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425 | |
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426 | Cube::Cube(size_t *dimensions) |
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427 | { |
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428 | /// Alternative Cube constructor, where sizes of dimensions are given. |
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429 | /// Arrays are allocated as appropriate (according to the |
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430 | /// relevant flags in Param set), as is the Cube::axisDim array. |
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431 | |
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432 | int size = dimensions[0] * dimensions[1] * dimensions[2]; |
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433 | int imsize = dimensions[0] * dimensions[1]; |
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434 | this->reconAllocated = false; |
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435 | this->baselineAllocated = false; |
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436 | this->axisDimAllocated = false; |
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437 | this->arrayAllocated = false; |
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438 | this->numPixels = this->numDim = 0; |
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439 | if((size<0) || (imsize<0) ){ |
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440 | DUCHAMPERROR("Cube(dimArray)","Negative size -- could not define Cube"); |
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441 | } |
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442 | else{ |
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443 | this->numPixels = size; |
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444 | if(size>0){ |
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445 | this->array = new float[size]; |
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446 | this->arrayAllocated = true; |
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447 | this->detectMap = new short[imsize]; |
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448 | if(this->par.getFlagATrous()||this->par.getFlagSmooth()){ |
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449 | this->recon = new float[size]; |
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450 | this->reconAllocated = true; |
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451 | } |
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452 | if(this->par.getFlagBaseline()){ |
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453 | this->baseline = new float[size]; |
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454 | this->baselineAllocated = true; |
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455 | } |
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456 | } |
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457 | this->numDim = 3; |
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458 | this->axisDim = new size_t[3]; |
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459 | this->axisDimAllocated = true; |
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460 | for(int i=0;i<3 ;i++) this->axisDim[i] = dimensions[i]; |
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461 | for(int i=0;i<imsize;i++) this->detectMap[i] = 0; |
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462 | this->reconExists = false; |
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463 | } |
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464 | } |
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465 | //-------------------------------------------------------------------- |
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466 | |
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467 | Cube::~Cube() |
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468 | { |
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469 | /// @details |
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470 | /// The destructor deletes the memory allocated for Cube::detectMap, and, |
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471 | /// if these have been allocated, Cube::recon and Cube::baseline. |
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472 | |
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473 | if(this->numPixels>0 && this->arrayAllocated) delete [] this->detectMap; |
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474 | if(this->reconAllocated) delete [] this->recon; |
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475 | if(this->baselineAllocated) delete [] this->baseline; |
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476 | } |
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477 | //-------------------------------------------------------------------- |
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478 | |
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479 | Cube::Cube(const Cube &c): |
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480 | DataArray(c) |
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481 | { |
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482 | this->operator=(c); |
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483 | } |
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484 | //-------------------------------------------------------------------- |
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485 | |
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486 | Cube& Cube::operator=(const Cube &c) |
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487 | { |
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488 | if(this==&c) return *this; |
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489 | if(this->arrayAllocated) delete [] this->detectMap; |
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490 | ((DataArray &) *this) = c; |
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491 | this->reconExists = c.reconExists; |
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492 | if(this->reconAllocated) delete [] this->recon; |
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493 | this->reconAllocated = c.reconAllocated; |
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494 | if(this->reconAllocated) { |
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495 | this->recon = new float[this->numPixels]; |
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496 | for(size_t i=0;i<size_t(this->numPixels);i++) this->recon[i] = c.recon[i]; |
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497 | } |
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498 | if(this->arrayAllocated){ |
---|
499 | this->detectMap = new short[this->axisDim[0]*this->axisDim[1]]; |
---|
500 | for(size_t i=0;i<size_t(this->axisDim[0]*this->axisDim[1]);i++) this->detectMap[i] = c.detectMap[i]; |
---|
501 | } |
---|
502 | if(this->baselineAllocated) delete [] this->baseline; |
---|
503 | this->baselineAllocated = c.baselineAllocated; |
---|
504 | if(this->baselineAllocated){ |
---|
505 | this->baseline = new float[this->numPixels]; |
---|
506 | for(size_t i=0;i<size_t(this->numPixels);i++) this->baseline[i] = c.baseline[i]; |
---|
507 | } |
---|
508 | this->head = c.head; |
---|
509 | this->fullCols = c.fullCols; |
---|
510 | return *this; |
---|
511 | } |
---|
512 | //-------------------------------------------------------------------- |
---|
513 | |
---|
514 | Cube* Cube::slice(Section subsection) |
---|
515 | { |
---|
516 | Cube *output = new Cube; |
---|
517 | Section thisSection; |
---|
518 | std::string nullsec=nullSection(this->numDim); |
---|
519 | if(this->par.section().isParsed()) thisSection=this->par.section(); |
---|
520 | else{ |
---|
521 | thisSection = Section(nullsec); |
---|
522 | thisSection.parse(this->axisDim, this->numDim); |
---|
523 | } |
---|
524 | |
---|
525 | subsection.parse(this->axisDim, this->numDim); |
---|
526 | if(subsection.isValid()){ |
---|
527 | output->par = this->par; |
---|
528 | output->par.section() = thisSection * subsection; |
---|
529 | output->par.setXOffset(output->par.getXOffset()+subsection.getStart(0)); |
---|
530 | output->par.setYOffset(output->par.getYOffset()+subsection.getStart(1)); |
---|
531 | output->par.setZOffset(output->par.getZOffset()+subsection.getStart(2)); |
---|
532 | output->head = this->head; |
---|
533 | // correct the reference pixel in the WCS |
---|
534 | output->head.WCS().crpix[output->head.WCS().lng] -= subsection.getStart(output->head.WCS().lng); |
---|
535 | output->head.WCS().crpix[output->head.WCS().lat] -= subsection.getStart(output->head.WCS().lat); |
---|
536 | if(output->head.WCS().spec>0) |
---|
537 | output->head.WCS().crpix[output->head.WCS().spec] -= subsection.getStart(output->head.WCS().spec); |
---|
538 | output->Stats = this->Stats; |
---|
539 | output->fullCols = this->fullCols; |
---|
540 | size_t *dims = new size_t[3]; |
---|
541 | for(size_t i=0;i<3;i++){ |
---|
542 | dims[i] = subsection.getDimList()[i]; |
---|
543 | std::cout << "Dim " << i+1 << " = " << dims[i] << "\n"; |
---|
544 | } |
---|
545 | |
---|
546 | output->initialiseCube(dims,true); |
---|
547 | for(size_t z=0;z<output->axisDim[2];z++){ |
---|
548 | for(size_t y=0;y<output->axisDim[1];y++){ |
---|
549 | for(size_t x=0;x<output->axisDim[0];x++){ |
---|
550 | size_t impos=x+y*output->axisDim[0]; |
---|
551 | size_t pos=impos+z*output->axisDim[0]*output->axisDim[1]; |
---|
552 | if(pos>=output->numPixels) DUCHAMPERROR("cube slicer","Out of bounds in new Cube"); |
---|
553 | size_t imposIn=(x+subsection.getStart(0)) + (y+subsection.getStart(1))*this->axisDim[0]; |
---|
554 | size_t posIn=imposIn + (z+subsection.getStart(2))*this->axisDim[0]*this->axisDim[1]; |
---|
555 | if(posIn>=this->numPixels) DUCHAMPERROR("cube slicer","Out of bounds in new Cube"); |
---|
556 | output->array[pos] = this->array[posIn]; |
---|
557 | output->detectMap[impos] = this->detectMap[imposIn]; |
---|
558 | if(this->reconAllocated) output->recon[pos] = this->recon[posIn]; |
---|
559 | if(this->baselineAllocated) output->baseline[pos] = this->baseline[posIn]; |
---|
560 | } |
---|
561 | } |
---|
562 | } |
---|
563 | std::cout << this->par << "\n"<<output->par <<"\n"; |
---|
564 | } |
---|
565 | else{ |
---|
566 | DUCHAMPERROR("cube slicer","Subsection does not parse"); |
---|
567 | } |
---|
568 | |
---|
569 | return output; |
---|
570 | |
---|
571 | } |
---|
572 | //-------------------------------------------------------------------- |
---|
573 | |
---|
574 | OUTCOME Cube::initialiseCube(long *dimensions, bool allocateArrays) |
---|
575 | { |
---|
576 | int numAxes = this->head.getNumAxes(); |
---|
577 | if(numAxes<=0) numAxes=3; |
---|
578 | size_t *dim = new size_t[numAxes]; |
---|
579 | for(int i=0;i<numAxes;i++) dim[i]=dimensions[i]; |
---|
580 | OUTCOME outcome=this->initialiseCube(dim,allocateArrays); |
---|
581 | delete [] dim; |
---|
582 | return outcome; |
---|
583 | } |
---|
584 | |
---|
585 | |
---|
586 | OUTCOME Cube::initialiseCube(size_t *dimensions, bool allocateArrays) |
---|
587 | { |
---|
588 | /// @details |
---|
589 | /// This function will set the sizes of all arrays that will be used by Cube. |
---|
590 | /// It will also define the values of the axis dimensions: this will be done |
---|
591 | /// using the WCS in the FitsHeader class, so the WCS needs to be good and |
---|
592 | /// have three axes. If this is not the case, the axes are assumed to be |
---|
593 | /// ordered in the sense of lng,lat,spc. |
---|
594 | /// |
---|
595 | /// \param dimensions An array of values giving the dimensions (sizes) for |
---|
596 | /// all axes. |
---|
597 | /// \param allocateArrays A flag indicating whether to allocate |
---|
598 | /// the memory for the data arrays: the default is true. The |
---|
599 | /// dimension arrays will be allocated and filled. |
---|
600 | |
---|
601 | int lng,lat,spc; |
---|
602 | size_t size,imsize; |
---|
603 | |
---|
604 | int numAxes = this->head.getNumAxes(); |
---|
605 | if(numAxes<=0) numAxes=3; |
---|
606 | |
---|
607 | if(this->head.isWCS() && (numAxes>=3) && (this->head.WCS().spec>=0)){ |
---|
608 | // if there is a WCS and there is at least 3 axes |
---|
609 | lng = this->head.WCS().lng; |
---|
610 | lat = this->head.WCS().lat; |
---|
611 | spc = this->head.WCS().spec; |
---|
612 | } |
---|
613 | else{ |
---|
614 | // just take dimensions[] at face value |
---|
615 | lng = 0; |
---|
616 | lat = 1; |
---|
617 | spc = 2; |
---|
618 | } |
---|
619 | |
---|
620 | size = dimensions[lng]; |
---|
621 | if(numAxes>1) size *= dimensions[lat]; |
---|
622 | if(this->head.canUseThirdAxis() && numAxes>spc) size *= dimensions[spc]; |
---|
623 | |
---|
624 | imsize = dimensions[lng]; |
---|
625 | if(numAxes>1) imsize *= dimensions[lat]; |
---|
626 | |
---|
627 | this->reconAllocated = false; |
---|
628 | this->baselineAllocated = false; |
---|
629 | |
---|
630 | if(this->axisDimAllocated){ |
---|
631 | delete [] this->axisDim; |
---|
632 | this->axisDimAllocated = false; |
---|
633 | } |
---|
634 | |
---|
635 | if(this->arrayAllocated){ |
---|
636 | delete [] this->array; |
---|
637 | delete [] this->detectMap; |
---|
638 | this->arrayAllocated = false; |
---|
639 | } |
---|
640 | if(this->reconAllocated){ |
---|
641 | delete [] this->recon; |
---|
642 | this->reconAllocated = false; |
---|
643 | } |
---|
644 | if(this->baselineAllocated){ |
---|
645 | delete [] this->baseline; |
---|
646 | this->baselineAllocated = false; |
---|
647 | } |
---|
648 | |
---|
649 | this->numPixels = size; |
---|
650 | this->numDim = 3; |
---|
651 | |
---|
652 | this->axisDim = new size_t[this->numDim]; |
---|
653 | this->axisDimAllocated = true; |
---|
654 | this->axisDim[0] = dimensions[lng]; |
---|
655 | if(numAxes>1) this->axisDim[1] = dimensions[lat]; |
---|
656 | else this->axisDim[1] = 1; |
---|
657 | if(this->head.canUseThirdAxis() && numAxes>spc) this->axisDim[2] = dimensions[spc]; |
---|
658 | else this->axisDim[2] = 1; |
---|
659 | |
---|
660 | this->numNondegDim=0; |
---|
661 | for(int i=0;i<3;i++) if(this->axisDim[i]>1) this->numNondegDim++; |
---|
662 | |
---|
663 | if(this->numNondegDim == 1){ |
---|
664 | if(!head.isWCS()) std::swap(this->axisDim[0],this->axisDim[2]); |
---|
665 | imsize=this->axisDim[2]; |
---|
666 | } |
---|
667 | |
---|
668 | bool haveChanged=false; |
---|
669 | int change=0; |
---|
670 | if(this->par.getMinPix() > this->axisDim[0]*this->axisDim[1]){ |
---|
671 | DUCHAMPWARN("Cube::initialiseCube", "The value of minPix ("<<this->par.getMinPix()<<") is greater than the image size. Setting to "<<this->axisDim[0]*this->axisDim[1]); |
---|
672 | change=this->par.getMinPix() - this->axisDim[0]*this->axisDim[1]; |
---|
673 | haveChanged=true; |
---|
674 | this->par.setMinPix(this->axisDim[0]*this->axisDim[1]); |
---|
675 | } |
---|
676 | if(this->par.getMinChannels() > this->axisDim[2]){ |
---|
677 | DUCHAMPWARN("Cube::initialiseCube", "The value of minChannels ("<<this->par.getMinChannels()<<") is greater than the spectral size. Setting to "<<this->axisDim[2]); |
---|
678 | change=this->par.getMinChannels() - this->axisDim[2]; |
---|
679 | haveChanged=true; |
---|
680 | this->par.setMinChannels(this->axisDim[2]); |
---|
681 | } |
---|
682 | if(haveChanged){ |
---|
683 | DUCHAMPWARN("Cube::initialiseCube","Reducing minVoxels to "<<this->par.getMinVoxels() - change<<" to accomodate these changes" ); |
---|
684 | this->par.setMinVoxels(this->par.getMinVoxels() - change); |
---|
685 | } |
---|
686 | |
---|
687 | if(this->par.getFlagSmooth()){ |
---|
688 | if(this->par.getSmoothType()=="spectral" && this->numNondegDim==2){ |
---|
689 | DUCHAMPWARN("Cube::initialiseCube", "Spectral smooth requested, but have a 2D image. Setting flagSmooth=false"); |
---|
690 | this->par.setFlagSmooth(false); |
---|
691 | } |
---|
692 | if(this->par.getSmoothType()=="spatial" && this->numNondegDim==1){ |
---|
693 | DUCHAMPWARN("Cube::initialiseCube", "Spatial smooth requested, but have a 1D image. Setting flagSmooth=false"); |
---|
694 | this->par.setFlagSmooth(false); |
---|
695 | } |
---|
696 | } |
---|
697 | if(this->par.getFlagATrous()){ |
---|
698 | for(int d=3; d>=1; d--){ |
---|
699 | if(this->par.getReconDim()==d && this->numNondegDim==(d-1)){ |
---|
700 | DUCHAMPWARN("Cube::initialiseCube", d << "D reconstruction requested, but image is " << d-1 <<"D. Setting flagAtrous=false"); |
---|
701 | this->par.setFlagATrous(false); |
---|
702 | } |
---|
703 | } |
---|
704 | } |
---|
705 | |
---|
706 | if(allocateArrays && this->par.isVerbose()) this->reportMemorySize(std::cout,allocateArrays); |
---|
707 | |
---|
708 | this->reconExists = false; |
---|
709 | if(allocateArrays){ |
---|
710 | this->array = new float[size]; |
---|
711 | this->arrayAllocated = true; |
---|
712 | this->detectMap = new short[imsize]; |
---|
713 | for(size_t i=0;i<imsize;i++) this->detectMap[i] = 0; |
---|
714 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()){ |
---|
715 | this->recon = new float[size]; |
---|
716 | this->reconAllocated = true; |
---|
717 | for(size_t i=0;i<size;i++) this->recon[i] = 0.; |
---|
718 | } |
---|
719 | if(this->par.getFlagBaseline()){ |
---|
720 | this->baseline = new float[size]; |
---|
721 | this->baselineAllocated = true; |
---|
722 | for(size_t i=0;i<size;i++) this->baseline[i] = 0.; |
---|
723 | } |
---|
724 | } |
---|
725 | |
---|
726 | return SUCCESS; |
---|
727 | } |
---|
728 | //-------------------------------------------------------------------- |
---|
729 | |
---|
730 | void Cube::reportMemorySize(std::ostream &theStream, bool allocateArrays) |
---|
731 | { |
---|
732 | std::string unitlist[4]={"kB","MB","GB","TB"}; |
---|
733 | size_t size=axisDim[0]*axisDim[1]*axisDim[2]; |
---|
734 | size_t imsize=axisDim[0]*axisDim[1]; |
---|
735 | |
---|
736 | // Calculate and report the total size of memory to be allocated. |
---|
737 | float allocSize=3*sizeof(size_t); // axisDim |
---|
738 | float arrAllocSize=0.; |
---|
739 | if(size>0 && allocateArrays){ |
---|
740 | allocSize += size * sizeof(float); // array |
---|
741 | arrAllocSize = size*sizeof(float); |
---|
742 | allocSize += imsize * sizeof(short); // detectMap |
---|
743 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()) |
---|
744 | allocSize += size * sizeof(float); // recon |
---|
745 | if(this->par.getFlagBaseline()) |
---|
746 | allocSize += size * sizeof(float); // baseline |
---|
747 | } |
---|
748 | std::string units="bytes"; |
---|
749 | for(int i=0;i<4 && allocSize>1024.;i++){ |
---|
750 | allocSize/=1024.; |
---|
751 | arrAllocSize /= 1024.; |
---|
752 | units=unitlist[i]; |
---|
753 | } |
---|
754 | |
---|
755 | theStream << "\n About to allocate " << allocSize << units; |
---|
756 | if(arrAllocSize > 0.) theStream << " of which " << arrAllocSize << units << " is for the image\n"; |
---|
757 | else theStream << "\n"; |
---|
758 | } |
---|
759 | |
---|
760 | |
---|
761 | bool Cube::is2D() |
---|
762 | { |
---|
763 | /// @details |
---|
764 | /// Check whether the image is 2-dimensional, by counting |
---|
765 | /// the number of dimensions that are greater than 1 |
---|
766 | |
---|
767 | if(this->head.WCS().naxis==2) return true; |
---|
768 | else{ |
---|
769 | int numDim=0; |
---|
770 | for(int i=0;i<this->numDim;i++) if(axisDim[i]>1) numDim++; |
---|
771 | return numDim<=2; |
---|
772 | } |
---|
773 | |
---|
774 | } |
---|
775 | //-------------------------------------------------------------------- |
---|
776 | |
---|
777 | OUTCOME Cube::getCube() |
---|
778 | { |
---|
779 | /// @details |
---|
780 | /// A front-end to the Cube::getCube() function, that does |
---|
781 | /// subsection checks. |
---|
782 | /// Assumes the Param is set up properly. |
---|
783 | |
---|
784 | std::string fname = par.getImageFile(); |
---|
785 | if(par.getFlagSubsection()) fname+=par.getSubsection(); |
---|
786 | return getCube(fname); |
---|
787 | } |
---|
788 | //-------------------------------------------------------------------- |
---|
789 | |
---|
790 | void Cube::saveArray(float *input, size_t size) |
---|
791 | { |
---|
792 | if(size != this->numPixels){ |
---|
793 | DUCHAMPERROR("Cube::saveArray","Input array different size to existing array (" << size << " cf. " << this->numPixels << "). Cannot save."); |
---|
794 | } |
---|
795 | else { |
---|
796 | if(this->numPixels>0 && this->arrayAllocated) delete [] array; |
---|
797 | this->numPixels = size; |
---|
798 | this->array = new float[size]; |
---|
799 | this->arrayAllocated = true; |
---|
800 | for(size_t i=0;i<size;i++) this->array[i] = input[i]; |
---|
801 | } |
---|
802 | } |
---|
803 | //-------------------------------------------------------------------- |
---|
804 | |
---|
805 | void Cube::saveArray(std::vector<float> &input) |
---|
806 | { |
---|
807 | /// @details |
---|
808 | /// Saves the array in input to the pixel array Cube::array. |
---|
809 | /// The size of the array given must be the same as the current number of |
---|
810 | /// pixels, else an error message is returned and nothing is done. |
---|
811 | /// \param input The array of values to be saved. |
---|
812 | |
---|
813 | if(input.size() != this->numPixels){ |
---|
814 | DUCHAMPERROR("Cube::saveArray","Input array different size to existing array (" << input.size() << " cf. " << this->numPixels << "). Cannot save."); |
---|
815 | } |
---|
816 | else { |
---|
817 | if(this->numPixels>0 && this->arrayAllocated) delete [] this->array; |
---|
818 | this->numPixels = input.size(); |
---|
819 | this->array = new float[input.size()]; |
---|
820 | this->arrayAllocated = true; |
---|
821 | for(size_t i=0;i<input.size();i++) this->array[i] = input[i]; |
---|
822 | } |
---|
823 | } |
---|
824 | //-------------------------------------------------------------------- |
---|
825 | |
---|
826 | void Cube::saveRecon(float *input, size_t size) |
---|
827 | { |
---|
828 | /// @details |
---|
829 | /// Saves the array in input to the reconstructed array Cube::recon |
---|
830 | /// The size of the array given must be the same as the current number of |
---|
831 | /// pixels, else an error message is returned and nothing is done. |
---|
832 | /// If the recon array has already been allocated, it is deleted first, and |
---|
833 | /// then the space is allocated. |
---|
834 | /// Afterwards, the appropriate flags are set. |
---|
835 | /// \param input The array of values to be saved. |
---|
836 | /// \param size The size of input. |
---|
837 | |
---|
838 | if(size != this->numPixels){ |
---|
839 | DUCHAMPERROR("Cube::saveRecon","Input array different size to existing array (" << size << " cf. " << this->numPixels << "). Cannot save."); |
---|
840 | } |
---|
841 | else { |
---|
842 | if(this->numPixels>0){ |
---|
843 | if(this->reconAllocated) delete [] this->recon; |
---|
844 | this->numPixels = size; |
---|
845 | this->recon = new float[size]; |
---|
846 | this->reconAllocated = true; |
---|
847 | for(size_t i=0;i<size;i++) this->recon[i] = input[i]; |
---|
848 | this->reconExists = true; |
---|
849 | } |
---|
850 | } |
---|
851 | } |
---|
852 | //-------------------------------------------------------------------- |
---|
853 | |
---|
854 | void Cube::getRecon(float *output) |
---|
855 | { |
---|
856 | /// @details |
---|
857 | /// The reconstructed array is written to output. The output array needs to |
---|
858 | /// be defined beforehand: no checking is done on the memory. |
---|
859 | /// \param output The array that is written to. |
---|
860 | |
---|
861 | // Need check for change in number of pixels! |
---|
862 | for(size_t i=0;i<this->numPixels;i++){ |
---|
863 | if(this->reconExists) output[i] = this->recon[i]; |
---|
864 | else output[i] = 0.; |
---|
865 | } |
---|
866 | } |
---|
867 | //-------------------------------------------------------------------- |
---|
868 | |
---|
869 | void Cube::getBaseline(float *output) |
---|
870 | { |
---|
871 | /// @details |
---|
872 | /// The baseline array is written to output. The output array needs to |
---|
873 | /// be defined beforehand: no checking is done on the memory. |
---|
874 | /// \param output The array that is written to. |
---|
875 | |
---|
876 | // Need check for change in number of pixels! |
---|
877 | for(size_t i=0;i<this->numPixels;i++){ |
---|
878 | if(this->baselineAllocated) output[i] = this->baseline[i]; |
---|
879 | else output[i] = 0.; |
---|
880 | } |
---|
881 | } |
---|
882 | //-------------------------------------------------------------------- |
---|
883 | void Cube::setCubeStats() |
---|
884 | { |
---|
885 | /// @details |
---|
886 | /// Calculates the full statistics for the cube: |
---|
887 | /// mean, rms, median, madfm |
---|
888 | /// Only do this if the threshold has not been defined (ie. is still 0., |
---|
889 | /// its default). |
---|
890 | /// Also work out the threshold and store it in the par set. |
---|
891 | /// |
---|
892 | /// Different from Cube::setCubeStatsOld() as it doesn't use the |
---|
893 | /// getStats functions but has own versions of them hardcoded to |
---|
894 | /// ignore BLANKs and flagged channels. This saves on memory usage -- necessary |
---|
895 | /// for dealing with very big files. |
---|
896 | /// |
---|
897 | /// Three cases exist: |
---|
898 | /// <ul><li>Simple case, with no reconstruction/smoothing: all stats |
---|
899 | /// calculated from the original array. |
---|
900 | /// <li>Wavelet reconstruction: mean & median calculated from the |
---|
901 | /// original array, and stddev & madfm from the residual. |
---|
902 | /// <li>Smoothing: all four stats calculated from the recon array |
---|
903 | /// (which holds the smoothed data). |
---|
904 | /// </ul> |
---|
905 | |
---|
906 | if(this->par.getFlagUserThreshold() ){ |
---|
907 | // if the user has defined a threshold, set this in the StatsContainer |
---|
908 | this->Stats.setThreshold( this->par.getThreshold() ); |
---|
909 | } |
---|
910 | else{ |
---|
911 | // only work out the stats if we need to. |
---|
912 | // the only reason we don't is if the user has specified a threshold. |
---|
913 | |
---|
914 | this->Stats.setRobust(this->par.getFlagRobustStats()); |
---|
915 | |
---|
916 | if(this->par.isVerbose()) |
---|
917 | std::cout << "Calculating the cube statistics... " << std::flush; |
---|
918 | |
---|
919 | // size_t xysize = this->axisDim[0]*this->axisDim[1]; |
---|
920 | |
---|
921 | bool needMask=true; |
---|
922 | if (!this->par.getFlagBlankPix() && !this->par.getFlagStatSec() && (this->par.getFlaggedChannels().size()==0) ) |
---|
923 | needMask=false; |
---|
924 | |
---|
925 | std::vector<bool> mask; |
---|
926 | size_t vox=0,goodSize=this->numPixels; |
---|
927 | if (needMask) { |
---|
928 | mask = std::vector<bool>(this->numPixels,false); |
---|
929 | goodSize = 0; |
---|
930 | for(size_t z=0;z<this->axisDim[2];z++){ |
---|
931 | for(size_t y=0;y<this->axisDim[1];y++){ |
---|
932 | for(size_t x=0;x<this->axisDim[0];x++){ |
---|
933 | // vox = z * xysize + y*this->axisDim[0] + x; |
---|
934 | bool isBlank=this->isBlank(vox); |
---|
935 | bool statOK = this->par.isStatOK(x,y,z); |
---|
936 | bool isFlagged = this->par.isFlaggedChannel(z); |
---|
937 | mask[vox] = (!isBlank && !isFlagged && statOK ); |
---|
938 | if(mask[vox]) goodSize++; |
---|
939 | vox++; |
---|
940 | } |
---|
941 | } |
---|
942 | } |
---|
943 | } |
---|
944 | |
---|
945 | // float mean,median,stddev,madfm; |
---|
946 | if( this->par.getFlagATrous() ){ |
---|
947 | // Case #2 -- wavelet reconstruction |
---|
948 | // just get mean & median from orig array, and rms & madfm from |
---|
949 | // residual recompute array values to be residuals & then find |
---|
950 | // stddev & madfm |
---|
951 | if(!this->reconExists){ |
---|
952 | DUCHAMPERROR("setCubeStats", "Reconstruction not yet done! Cannot calculate stats!"); |
---|
953 | } |
---|
954 | else{ |
---|
955 | float *tempArray = new float[goodSize]; |
---|
956 | |
---|
957 | goodSize=0; |
---|
958 | vox=0; |
---|
959 | for(size_t z=0;z<this->axisDim[2];z++){ |
---|
960 | for(size_t y=0;y<this->axisDim[1];y++){ |
---|
961 | for(size_t x=0;x<this->axisDim[0];x++){ |
---|
962 | // vox = z * xysize + y*this->axisDim[0] + x; |
---|
963 | if(!needMask || mask[vox]) tempArray[goodSize++] = this->array[vox]; |
---|
964 | vox++; |
---|
965 | } |
---|
966 | } |
---|
967 | } |
---|
968 | |
---|
969 | // First, find the mean of the original array. Store it. |
---|
970 | float mean = findMean<float>(tempArray, goodSize); |
---|
971 | |
---|
972 | // Now sort it and find the median. Store it. |
---|
973 | float median = findMedian<float>(tempArray, goodSize, true); |
---|
974 | |
---|
975 | // Now calculate the residuals and find the mean & median of |
---|
976 | // them. We don't store these, but they are necessary to find |
---|
977 | // the sttdev & madfm. |
---|
978 | goodSize = 0; |
---|
979 | // for(int p=0;p<xysize;p++){ |
---|
980 | vox=0; |
---|
981 | for(size_t z=0;z<this->axisDim[2];z++){ |
---|
982 | for(size_t y=0;y<this->axisDim[1];y++){ |
---|
983 | for(size_t x=0;x<this->axisDim[0];x++){ |
---|
984 | // vox = z * xysize + p; |
---|
985 | if(!needMask || mask[vox]) |
---|
986 | tempArray[goodSize++] = this->array[vox] - this->recon[vox]; |
---|
987 | vox++; |
---|
988 | } |
---|
989 | } |
---|
990 | } |
---|
991 | |
---|
992 | float stddev = findStddev<float>(tempArray, goodSize); |
---|
993 | |
---|
994 | // Now find the madfm of the residuals. Store it. |
---|
995 | float madfm = findMADFM<float>(tempArray, goodSize, true); |
---|
996 | |
---|
997 | this->Stats.define(mean,median,stddev,madfm); |
---|
998 | |
---|
999 | delete [] tempArray; |
---|
1000 | } |
---|
1001 | } |
---|
1002 | else if(this->par.getFlagSmooth()) { |
---|
1003 | // Case #3 -- smoothing |
---|
1004 | // get all four stats from the recon array, which holds the |
---|
1005 | // smoothed data. This can just be done with the |
---|
1006 | // StatsContainer::calculate function, using the mask generated |
---|
1007 | // earlier. |
---|
1008 | if(!this->reconExists){ |
---|
1009 | DUCHAMPERROR("setCubeStats","Smoothing not yet done! Cannot calculate stats!"); |
---|
1010 | } |
---|
1011 | else{ |
---|
1012 | if(needMask) this->Stats.calculate(this->recon,this->numPixels,mask); |
---|
1013 | else this->Stats.calculate(this->recon,this->numPixels); |
---|
1014 | } |
---|
1015 | } |
---|
1016 | else{ |
---|
1017 | // Case #1 -- default case, with no smoothing or reconstruction. |
---|
1018 | // get all four stats from the original array. This can just be |
---|
1019 | // done with the StatsContainer::calculate function, using the |
---|
1020 | // mask generated earlier. |
---|
1021 | if(needMask) this->Stats.calculate(this->array,this->numPixels,mask); |
---|
1022 | else this->Stats.calculate(this->array,this->numPixels); |
---|
1023 | } |
---|
1024 | |
---|
1025 | this->Stats.setUseFDR( this->par.getFlagFDR() ); |
---|
1026 | // If the FDR method has been requested, define the P-value |
---|
1027 | // threshold |
---|
1028 | if(this->par.getFlagFDR()) this->setupFDR(); |
---|
1029 | else{ |
---|
1030 | // otherwise, calculate threshold based on the requested SNR cut |
---|
1031 | // level, and then set the threshold parameter in the Par set. |
---|
1032 | this->Stats.setThresholdSNR( this->par.getCut() ); |
---|
1033 | this->par.setThreshold( this->Stats.getThreshold() ); |
---|
1034 | } |
---|
1035 | |
---|
1036 | } |
---|
1037 | |
---|
1038 | if(this->par.isVerbose()){ |
---|
1039 | std::cout << "Using "; |
---|
1040 | if(this->par.getFlagFDR()) std::cout << "effective "; |
---|
1041 | std::cout << "flux threshold of: "; |
---|
1042 | float thresh = this->Stats.getThreshold(); |
---|
1043 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
1044 | std::cout << thresh; |
---|
1045 | if(this->par.getFlagGrowth()){ |
---|
1046 | std::cout << " and growing to threshold of: "; |
---|
1047 | if(this->par.getFlagUserGrowthThreshold()) thresh= this->par.getGrowthThreshold(); |
---|
1048 | else thresh= this->Stats.snrToValue(this->par.getGrowthCut()); |
---|
1049 | if(this->par.getFlagNegative()) thresh *= -1.; |
---|
1050 | std::cout << thresh; |
---|
1051 | } |
---|
1052 | std::cout << std::endl; |
---|
1053 | } |
---|
1054 | |
---|
1055 | } |
---|
1056 | //-------------------------------------------------------------------- |
---|
1057 | |
---|
1058 | void Cube::setupFDR() |
---|
1059 | { |
---|
1060 | /// @details |
---|
1061 | /// Call the setupFDR(float *) function on the pixel array of the |
---|
1062 | /// cube. This is the usual way of running it. |
---|
1063 | /// |
---|
1064 | /// However, if we are in smoothing mode, we calculate the FDR |
---|
1065 | /// parameters using the recon array, which holds the smoothed |
---|
1066 | /// data. Gives an error message if the reconExists flag is not set. |
---|
1067 | |
---|
1068 | if(this->par.getFlagSmooth()) |
---|
1069 | if(this->reconExists) this->setupFDR(this->recon); |
---|
1070 | else{ |
---|
1071 | DUCHAMPERROR("setupFDR", "Smoothing not done properly! Using original array for defining threshold."); |
---|
1072 | this->setupFDR(this->array); |
---|
1073 | } |
---|
1074 | else if( this->par.getFlagATrous() ){ |
---|
1075 | if(this->reconExists) this->setupFDR(this->recon); |
---|
1076 | else{ |
---|
1077 | DUCHAMPERROR("setupFDR", "Reconstruction not done properly! Using original array for defining threshold."); |
---|
1078 | this->setupFDR(this->array); |
---|
1079 | } |
---|
1080 | } |
---|
1081 | else{ |
---|
1082 | this->setupFDR(this->array); |
---|
1083 | } |
---|
1084 | } |
---|
1085 | //-------------------------------------------------------------------- |
---|
1086 | |
---|
1087 | void Cube::setupFDR(float *input) |
---|
1088 | { |
---|
1089 | /// @details |
---|
1090 | /// Determines the critical Probability value for the False |
---|
1091 | /// Discovery Rate detection routine. All pixels in the given arry |
---|
1092 | /// with Prob less than this value will be considered detections. |
---|
1093 | /// |
---|
1094 | /// Note that the Stats of the cube need to be calculated first. |
---|
1095 | /// |
---|
1096 | /// The Prob here is the probability, assuming a Normal |
---|
1097 | /// distribution, of obtaining a value as high or higher than the |
---|
1098 | /// pixel value (ie. only the positive tail of the PDF). |
---|
1099 | /// |
---|
1100 | /// The probabilities are calculated using the |
---|
1101 | /// StatsContainer::getPValue(), which calculates the z-statistic, |
---|
1102 | /// and then the probability via |
---|
1103 | /// \f$0.5\operatorname{erfc}(z/\sqrt{2})\f$ -- giving the positive |
---|
1104 | /// tail probability. |
---|
1105 | |
---|
1106 | // first calculate p-value for each pixel -- assume Gaussian for now. |
---|
1107 | |
---|
1108 | float *orderedP = new float[this->numPixels]; |
---|
1109 | size_t count = 0; |
---|
1110 | for(size_t x=0;x<this->axisDim[0];x++){ |
---|
1111 | for(size_t y=0;y<this->axisDim[1];y++){ |
---|
1112 | for(size_t z=0;z<this->axisDim[2];z++){ |
---|
1113 | size_t pix = z * this->axisDim[0]*this->axisDim[1] + |
---|
1114 | y*this->axisDim[0] + x; |
---|
1115 | |
---|
1116 | if(!(this->par.isBlank(this->array[pix])) && !this->par.isFlaggedChannel(z)){ |
---|
1117 | // only look at non-blank, valid pixels |
---|
1118 | // orderedP[count++] = this->Stats.getPValue(this->array[pix]); |
---|
1119 | orderedP[count++] = this->Stats.getPValue(input[pix]); |
---|
1120 | } |
---|
1121 | } |
---|
1122 | } |
---|
1123 | } |
---|
1124 | |
---|
1125 | // now order them |
---|
1126 | std::stable_sort(orderedP,orderedP+count); |
---|
1127 | |
---|
1128 | // now find the maximum P value. |
---|
1129 | size_t max = 0; |
---|
1130 | double cN = 0.; |
---|
1131 | // Calculate number of correlated pixels. Assume all spatial |
---|
1132 | // pixels within the beam are correlated, and multiply this by the |
---|
1133 | // number of correlated pixels as determined by the beam |
---|
1134 | int numVox; |
---|
1135 | if(this->head.beam().isDefined()) numVox = int(ceil(this->head.beam().area())); |
---|
1136 | else numVox = 1; |
---|
1137 | if(this->head.canUseThirdAxis()) numVox *= this->par.getFDRnumCorChan(); |
---|
1138 | for(int psfCtr=1;psfCtr<=numVox;psfCtr++) cN += 1./float(psfCtr); |
---|
1139 | |
---|
1140 | double slope = this->par.getAlpha()/cN; |
---|
1141 | for(size_t loopCtr=0;loopCtr<count;loopCtr++) { |
---|
1142 | if( orderedP[loopCtr] < (slope * double(loopCtr+1)/ double(count)) ){ |
---|
1143 | max = loopCtr; |
---|
1144 | } |
---|
1145 | } |
---|
1146 | |
---|
1147 | this->Stats.setPThreshold( orderedP[max] ); |
---|
1148 | |
---|
1149 | |
---|
1150 | // Find real value of the P threshold by finding the inverse of the |
---|
1151 | // error function -- root finding with brute force technique |
---|
1152 | // (relatively slow, but we only do it once). |
---|
1153 | double zStat = 0.; |
---|
1154 | double deltaZ = 0.1; |
---|
1155 | double tolerance = 1.e-6; |
---|
1156 | double initial = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
1157 | do{ |
---|
1158 | zStat+=deltaZ; |
---|
1159 | double current = 0.5 * erfc(zStat/M_SQRT2) - this->Stats.getPThreshold(); |
---|
1160 | if((initial*current)<0.){ |
---|
1161 | zStat-=deltaZ; |
---|
1162 | deltaZ/=2.; |
---|
1163 | } |
---|
1164 | }while(deltaZ>tolerance); |
---|
1165 | this->Stats.setThreshold( zStat*this->Stats.getSpread() + |
---|
1166 | this->Stats.getMiddle() ); |
---|
1167 | |
---|
1168 | /////////////////////////// |
---|
1169 | // if(TESTING){ |
---|
1170 | // std::stringstream ss; |
---|
1171 | // float *xplot = new float[2*max]; |
---|
1172 | // for(int i=0;i<2*max;i++) xplot[i]=float(i)/float(count); |
---|
1173 | // cpgopen("latestFDR.ps/vcps"); |
---|
1174 | // cpgpap(8.,1.); |
---|
1175 | // cpgslw(3); |
---|
1176 | // cpgenv(0,float(2*max)/float(count),0,orderedP[2*max],0,0); |
---|
1177 | // cpglab("i/N (index)", "p-value",""); |
---|
1178 | // cpgpt(2*max,xplot,orderedP,DOT); |
---|
1179 | |
---|
1180 | // ss.str(""); |
---|
1181 | // ss << "\\gm = " << this->Stats.getMiddle(); |
---|
1182 | // cpgtext(max/(4.*count),0.9*orderedP[2*max],ss.str().c_str()); |
---|
1183 | // ss.str(""); |
---|
1184 | // ss << "\\gs = " << this->Stats.getSpread(); |
---|
1185 | // cpgtext(max/(4.*count),0.85*orderedP[2*max],ss.str().c_str()); |
---|
1186 | // ss.str(""); |
---|
1187 | // ss << "Slope = " << slope; |
---|
1188 | // cpgtext(max/(4.*count),0.8*orderedP[2*max],ss.str().c_str()); |
---|
1189 | // ss.str(""); |
---|
1190 | // ss << "Alpha = " << this->par.getAlpha(); |
---|
1191 | // cpgtext(max/(4.*count),0.75*orderedP[2*max],ss.str().c_str()); |
---|
1192 | // ss.str(""); |
---|
1193 | // ss << "c\\dN\\u = " << cN; |
---|
1194 | // cpgtext(max/(4.*count),0.7*orderedP[2*max],ss.str().c_str()); |
---|
1195 | // ss.str(""); |
---|
1196 | // ss << "max = "<<max << " (out of " << count << ")"; |
---|
1197 | // cpgtext(max/(4.*count),0.65*orderedP[2*max],ss.str().c_str()); |
---|
1198 | // ss.str(""); |
---|
1199 | // ss << "Threshold = "<<zStat*this->Stats.getSpread()+this->Stats.getMiddle(); |
---|
1200 | // cpgtext(max/(4.*count),0.6*orderedP[2*max],ss.str().c_str()); |
---|
1201 | |
---|
1202 | // cpgslw(1); |
---|
1203 | // cpgsci(RED); |
---|
1204 | // cpgmove(0,0); |
---|
1205 | // cpgdraw(1,slope); |
---|
1206 | // cpgsci(BLUE); |
---|
1207 | // cpgsls(DOTTED); |
---|
1208 | // cpgmove(0,orderedP[max]); |
---|
1209 | // cpgdraw(2*max/float(count),orderedP[max]); |
---|
1210 | // cpgmove(max/float(count),0); |
---|
1211 | // cpgdraw(max/float(count),orderedP[2*max]); |
---|
1212 | // cpgsci(GREEN); |
---|
1213 | // cpgsls(SOLID); |
---|
1214 | // for(int i=1;i<=10;i++) { |
---|
1215 | // ss.str(""); |
---|
1216 | // ss << float(i)/2. << "\\gs"; |
---|
1217 | // float prob = 0.5*erfc((float(i)/2.)/M_SQRT2); |
---|
1218 | // cpgtick(0, 0, 0, orderedP[2*max], |
---|
1219 | // prob/orderedP[2*max], |
---|
1220 | // 0, 1, 1.5, 90., ss.str().c_str()); |
---|
1221 | // } |
---|
1222 | // cpgend(); |
---|
1223 | // delete [] xplot; |
---|
1224 | // } |
---|
1225 | delete [] orderedP; |
---|
1226 | |
---|
1227 | } |
---|
1228 | //-------------------------------------------------------------------- |
---|
1229 | |
---|
1230 | void Cube::Search() |
---|
1231 | { |
---|
1232 | /// @details |
---|
1233 | /// This acts as a switching function to select the correct searching function based on the user's parameters. |
---|
1234 | /// @param verboseFlag If true, text is written to stdout describing the search function being used. |
---|
1235 | if(this->par.getFlagATrous()){ |
---|
1236 | if(this->par.isVerbose()) std::cout<<"Commencing search in reconstructed cube..."<<std::endl; |
---|
1237 | this->ReconSearch(); |
---|
1238 | } |
---|
1239 | else if(this->par.getFlagSmooth()){ |
---|
1240 | if(this->par.isVerbose()) std::cout<<"Commencing search in smoothed cube..."<<std::endl; |
---|
1241 | this->SmoothSearch(); |
---|
1242 | } |
---|
1243 | else{ |
---|
1244 | if(this->par.isVerbose()) std::cout<<"Commencing search in cube..."<<std::endl; |
---|
1245 | this->CubicSearch(); |
---|
1246 | } |
---|
1247 | |
---|
1248 | } |
---|
1249 | |
---|
1250 | bool Cube::isDetection(size_t x, size_t y, size_t z) |
---|
1251 | { |
---|
1252 | /// @details |
---|
1253 | /// Is a given voxel at position (x,y,z) a detection, based on the statistics |
---|
1254 | /// in the Cube's StatsContainer? |
---|
1255 | /// If the pixel lies outside the valid range for the data array, |
---|
1256 | /// return false. |
---|
1257 | /// \param x X-value of the Cube's voxel to be tested. |
---|
1258 | /// \param y Y-value of the Cube's voxel to be tested. |
---|
1259 | /// \param z Z-value of the Cube's voxel to be tested. |
---|
1260 | |
---|
1261 | size_t voxel = z*axisDim[0]*axisDim[1] + y*axisDim[0] + x; |
---|
1262 | return DataArray::isDetection(array[voxel]); |
---|
1263 | } |
---|
1264 | //-------------------------------------------------------------------- |
---|
1265 | |
---|
1266 | void Cube::calcObjectFluxes() |
---|
1267 | { |
---|
1268 | /// @details |
---|
1269 | /// A function to calculate the fluxes and centroids for each |
---|
1270 | /// object in the Cube's list of detections. Uses |
---|
1271 | /// Detection::calcFluxes() for each object. |
---|
1272 | |
---|
1273 | std::vector<Detection>::iterator obj; |
---|
1274 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1275 | obj->calcFluxes(this->array, this->axisDim); |
---|
1276 | if(!this->par.getFlagUserThreshold()) |
---|
1277 | obj->setPeakSNR( (obj->getPeakFlux() - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
1278 | } |
---|
1279 | } |
---|
1280 | //-------------------------------------------------------------------- |
---|
1281 | |
---|
1282 | void Cube::calcObjectWCSparams() |
---|
1283 | { |
---|
1284 | /// @details |
---|
1285 | /// A function that calculates the WCS parameters for each object in the |
---|
1286 | /// Cube's list of detections. |
---|
1287 | /// Each object gets an ID number assigned to it (which is simply its order |
---|
1288 | /// in the list), and if the WCS is good, the WCS paramters are calculated. |
---|
1289 | |
---|
1290 | std::vector<Detection>::iterator obj; |
---|
1291 | int ct=0; |
---|
1292 | ProgressBar bar; |
---|
1293 | if(this->par.isVerbose()) bar.init(this->objectList->size()); |
---|
1294 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1295 | // std::cerr << ct << ' ' << this->array << '\n'; |
---|
1296 | if(this->par.isVerbose()) bar.update(ct); |
---|
1297 | obj->setID(ct++); |
---|
1298 | if(!obj->hasParams()){ |
---|
1299 | obj->setCentreType(this->par.getPixelCentre()); |
---|
1300 | obj->calcFluxes(this->array,this->axisDim); |
---|
1301 | obj->findShape(this->array,this->axisDim,this->head); |
---|
1302 | // obj->calcWCSparams(this->array,this->axisDim,this->head); |
---|
1303 | obj->calcWCSparams(this->head); |
---|
1304 | obj->calcIntegFlux(this->array,this->axisDim,this->head, this->par); |
---|
1305 | |
---|
1306 | if(!this->par.getFlagUserThreshold()){ |
---|
1307 | |
---|
1308 | float peak=obj->getPeakFlux(); |
---|
1309 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()) { |
---|
1310 | // for these situations, need to measure peak flux in the reconstructed array, where we do the searching |
---|
1311 | Detection *newobj = new Detection(*obj); |
---|
1312 | newobj->calcFluxes(this->recon,this->axisDim); |
---|
1313 | peak=newobj->getPeakFlux(); |
---|
1314 | delete newobj; |
---|
1315 | } |
---|
1316 | obj->setPeakSNR( (peak - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
1317 | |
---|
1318 | if(!this->par.getFlagSmooth()){ |
---|
1319 | obj->setTotalFluxError( sqrt(float(obj->getSize())) * this->Stats.getSpread() ); |
---|
1320 | obj->setIntegFluxError( sqrt(double(obj->getSize())) * this->Stats.getSpread() ); |
---|
1321 | } |
---|
1322 | |
---|
1323 | if(!this->head.is2D()){ |
---|
1324 | double x=obj->getXcentre(),y=obj->getYcentre(),z1=obj->getZcentre(),z2=z1+1; |
---|
1325 | double dz=this->head.pixToVel(x,y,z1)-this->head.pixToVel(x,y,z2); |
---|
1326 | obj->setIntegFluxError( obj->getIntegFluxError() * fabs(dz)); |
---|
1327 | } |
---|
1328 | if(head.needBeamSize()) obj->setIntegFluxError( obj->getIntegFluxError() / head.beam().area() ); |
---|
1329 | } |
---|
1330 | |
---|
1331 | |
---|
1332 | } |
---|
1333 | } |
---|
1334 | if(this->par.isVerbose()) bar.remove(); |
---|
1335 | |
---|
1336 | if(!this->head.isWCS()){ |
---|
1337 | // if the WCS is bad, set the object names to Obj01 etc |
---|
1338 | int numspaces = int(log10(this->objectList->size())) + 1; |
---|
1339 | std::stringstream ss; |
---|
1340 | for(size_t i=0;i<this->objectList->size();i++){ |
---|
1341 | ss.str(""); |
---|
1342 | ss << "Obj" << std::setfill('0') << std::setw(numspaces) << i+1; |
---|
1343 | this->objectList->at(i).setName(ss.str()); |
---|
1344 | } |
---|
1345 | } |
---|
1346 | |
---|
1347 | } |
---|
1348 | //-------------------------------------------------------------------- |
---|
1349 | |
---|
1350 | void Cube::calcObjectWCSparams(std::vector< std::vector<PixelInfo::Voxel> > bigVoxList) |
---|
1351 | { |
---|
1352 | /// @details |
---|
1353 | /// A function that calculates the WCS parameters for each object in the |
---|
1354 | /// Cube's list of detections. |
---|
1355 | /// Each object gets an ID number assigned to it (which is simply its order |
---|
1356 | /// in the list), and if the WCS is good, the WCS paramters are calculated. |
---|
1357 | /// |
---|
1358 | /// This version uses vectors of Voxels to define the fluxes. |
---|
1359 | /// |
---|
1360 | /// \param bigVoxList A vector of vectors of Voxels, with the same |
---|
1361 | /// number of elements as this->objectList, where each element is a |
---|
1362 | /// vector of Voxels corresponding to the same voxels in each |
---|
1363 | /// detection and indicating the flux of each voxel. |
---|
1364 | |
---|
1365 | std::vector<Detection>::iterator obj; |
---|
1366 | int ct=0; |
---|
1367 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1368 | obj->setID(ct+1); |
---|
1369 | if(!obj->hasParams()){ |
---|
1370 | obj->setCentreType(this->par.getPixelCentre()); |
---|
1371 | obj->calcFluxes(bigVoxList[ct]); |
---|
1372 | obj->calcWCSparams(this->head); |
---|
1373 | obj->calcIntegFlux(this->axisDim[2],bigVoxList[ct],this->head); |
---|
1374 | |
---|
1375 | if(!this->par.getFlagUserThreshold()){ |
---|
1376 | |
---|
1377 | float peak=obj->getPeakFlux(); |
---|
1378 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()) { |
---|
1379 | // for these situations, need to measure peak flux in the reconstructed array, where we do the searching |
---|
1380 | Detection *newobj = new Detection(*obj); |
---|
1381 | newobj->calcFluxes(this->recon,this->axisDim); |
---|
1382 | peak=newobj->getPeakFlux(); |
---|
1383 | } |
---|
1384 | obj->setPeakSNR( (peak - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
1385 | |
---|
1386 | if(!this->par.getFlagSmooth()){ |
---|
1387 | obj->setTotalFluxError( sqrt(float(obj->getSize())) * this->Stats.getSpread() ); |
---|
1388 | obj->setIntegFluxError( sqrt(double(obj->getSize())) * this->Stats.getSpread() ); |
---|
1389 | } |
---|
1390 | |
---|
1391 | if(!this->head.is2D()){ |
---|
1392 | double x=obj->getXcentre(),y=obj->getYcentre(),z1=obj->getZcentre(),z2=z1+1; |
---|
1393 | double dz=this->head.pixToVel(x,y,z1)-this->head.pixToVel(x,y,z2); |
---|
1394 | obj->setIntegFluxError( obj->getIntegFluxError() * fabs(dz)); |
---|
1395 | } |
---|
1396 | if(head.needBeamSize()) obj->setIntegFluxError( obj->getIntegFluxError() / head.beam().area() ); |
---|
1397 | } |
---|
1398 | |
---|
1399 | } |
---|
1400 | ct++; |
---|
1401 | } |
---|
1402 | |
---|
1403 | if(!this->head.isWCS()){ |
---|
1404 | // if the WCS is bad, set the object names to Obj01 etc |
---|
1405 | int numspaces = int(log10(this->objectList->size())) + 1; |
---|
1406 | std::stringstream ss; |
---|
1407 | for(size_t i=0;i<this->objectList->size();i++){ |
---|
1408 | ss.str(""); |
---|
1409 | ss << "Obj" << std::setfill('0') << std::setw(numspaces) << i+1; |
---|
1410 | this->objectList->at(i).setName(ss.str()); |
---|
1411 | } |
---|
1412 | } |
---|
1413 | |
---|
1414 | } |
---|
1415 | //-------------------------------------------------------------------- |
---|
1416 | |
---|
1417 | void Cube::calcObjectWCSparams(std::map<PixelInfo::Voxel,float> &voxelMap) |
---|
1418 | { |
---|
1419 | /// @details |
---|
1420 | /// A function that calculates the WCS parameters for each object in the |
---|
1421 | /// Cube's list of detections. |
---|
1422 | /// Each object gets an ID number assigned to it (which is simply its order |
---|
1423 | /// in the list), and if the WCS is good, the WCS paramters are calculated. |
---|
1424 | /// |
---|
1425 | /// This version uses vectors of Voxels to define the fluxes. |
---|
1426 | /// |
---|
1427 | /// \param bigVoxList A vector of vectors of Voxels, with the same |
---|
1428 | /// number of elements as this->objectList, where each element is a |
---|
1429 | /// vector of Voxels corresponding to the same voxels in each |
---|
1430 | /// detection and indicating the flux of each voxel. |
---|
1431 | |
---|
1432 | std::vector<Detection>::iterator obj; |
---|
1433 | int ct=0; |
---|
1434 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1435 | obj->setID(ct+1); |
---|
1436 | if(!obj->hasParams()){ |
---|
1437 | obj->setCentreType(this->par.getPixelCentre()); |
---|
1438 | obj->calcFluxes(voxelMap); |
---|
1439 | obj->calcWCSparams(this->head); |
---|
1440 | obj->calcIntegFlux(this->axisDim[2],voxelMap,this->head); |
---|
1441 | |
---|
1442 | if(!this->par.getFlagUserThreshold()){ |
---|
1443 | |
---|
1444 | float peak=obj->getPeakFlux(); |
---|
1445 | if(this->par.getFlagATrous() || this->par.getFlagSmooth()) { |
---|
1446 | // for these situations, need to measure peak flux in the reconstructed array, where we do the searching |
---|
1447 | Detection *newobj = new Detection(*obj); |
---|
1448 | newobj->calcFluxes(this->recon,this->axisDim); |
---|
1449 | peak=newobj->getPeakFlux(); |
---|
1450 | } |
---|
1451 | obj->setPeakSNR( (peak - this->Stats.getMiddle()) / this->Stats.getSpread() ); |
---|
1452 | |
---|
1453 | if(!this->par.getFlagSmooth()){ |
---|
1454 | obj->setTotalFluxError( sqrt(float(obj->getSize())) * this->Stats.getSpread() ); |
---|
1455 | obj->setIntegFluxError( sqrt(double(obj->getSize())) * this->Stats.getSpread() ); |
---|
1456 | } |
---|
1457 | |
---|
1458 | if(!this->head.is2D()){ |
---|
1459 | double x=obj->getXcentre(),y=obj->getYcentre(),z1=obj->getZcentre(),z2=z1+1; |
---|
1460 | double dz=this->head.pixToVel(x,y,z1)-this->head.pixToVel(x,y,z2); |
---|
1461 | obj->setIntegFluxError( obj->getIntegFluxError() * fabs(dz)); |
---|
1462 | } |
---|
1463 | if(head.needBeamSize()) obj->setIntegFluxError( obj->getIntegFluxError() / head.beam().area() ); |
---|
1464 | } |
---|
1465 | } |
---|
1466 | ct++; |
---|
1467 | } |
---|
1468 | |
---|
1469 | if(!this->head.isWCS()){ |
---|
1470 | // if the WCS is bad, set the object names to Obj01 etc |
---|
1471 | int numspaces = int(log10(this->objectList->size())) + 1; |
---|
1472 | std::stringstream ss; |
---|
1473 | for(size_t i=0;i<this->objectList->size();i++){ |
---|
1474 | ss.str(""); |
---|
1475 | ss << "Obj" << std::setfill('0') << std::setw(numspaces) << i+1; |
---|
1476 | this->objectList->at(i).setName(ss.str()); |
---|
1477 | } |
---|
1478 | } |
---|
1479 | |
---|
1480 | } |
---|
1481 | //-------------------------------------------------------------------- |
---|
1482 | |
---|
1483 | void Cube::updateDetectMap() |
---|
1484 | { |
---|
1485 | /// @details A function that, for each detected object in the |
---|
1486 | /// cube's list, increments the cube's detection map by the |
---|
1487 | /// required amount at each pixel. Uses |
---|
1488 | /// updateDetectMap(Detection). |
---|
1489 | |
---|
1490 | std::vector<Detection>::iterator obj; |
---|
1491 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1492 | this->updateDetectMap(*obj); |
---|
1493 | } |
---|
1494 | |
---|
1495 | } |
---|
1496 | //-------------------------------------------------------------------- |
---|
1497 | |
---|
1498 | void Cube::updateDetectMap(Detection obj) |
---|
1499 | { |
---|
1500 | /// @details |
---|
1501 | /// A function that, for the given object, increments the cube's |
---|
1502 | /// detection map by the required amount at each pixel. |
---|
1503 | /// |
---|
1504 | /// \param obj A Detection object that is being incorporated into the map. |
---|
1505 | |
---|
1506 | std::vector<Voxel> vlist = obj.getPixelSet(); |
---|
1507 | for(std::vector<Voxel>::iterator vox=vlist.begin();vox<vlist.end();vox++) { |
---|
1508 | if(this->numNondegDim==1) |
---|
1509 | this->detectMap[vox->getZ()]++; |
---|
1510 | else |
---|
1511 | this->detectMap[vox->getX()+vox->getY()*this->axisDim[0]]++; |
---|
1512 | } |
---|
1513 | } |
---|
1514 | //-------------------------------------------------------------------- |
---|
1515 | |
---|
1516 | float Cube::enclosedFlux(Detection obj) |
---|
1517 | { |
---|
1518 | /// @details |
---|
1519 | /// A function to calculate the flux enclosed by the range |
---|
1520 | /// of pixels detected in the object obj (not necessarily all |
---|
1521 | /// pixels will have been detected). |
---|
1522 | /// |
---|
1523 | /// \param obj The Detection under consideration. |
---|
1524 | |
---|
1525 | obj.calcFluxes(this->array, this->axisDim); |
---|
1526 | int xsize = obj.getXmax()-obj.getXmin()+1; |
---|
1527 | int ysize = obj.getYmax()-obj.getYmin()+1; |
---|
1528 | int zsize = obj.getZmax()-obj.getZmin()+1; |
---|
1529 | std::vector <float> fluxArray(xsize*ysize*zsize,0.); |
---|
1530 | for(int x=0;x<xsize;x++){ |
---|
1531 | for(int y=0;y<ysize;y++){ |
---|
1532 | for(int z=0;z<zsize;z++){ |
---|
1533 | fluxArray[x+y*xsize+z*ysize*xsize] = |
---|
1534 | this->getPixValue(x+obj.getXmin(), |
---|
1535 | y+obj.getYmin(), |
---|
1536 | z+obj.getZmin()); |
---|
1537 | if(this->par.getFlagNegative()) |
---|
1538 | fluxArray[x+y*xsize+z*ysize*xsize] *= -1.; |
---|
1539 | } |
---|
1540 | } |
---|
1541 | } |
---|
1542 | float sum = 0.; |
---|
1543 | for(size_t i=0;i<fluxArray.size();i++) |
---|
1544 | if(!this->par.isBlank(fluxArray[i])) sum+=fluxArray[i]; |
---|
1545 | return sum; |
---|
1546 | } |
---|
1547 | //-------------------------------------------------------------------- |
---|
1548 | |
---|
1549 | void Cube::setupColumns() |
---|
1550 | { |
---|
1551 | /// @details |
---|
1552 | /// A front-end to the two setup routines in columns.cc. |
---|
1553 | /// |
---|
1554 | /// This first gets the starting precisions, which may be from |
---|
1555 | /// the input parameters. It then sets up the columns (calculates |
---|
1556 | /// their widths and precisions and so on based on the values |
---|
1557 | /// within). The precisions are also stored in each Detection |
---|
1558 | /// object. |
---|
1559 | /// |
---|
1560 | /// Need to have called calcObjectWCSparams() somewhere |
---|
1561 | /// beforehand. |
---|
1562 | |
---|
1563 | std::vector<Detection>::iterator obj; |
---|
1564 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1565 | obj->setVelPrec( this->par.getPrecVel() ); |
---|
1566 | obj->setFpeakPrec( this->par.getPrecFlux() ); |
---|
1567 | obj->setXYZPrec( Catalogues::prXYZ ); |
---|
1568 | obj->setPosPrec( Catalogues::prWPOS ); |
---|
1569 | obj->setFintPrec( this->par.getPrecFlux() ); |
---|
1570 | obj->setSNRPrec( this->par.getPrecSNR() ); |
---|
1571 | } |
---|
1572 | |
---|
1573 | this->fullCols = getFullColSet(*(this->objectList), this->head); |
---|
1574 | |
---|
1575 | if(this->par.getFlagUserThreshold()){ |
---|
1576 | this->fullCols.removeColumn("FTOTERR"); |
---|
1577 | this->fullCols.removeColumn("SNRPEAK"); |
---|
1578 | this->fullCols.removeColumn("FINTERR"); |
---|
1579 | } |
---|
1580 | |
---|
1581 | if(this->par.getFlagSmooth()){ |
---|
1582 | this->fullCols.removeColumn("FTOTERR"); |
---|
1583 | this->fullCols.removeColumn("FINTERR"); |
---|
1584 | } |
---|
1585 | |
---|
1586 | if(!this->head.isWCS()){ |
---|
1587 | this->fullCols.removeColumn("RA"); |
---|
1588 | this->fullCols.removeColumn("DEC"); |
---|
1589 | this->fullCols.removeColumn("VEL"); |
---|
1590 | this->fullCols.removeColumn("w_RA"); |
---|
1591 | this->fullCols.removeColumn("w_DEC"); |
---|
1592 | } |
---|
1593 | |
---|
1594 | int vel,fpeak,fint,pos,xyz,snr; |
---|
1595 | vel = fullCols.column("VEL").getPrecision(); |
---|
1596 | fpeak = fullCols.column("FPEAK").getPrecision(); |
---|
1597 | if(!this->par.getFlagUserThreshold()) |
---|
1598 | snr = fullCols.column("SNRPEAK").getPrecision(); |
---|
1599 | xyz = fullCols.column("X").getPrecision(); |
---|
1600 | xyz = std::max(xyz, fullCols.column("Y").getPrecision()); |
---|
1601 | xyz = std::max(xyz, fullCols.column("Z").getPrecision()); |
---|
1602 | if(this->head.isWCS()) fint = fullCols.column("FINT").getPrecision(); |
---|
1603 | else fint = fullCols.column("FTOT").getPrecision(); |
---|
1604 | pos = fullCols.column("WRA").getPrecision(); |
---|
1605 | pos = std::max(pos, fullCols.column("WDEC").getPrecision()); |
---|
1606 | |
---|
1607 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1608 | obj->setVelPrec(vel); |
---|
1609 | obj->setFpeakPrec(fpeak); |
---|
1610 | obj->setXYZPrec(xyz); |
---|
1611 | obj->setPosPrec(pos); |
---|
1612 | obj->setFintPrec(fint); |
---|
1613 | if(!this->par.getFlagUserThreshold()) |
---|
1614 | obj->setSNRPrec(snr); |
---|
1615 | } |
---|
1616 | |
---|
1617 | } |
---|
1618 | //-------------------------------------------------------------------- |
---|
1619 | |
---|
1620 | bool Cube::objAtSpatialEdge(Detection obj) |
---|
1621 | { |
---|
1622 | /// @details |
---|
1623 | /// A function to test whether the object obj |
---|
1624 | /// lies at the edge of the cube's spatial field -- |
---|
1625 | /// either at the boundary, or next to BLANKs. |
---|
1626 | /// |
---|
1627 | /// \param obj The Detection under consideration. |
---|
1628 | |
---|
1629 | bool atEdge = false; |
---|
1630 | |
---|
1631 | size_t pix = 0; |
---|
1632 | std::vector<Voxel> voxlist = obj.getPixelSet(); |
---|
1633 | while(!atEdge && pix<voxlist.size()){ |
---|
1634 | // loop over each pixel in the object, until we find an edge pixel. |
---|
1635 | for(int dx=-1;dx<=1;dx+=2){ |
---|
1636 | if( ((voxlist[pix].getX()+dx)<0) || |
---|
1637 | ((voxlist[pix].getX()+dx)>=int(this->axisDim[0])) ) |
---|
1638 | atEdge = true; |
---|
1639 | else if(this->isBlank(voxlist[pix].getX()+dx, |
---|
1640 | voxlist[pix].getY(), |
---|
1641 | voxlist[pix].getZ())) |
---|
1642 | atEdge = true; |
---|
1643 | } |
---|
1644 | for(int dy=-1;dy<=1;dy+=2){ |
---|
1645 | if( ((voxlist[pix].getY()+dy)<0) || |
---|
1646 | ((voxlist[pix].getY()+dy)>=int(this->axisDim[1])) ) |
---|
1647 | atEdge = true; |
---|
1648 | else if(this->isBlank(voxlist[pix].getX(), |
---|
1649 | voxlist[pix].getY()+dy, |
---|
1650 | voxlist[pix].getZ())) |
---|
1651 | atEdge = true; |
---|
1652 | } |
---|
1653 | pix++; |
---|
1654 | } |
---|
1655 | |
---|
1656 | return atEdge; |
---|
1657 | } |
---|
1658 | //-------------------------------------------------------------------- |
---|
1659 | |
---|
1660 | bool Cube::objAtSpectralEdge(Detection obj) |
---|
1661 | { |
---|
1662 | /// @details |
---|
1663 | /// A function to test whether the object obj |
---|
1664 | /// lies at the edge of the cube's spectral extent -- |
---|
1665 | /// either at the boundary, or next to BLANKs. |
---|
1666 | /// |
---|
1667 | /// \param obj The Detection under consideration. |
---|
1668 | |
---|
1669 | bool atEdge = false; |
---|
1670 | |
---|
1671 | size_t pix = 0; |
---|
1672 | std::vector<Voxel> voxlist = obj.getPixelSet(); |
---|
1673 | while(!atEdge && pix<voxlist.size()){ |
---|
1674 | // loop over each pixel in the object, until we find an edge pixel. |
---|
1675 | for(int dz=-1;dz<=1;dz+=2){ |
---|
1676 | if( ((voxlist[pix].getZ()+dz)<0) || |
---|
1677 | ((voxlist[pix].getZ()+dz)>=int(this->axisDim[2])) ) |
---|
1678 | atEdge = true; |
---|
1679 | else if(this->isBlank(voxlist[pix].getX(), |
---|
1680 | voxlist[pix].getY(), |
---|
1681 | voxlist[pix].getZ()+dz)) |
---|
1682 | atEdge = true; |
---|
1683 | } |
---|
1684 | pix++; |
---|
1685 | } |
---|
1686 | |
---|
1687 | return atEdge; |
---|
1688 | } |
---|
1689 | //-------------------------------------------------------------------- |
---|
1690 | |
---|
1691 | bool Cube::objNextToFlaggedChan(Detection &obj) |
---|
1692 | { |
---|
1693 | /// @details A function to test whether the object obj lies |
---|
1694 | /// adjacent to a flagged channel or straddles one or more |
---|
1695 | /// (conceivably, you could have disconnected channels in your |
---|
1696 | /// object that don't touch flagged channels, but lie either side - |
---|
1697 | /// in this case we want to flag the object). |
---|
1698 | /// |
---|
1699 | /// We scan across the channel range from one below the |
---|
1700 | /// \param obj The Detection under consideration. |
---|
1701 | |
---|
1702 | bool isNext=false; |
---|
1703 | int zstart=std::max(obj.getZmin()-1,0L); |
---|
1704 | int zend=std::min(obj.getZmax()+1,long(this->axisDim[2]-1)); |
---|
1705 | for(int z=zstart;z<=zend && !isNext; z++) |
---|
1706 | isNext = isNext || this->par.isFlaggedChannel(z); |
---|
1707 | return isNext; |
---|
1708 | |
---|
1709 | } |
---|
1710 | |
---|
1711 | //-------------------------------------------------------------------- |
---|
1712 | |
---|
1713 | void Cube::setObjectFlags() |
---|
1714 | { |
---|
1715 | /// @details |
---|
1716 | /// A function to set any warning flags for all the detected objects |
---|
1717 | /// associated with the cube. |
---|
1718 | /// Flags to be looked for: |
---|
1719 | /// <ul><li> Negative enclosed flux (N) |
---|
1720 | /// <li> Detection at edge of field (spatially) (E) |
---|
1721 | /// <li> Detection at edge of spectral region (S) |
---|
1722 | /// </ul> |
---|
1723 | |
---|
1724 | std::vector<Detection>::iterator obj; |
---|
1725 | for(obj=this->objectList->begin();obj<this->objectList->end();obj++){ |
---|
1726 | |
---|
1727 | if( (!this->par.getFlagNegative() &&this->enclosedFlux(*obj) < 0.) || |
---|
1728 | (this->par.getFlagNegative() && this->enclosedFlux(*obj)>0.)) |
---|
1729 | obj->addToFlagText("N"); |
---|
1730 | |
---|
1731 | if( this->objAtSpatialEdge(*obj) ) |
---|
1732 | obj->addToFlagText("E"); |
---|
1733 | |
---|
1734 | if( this->objAtSpectralEdge(*obj) && (this->axisDim[2] > 2)) |
---|
1735 | obj->addToFlagText("S"); |
---|
1736 | |
---|
1737 | if( this->objNextToFlaggedChan(*obj) ) |
---|
1738 | obj->addToFlagText("F"); |
---|
1739 | |
---|
1740 | if(obj->getFlagText()=="") obj->addToFlagText("-"); |
---|
1741 | |
---|
1742 | } |
---|
1743 | |
---|
1744 | } |
---|
1745 | //-------------------------------------------------------------------- |
---|
1746 | |
---|
1747 | OUTCOME Cube::saveReconstructedCube() |
---|
1748 | { |
---|
1749 | std::string report; |
---|
1750 | OUTCOME result=SUCCESS; |
---|
1751 | if(!this->par.getFlagUsePrevious()){ |
---|
1752 | if(this->par.getFlagATrous()){ |
---|
1753 | if(this->par.getFlagOutputRecon()){ |
---|
1754 | if(this->par.isVerbose()) |
---|
1755 | std::cout << " Saving reconstructed cube to " << this->par.outputReconFile() << "... "<<std::flush; |
---|
1756 | WriteReconArray writer(this); |
---|
1757 | writer.setFilename(this->par.outputReconFile()); |
---|
1758 | result = writer.write(); |
---|
1759 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1760 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1761 | } |
---|
1762 | if(result==SUCCESS && this->par.getFlagOutputResid()){ |
---|
1763 | if(this->par.isVerbose()) |
---|
1764 | std::cout << " Saving reconstruction residual cube to " << this->par.outputResidFile() << "... "<<std::flush; |
---|
1765 | WriteReconArray writer(this); |
---|
1766 | writer.setFilename(this->par.outputResidFile()); |
---|
1767 | writer.setIsRecon(false); |
---|
1768 | result = writer.write(); |
---|
1769 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1770 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1771 | } |
---|
1772 | } |
---|
1773 | } |
---|
1774 | return result; |
---|
1775 | } |
---|
1776 | |
---|
1777 | OUTCOME Cube::saveSmoothedCube() |
---|
1778 | { |
---|
1779 | std::string report; |
---|
1780 | OUTCOME result=SUCCESS; |
---|
1781 | if(!this->par.getFlagUsePrevious()){ |
---|
1782 | if(this->par.getFlagSmooth() && this->par.getFlagOutputSmooth()){ |
---|
1783 | if(this->par.isVerbose()) |
---|
1784 | std::cout << " Saving smoothed cube to " << this->par.outputSmoothFile() << "... "<<std::flush; |
---|
1785 | WriteSmoothArray writer(this); |
---|
1786 | writer.setFilename(this->par.outputSmoothFile()); |
---|
1787 | result = writer.write(); |
---|
1788 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1789 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1790 | } |
---|
1791 | } |
---|
1792 | return result; |
---|
1793 | } |
---|
1794 | |
---|
1795 | OUTCOME Cube::saveMaskCube() |
---|
1796 | { |
---|
1797 | std::string report; |
---|
1798 | OUTCOME result=SUCCESS; |
---|
1799 | if(this->par.getFlagOutputMask()){ |
---|
1800 | if(this->par.isVerbose()) |
---|
1801 | std::cout << " Saving mask cube to " << this->par.outputMaskFile() << "... "<<std::flush; |
---|
1802 | WriteMaskArray writer(this); |
---|
1803 | writer.setFilename(this->par.outputMaskFile()); |
---|
1804 | OUTCOME result = writer.write(); |
---|
1805 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1806 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1807 | } |
---|
1808 | return result; |
---|
1809 | } |
---|
1810 | |
---|
1811 | OUTCOME Cube::saveMomentMapImage() |
---|
1812 | { |
---|
1813 | std::string report; |
---|
1814 | OUTCOME result=SUCCESS; |
---|
1815 | if(this->par.getFlagOutputMomentMap()){ |
---|
1816 | if(this->par.isVerbose()) |
---|
1817 | std::cout << " Saving moment map to " << this->par.outputMomentMapFile() << "... "<<std::flush; |
---|
1818 | WriteMomentMapArray writer(this); |
---|
1819 | writer.setFilename(this->par.outputMomentMapFile()); |
---|
1820 | OUTCOME result = writer.write(); |
---|
1821 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1822 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1823 | } |
---|
1824 | return result; |
---|
1825 | } |
---|
1826 | |
---|
1827 | OUTCOME Cube::saveMomentMask() |
---|
1828 | { |
---|
1829 | std::string report; |
---|
1830 | OUTCOME result=SUCCESS; |
---|
1831 | if(this->par.getFlagOutputMomentMask()){ |
---|
1832 | if(this->par.isVerbose()) |
---|
1833 | std::cout << " Saving moment-0 mask to " << this->par.outputMomentMaskFile() << "... "<<std::flush; |
---|
1834 | WriteMomentMaskArray writer(this); |
---|
1835 | writer.setFilename(this->par.outputMomentMaskFile()); |
---|
1836 | OUTCOME result = writer.write(); |
---|
1837 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1838 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1839 | } |
---|
1840 | return result; |
---|
1841 | } |
---|
1842 | |
---|
1843 | OUTCOME Cube::saveBaselineCube() |
---|
1844 | { |
---|
1845 | std::string report; |
---|
1846 | OUTCOME result=SUCCESS; |
---|
1847 | if(this->par.getFlagOutputBaseline()){ |
---|
1848 | if(this->par.isVerbose()) |
---|
1849 | std::cout << " Saving baseline cube to " << this->par.outputBaselineFile() << "... "<<std::flush; |
---|
1850 | WriteBaselineArray writer(this); |
---|
1851 | writer.setFilename(this->par.outputBaselineFile()); |
---|
1852 | OUTCOME result = writer.write(); |
---|
1853 | report=(result==FAILURE)?"Failed!":"done."; |
---|
1854 | if(this->par.isVerbose()) std::cout << report << "\n"; |
---|
1855 | } |
---|
1856 | return result; |
---|
1857 | } |
---|
1858 | |
---|
1859 | void Cube::writeToFITS() |
---|
1860 | { |
---|
1861 | this->saveReconstructedCube(); |
---|
1862 | this->saveSmoothedCube(); |
---|
1863 | this->saveMomentMapImage(); |
---|
1864 | this->saveMomentMask(); |
---|
1865 | this->saveBaselineCube(); |
---|
1866 | this->saveMaskCube(); |
---|
1867 | } |
---|
1868 | |
---|
1869 | |
---|
1870 | /****************************************************************/ |
---|
1871 | ///////////////////////////////////////////////////////////// |
---|
1872 | //// Functions for Image class |
---|
1873 | ///////////////////////////////////////////////////////////// |
---|
1874 | |
---|
1875 | Image::Image(size_t size) |
---|
1876 | { |
---|
1877 | this->numPixels = this->numDim = 0; |
---|
1878 | this->minSize = 2; |
---|
1879 | if(!this->arrayAllocated){ |
---|
1880 | this->array = new float[size]; |
---|
1881 | this->arrayAllocated = true; |
---|
1882 | } |
---|
1883 | this->numPixels = size; |
---|
1884 | this->axisDim = new size_t[2]; |
---|
1885 | this->axisDimAllocated = true; |
---|
1886 | this->numDim = 2; |
---|
1887 | } |
---|
1888 | //-------------------------------------------------------------------- |
---|
1889 | |
---|
1890 | Image::Image(size_t *dimensions) |
---|
1891 | { |
---|
1892 | this->numPixels = this->numDim = 0; |
---|
1893 | this->minSize = 2; |
---|
1894 | size_t size = dimensions[0] * dimensions[1]; |
---|
1895 | this->numPixels = size; |
---|
1896 | this->array = new float[size]; |
---|
1897 | this->arrayAllocated = true; |
---|
1898 | this->numDim=2; |
---|
1899 | this->axisDim = new size_t[2]; |
---|
1900 | this->axisDimAllocated = true; |
---|
1901 | for(int i=0;i<2;i++) this->axisDim[i] = dimensions[i]; |
---|
1902 | } |
---|
1903 | //-------------------------------------------------------------------- |
---|
1904 | Image::Image(const Image &i): |
---|
1905 | DataArray(i) |
---|
1906 | { |
---|
1907 | this->operator=(i); |
---|
1908 | } |
---|
1909 | |
---|
1910 | Image& Image::operator=(const Image &i) |
---|
1911 | { |
---|
1912 | if(this==&i) return *this; |
---|
1913 | ((DataArray &) *this) = i; |
---|
1914 | this->minSize = i.minSize; |
---|
1915 | return *this; |
---|
1916 | } |
---|
1917 | |
---|
1918 | //-------------------------------------------------------------------- |
---|
1919 | |
---|
1920 | void Image::saveArray(float *input, size_t size) |
---|
1921 | { |
---|
1922 | /// @details |
---|
1923 | /// Saves the array in input to the pixel array Image::array. |
---|
1924 | /// The size of the array given must be the same as the current number of |
---|
1925 | /// pixels, else an error message is returned and nothing is done. |
---|
1926 | /// \param input The array of values to be saved. |
---|
1927 | /// \param size The size of input. |
---|
1928 | |
---|
1929 | if(size != this->numPixels){ |
---|
1930 | DUCHAMPERROR("Image::saveArray", "Input array different size to existing array. Cannot save."); |
---|
1931 | } |
---|
1932 | else { |
---|
1933 | if(this->numPixels>0 && this->arrayAllocated){ |
---|
1934 | delete [] array; |
---|
1935 | this->arrayAllocated=false; |
---|
1936 | } |
---|
1937 | this->numPixels = size; |
---|
1938 | if(this->numPixels>0){ |
---|
1939 | this->array = new float[size]; |
---|
1940 | this->arrayAllocated = true; |
---|
1941 | for(size_t i=0;i<size;i++) this->array[i] = input[i]; |
---|
1942 | } |
---|
1943 | } |
---|
1944 | } |
---|
1945 | //-------------------------------------------------------------------- |
---|
1946 | |
---|
1947 | void Image::extractSpectrum(float *Array, size_t *dim, size_t pixel) |
---|
1948 | { |
---|
1949 | /// @details |
---|
1950 | /// A function to extract a 1-D spectrum from a 3-D array. |
---|
1951 | /// The array is assumed to be 3-D with the third dimension the spectral one. |
---|
1952 | /// The spectrum extracted is the one lying in the spatial pixel referenced |
---|
1953 | /// by the third argument. |
---|
1954 | /// The extracted spectrum is stored in the pixel array Image::array. |
---|
1955 | /// \param Array The array containing the pixel values, from which |
---|
1956 | /// the spectrum is extracted. |
---|
1957 | /// \param dim The array of dimension values. |
---|
1958 | /// \param pixel The spatial pixel that contains the desired spectrum. |
---|
1959 | |
---|
1960 | if(pixel>=dim[0]*dim[1]){ |
---|
1961 | DUCHAMPERROR("Image::extractSpectrum", "Requested spatial pixel outside allowed range. Cannot save."); |
---|
1962 | } |
---|
1963 | else if(dim[2] != this->numPixels){ |
---|
1964 | DUCHAMPERROR("Image::extractSpectrum", "Input array different size to existing array. Cannot save."); |
---|
1965 | } |
---|
1966 | else { |
---|
1967 | if(this->numPixels>0 && this->arrayAllocated){ |
---|
1968 | delete [] array; |
---|
1969 | this->arrayAllocated=false; |
---|
1970 | } |
---|
1971 | this->numPixels = dim[2]; |
---|
1972 | if(this->numPixels>0){ |
---|
1973 | this->array = new float[dim[2]]; |
---|
1974 | this->arrayAllocated = true; |
---|
1975 | for(size_t z=0;z<dim[2];z++) this->array[z] = Array[z*dim[0]*dim[1] + pixel]; |
---|
1976 | } |
---|
1977 | } |
---|
1978 | } |
---|
1979 | //-------------------------------------------------------------------- |
---|
1980 | |
---|
1981 | void Image::extractSpectrum(Cube &cube, size_t pixel) |
---|
1982 | { |
---|
1983 | /// @details |
---|
1984 | /// A function to extract a 1-D spectrum from a Cube class |
---|
1985 | /// The spectrum extracted is the one lying in the spatial pixel referenced |
---|
1986 | /// by the second argument. |
---|
1987 | /// The extracted spectrum is stored in the pixel array Image::array. |
---|
1988 | /// \param cube The Cube containing the pixel values, from which the spectrum is extracted. |
---|
1989 | /// \param pixel The spatial pixel that contains the desired spectrum. |
---|
1990 | |
---|
1991 | size_t zdim = cube.getDimZ(); |
---|
1992 | size_t spatSize = cube.getDimX()*cube.getDimY(); |
---|
1993 | if(pixel>=spatSize){ |
---|
1994 | DUCHAMPERROR("Image::extractSpectrum", "Requested spatial pixel outside allowed range. Cannot save."); |
---|
1995 | } |
---|
1996 | else if(zdim != this->numPixels){ |
---|
1997 | DUCHAMPERROR("Image::extractSpectrum", "Input array different size to existing array. Cannot save."); |
---|
1998 | } |
---|
1999 | else { |
---|
2000 | if(this->numPixels>0 && this->arrayAllocated){ |
---|
2001 | delete [] array; |
---|
2002 | this->arrayAllocated=false; |
---|
2003 | } |
---|
2004 | this->numPixels = zdim; |
---|
2005 | if(this->numPixels>0){ |
---|
2006 | this->array = new float[zdim]; |
---|
2007 | this->arrayAllocated = true; |
---|
2008 | for(size_t z=0;z<zdim;z++) |
---|
2009 | this->array[z] = cube.getPixValue(z*spatSize + pixel); |
---|
2010 | } |
---|
2011 | } |
---|
2012 | } |
---|
2013 | //-------------------------------------------------------------------- |
---|
2014 | |
---|
2015 | void Image::extractImage(float *Array, size_t *dim, size_t channel) |
---|
2016 | { |
---|
2017 | /// @details |
---|
2018 | /// A function to extract a 2-D image from a 3-D array. |
---|
2019 | /// The array is assumed to be 3-D with the third dimension the spectral one. |
---|
2020 | /// The dimensions of the array are in the dim[] array. |
---|
2021 | /// The image extracted is the one lying in the channel referenced |
---|
2022 | /// by the third argument. |
---|
2023 | /// The extracted image is stored in the pixel array Image::array. |
---|
2024 | /// \param Array The array containing the pixel values, from which the image is extracted. |
---|
2025 | /// \param dim The array of dimension values. |
---|
2026 | /// \param channel The spectral channel that contains the desired image. |
---|
2027 | |
---|
2028 | size_t spatSize = dim[0]*dim[1]; |
---|
2029 | if(channel>=dim[2]){ |
---|
2030 | DUCHAMPERROR("Image::extractImage", "Requested channel outside allowed range. Cannot save."); |
---|
2031 | } |
---|
2032 | else if(spatSize != this->numPixels){ |
---|
2033 | DUCHAMPERROR("Image::extractImage", "Input array different size to existing array. Cannot save."); |
---|
2034 | } |
---|
2035 | else { |
---|
2036 | if(this->numPixels>0 && this->arrayAllocated){ |
---|
2037 | delete [] array; |
---|
2038 | this->arrayAllocated = false; |
---|
2039 | } |
---|
2040 | this->numPixels = spatSize; |
---|
2041 | if(this->numPixels>0){ |
---|
2042 | this->array = new float[spatSize]; |
---|
2043 | this->arrayAllocated = true; |
---|
2044 | for(size_t npix=0; npix<spatSize; npix++) |
---|
2045 | this->array[npix] = Array[channel*spatSize + npix]; |
---|
2046 | } |
---|
2047 | } |
---|
2048 | } |
---|
2049 | //-------------------------------------------------------------------- |
---|
2050 | |
---|
2051 | void Image::extractImage(Cube &cube, size_t channel) |
---|
2052 | { |
---|
2053 | /// @details |
---|
2054 | /// A function to extract a 2-D image from Cube class. |
---|
2055 | /// The image extracted is the one lying in the channel referenced |
---|
2056 | /// by the second argument. |
---|
2057 | /// The extracted image is stored in the pixel array Image::array. |
---|
2058 | /// \param cube The Cube containing the pixel values, from which the image is extracted. |
---|
2059 | /// \param channel The spectral channel that contains the desired image. |
---|
2060 | |
---|
2061 | size_t spatSize = cube.getDimX()*cube.getDimY(); |
---|
2062 | if(channel>=cube.getDimZ()){ |
---|
2063 | DUCHAMPERROR("Image::extractImage", "Requested channel outside allowed range. Cannot save."); |
---|
2064 | } |
---|
2065 | else if(spatSize != this->numPixels){ |
---|
2066 | DUCHAMPERROR("Image::extractImage", "Input array different size to existing array. Cannot save."); |
---|
2067 | } |
---|
2068 | else { |
---|
2069 | if(this->numPixels>0 && this->arrayAllocated){ |
---|
2070 | delete [] array; |
---|
2071 | this->arrayAllocated=false; |
---|
2072 | } |
---|
2073 | this->numPixels = spatSize; |
---|
2074 | if(this->numPixels>0){ |
---|
2075 | this->array = new float[spatSize]; |
---|
2076 | this->arrayAllocated = true; |
---|
2077 | for(size_t npix=0; npix<spatSize; npix++) |
---|
2078 | this->array[npix] = cube.getPixValue(channel*spatSize + npix); |
---|
2079 | } |
---|
2080 | } |
---|
2081 | } |
---|
2082 | //-------------------------------------------------------------------- |
---|
2083 | |
---|
2084 | void Image::removeFlaggedChannels() |
---|
2085 | { |
---|
2086 | /// @details |
---|
2087 | /// A function to remove the flagged channels from a 1-D spectrum. |
---|
2088 | /// The array in this Image is assumed to be 1-D, with only the first axisDim |
---|
2089 | /// equal to 1. |
---|
2090 | /// The values of the flagged channels are set to 0, unless they are BLANK. |
---|
2091 | |
---|
2092 | if(this->axisDim[1]==1) { |
---|
2093 | |
---|
2094 | std::vector<int> flaggedChans = this->par.getFlaggedChannels(); |
---|
2095 | for(std::vector<int>::iterator chan = flaggedChans.begin();chan!=flaggedChans.end();chan++){ |
---|
2096 | // channels are zero-based |
---|
2097 | if(!this->isBlank(*chan)) this->array[*chan]=0.; |
---|
2098 | } |
---|
2099 | |
---|
2100 | } |
---|
2101 | } |
---|
2102 | |
---|
2103 | //-------------------------------------------------------------------- |
---|
2104 | |
---|
2105 | std::vector<Object2D> Image::findSources2D() |
---|
2106 | { |
---|
2107 | std::vector<bool> thresholdedArray(this->axisDim[0]*this->axisDim[1]); |
---|
2108 | for(size_t posY=0;posY<this->axisDim[1];posY++){ |
---|
2109 | for(size_t posX=0;posX<this->axisDim[0];posX++){ |
---|
2110 | size_t loc = posX + this->axisDim[0]*posY; |
---|
2111 | thresholdedArray[loc] = this->isDetection(posX,posY); |
---|
2112 | } |
---|
2113 | } |
---|
2114 | return lutz_detect(thresholdedArray, this->axisDim[0], this->axisDim[1], this->minSize); |
---|
2115 | } |
---|
2116 | |
---|
2117 | std::vector<Scan> Image::findSources1D() |
---|
2118 | { |
---|
2119 | std::vector<bool> thresholdedArray(this->axisDim[0]); |
---|
2120 | for(size_t posX=0;posX<this->axisDim[0];posX++){ |
---|
2121 | thresholdedArray[posX] = this->isDetection(posX,0); |
---|
2122 | } |
---|
2123 | return spectrumDetect(thresholdedArray, this->axisDim[0], this->minSize); |
---|
2124 | } |
---|
2125 | |
---|
2126 | |
---|
2127 | std::vector< std::vector<PixelInfo::Voxel> > Cube::getObjVoxList() |
---|
2128 | { |
---|
2129 | |
---|
2130 | std::vector< std::vector<PixelInfo::Voxel> > biglist; |
---|
2131 | |
---|
2132 | std::vector<Detection>::iterator obj; |
---|
2133 | for(obj=this->objectList->begin(); obj<this->objectList->end(); obj++) { |
---|
2134 | |
---|
2135 | Cube *subcube = new Cube; |
---|
2136 | subcube->pars() = this->par; |
---|
2137 | subcube->pars().setVerbosity(false); |
---|
2138 | subcube->pars().setFlagSubsection(true); |
---|
2139 | duchamp::Section sec = obj->getBoundingSection(); |
---|
2140 | subcube->pars().setSubsection( sec.getSection() ); |
---|
2141 | if(subcube->pars().verifySubsection() == FAILURE) |
---|
2142 | DUCHAMPERROR("get object voxel list","Unable to verify the subsection - something's wrong!"); |
---|
2143 | if(subcube->getCube() == FAILURE) |
---|
2144 | DUCHAMPERROR("get object voxel list","Unable to read the FITS file - something's wrong!"); |
---|
2145 | std::vector<PixelInfo::Voxel> voxlist = obj->getPixelSet(); |
---|
2146 | std::vector<PixelInfo::Voxel>::iterator vox; |
---|
2147 | for(vox=voxlist.begin(); vox<voxlist.end(); vox++){ |
---|
2148 | size_t pix = (vox->getX()-subcube->pars().getXOffset()) + |
---|
2149 | subcube->getDimX()*(vox->getY()-subcube->pars().getYOffset()) + |
---|
2150 | subcube->getDimX()*subcube->getDimY()*(vox->getZ()-subcube->pars().getZOffset()); |
---|
2151 | vox->setF( subcube->getPixValue(pix) ); |
---|
2152 | } |
---|
2153 | biglist.push_back(voxlist); |
---|
2154 | delete subcube; |
---|
2155 | |
---|
2156 | } |
---|
2157 | |
---|
2158 | return biglist; |
---|
2159 | |
---|
2160 | } |
---|
2161 | |
---|
2162 | } |
---|