1 | //#--------------------------------------------------------------------------- |
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2 | //# SDMath.cc: A collection of single dish mathematical operations |
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3 | //#--------------------------------------------------------------------------- |
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4 | //# Copyright (C) 2004 |
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5 | //# ATNF |
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6 | //# |
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7 | //# This program is free software; you can redistribute it and/or modify it |
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8 | //# under the terms of the GNU General Public License as published by the Free |
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9 | //# Software Foundation; either version 2 of the License, or (at your option) |
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10 | //# any later version. |
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11 | //# |
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12 | //# This program is distributed in the hope that it will be useful, but |
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13 | //# WITHOUT ANY WARRANTY; without even the implied warranty of |
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14 | //# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General |
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15 | //# Public License for more details. |
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16 | //# |
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17 | //# You should have received a copy of the GNU General Public License along |
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18 | //# with this program; if not, write to the Free Software Foundation, Inc., |
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19 | //# 675 Massachusetts Ave, Cambridge, MA 02139, USA. |
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20 | //# |
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21 | //# Correspondence concerning this software should be addressed as follows: |
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22 | //# Internet email: Malte.Marquarding@csiro.au |
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23 | //# Postal address: Malte Marquarding, |
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24 | //# Australia Telescope National Facility, |
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25 | //# P.O. Box 76, |
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26 | //# Epping, NSW, 2121, |
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27 | //# AUSTRALIA |
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28 | //# |
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29 | //# $Id: |
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30 | //#--------------------------------------------------------------------------- |
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31 | #include <vector> |
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32 | |
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33 | #include <casa/aips.h> |
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34 | #include <casa/BasicSL/String.h> |
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35 | #include <casa/Arrays/IPosition.h> |
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36 | #include <casa/Arrays/Array.h> |
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37 | #include <casa/Arrays/ArrayIter.h> |
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38 | #include <casa/Arrays/VectorIter.h> |
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39 | #include <casa/Arrays/ArrayMath.h> |
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40 | #include <casa/Arrays/ArrayLogical.h> |
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41 | #include <casa/Arrays/MaskedArray.h> |
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42 | #include <casa/Arrays/MaskArrMath.h> |
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43 | #include <casa/Arrays/MaskArrLogi.h> |
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44 | #include <casa/Containers/Block.h> |
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45 | #include <casa/Quanta/QC.h> |
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46 | #include <casa/Utilities/Assert.h> |
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47 | #include <casa/Exceptions.h> |
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48 | |
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49 | #include <scimath/Mathematics/VectorKernel.h> |
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50 | #include <scimath/Mathematics/Convolver.h> |
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51 | |
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52 | #include <tables/Tables/Table.h> |
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53 | #include <tables/Tables/ScalarColumn.h> |
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54 | #include <tables/Tables/ArrayColumn.h> |
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55 | |
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56 | #include <lattices/Lattices/LatticeUtilities.h> |
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57 | #include <lattices/Lattices/RebinLattice.h> |
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58 | #include <coordinates/Coordinates/SpectralCoordinate.h> |
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59 | #include <coordinates/Coordinates/CoordinateSystem.h> |
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60 | #include <coordinates/Coordinates/CoordinateUtil.h> |
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61 | #include <coordinates/Coordinates/VelocityAligner.h> |
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62 | |
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63 | #include "MathUtils.h" |
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64 | #include "Definitions.h" |
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65 | #include "SDContainer.h" |
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66 | #include "SDMemTable.h" |
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67 | |
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68 | #include "SDMath.h" |
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69 | |
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70 | using namespace casa; |
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71 | using namespace asap; |
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72 | |
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73 | |
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74 | SDMath::SDMath() |
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75 | {;} |
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76 | |
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77 | SDMath::SDMath(const SDMath& other) |
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78 | { |
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79 | |
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80 | // No state |
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81 | |
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82 | } |
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83 | |
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84 | SDMath& SDMath::operator=(const SDMath& other) |
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85 | { |
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86 | if (this != &other) { |
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87 | // No state |
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88 | } |
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89 | return *this; |
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90 | } |
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91 | |
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92 | SDMath::~SDMath() |
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93 | {;} |
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94 | |
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95 | |
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96 | CountedPtr<SDMemTable> SDMath::average(const Block<CountedPtr<SDMemTable> >& in, |
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97 | const Vector<Bool>& mask, Bool scanAv, |
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98 | const std::string& weightStr) |
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99 | //Bool alignVelocity) |
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100 | // |
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101 | // Weighted averaging of spectra from one or more Tables. |
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102 | // |
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103 | { |
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104 | Bool alignVelocity = False; |
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105 | |
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106 | // Convert weight type |
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107 | |
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108 | WeightType wtType = NONE; |
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109 | convertWeightString(wtType, weightStr); |
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110 | |
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111 | // Create output Table by cloning from the first table |
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112 | |
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113 | SDMemTable* pTabOut = new SDMemTable(*in[0],True); |
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114 | |
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115 | // Setup |
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116 | |
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117 | IPosition shp = in[0]->rowAsMaskedArray(0).shape(); // Must not change |
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118 | Array<Float> arr(shp); |
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119 | Array<Bool> barr(shp); |
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120 | const Bool useMask = (mask.nelements() == shp(asap::ChanAxis)); |
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121 | |
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122 | // Columns from Tables |
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123 | |
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124 | ROArrayColumn<Float> tSysCol; |
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125 | ROScalarColumn<Double> mjdCol; |
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126 | ROScalarColumn<String> srcNameCol; |
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127 | ROScalarColumn<Double> intCol; |
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128 | ROArrayColumn<uInt> fqIDCol; |
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129 | |
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130 | // Create accumulation MaskedArray. We accumulate for each channel,if,pol,beam |
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131 | // Note that the mask of the accumulation array will ALWAYS remain ALL True. |
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132 | // The MA is only used so that when data which is masked Bad is added to it, |
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133 | // that data does not contribute. |
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134 | |
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135 | Array<Float> zero(shp); |
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136 | zero=0.0; |
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137 | Array<Bool> good(shp); |
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138 | good = True; |
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139 | MaskedArray<Float> sum(zero,good); |
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140 | |
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141 | // Counter arrays |
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142 | |
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143 | Array<Float> nPts(shp); // Number of points |
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144 | nPts = 0.0; |
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145 | Array<Float> nInc(shp); // Increment |
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146 | nInc = 1.0; |
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147 | |
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148 | // Create accumulation Array for variance. We accumulate for |
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149 | // each if,pol,beam, but average over channel. So we need |
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150 | // a shape with one less axis dropping channels. |
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151 | |
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152 | const uInt nAxesSub = shp.nelements() - 1; |
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153 | IPosition shp2(nAxesSub); |
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154 | for (uInt i=0,j=0; i<(nAxesSub+1); i++) { |
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155 | if (i!=asap::ChanAxis) { |
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156 | shp2(j) = shp(i); |
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157 | j++; |
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158 | } |
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159 | } |
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160 | Array<Float> sumSq(shp2); |
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161 | sumSq = 0.0; |
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162 | IPosition pos2(nAxesSub,0); // For indexing |
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163 | |
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164 | // Time-related accumulators |
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165 | |
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166 | Double time; |
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167 | Double timeSum = 0.0; |
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168 | Double intSum = 0.0; |
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169 | Double interval = 0.0; |
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170 | |
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171 | // To get the right shape for the Tsys accumulator we need to |
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172 | // access a column from the first table. The shape of this |
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173 | // array must not change |
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174 | |
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175 | Array<Float> tSysSum; |
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176 | { |
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177 | const Table& tabIn = in[0]->table(); |
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178 | tSysCol.attach(tabIn,"TSYS"); |
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179 | tSysSum.resize(tSysCol.shape(0)); |
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180 | } |
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181 | tSysSum =0.0; |
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182 | Array<Float> tSys; |
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183 | |
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184 | // Scan and row tracking |
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185 | |
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186 | Int oldScanID = 0; |
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187 | Int outScanID = 0; |
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188 | Int scanID = 0; |
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189 | Int rowStart = 0; |
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190 | Int nAccum = 0; |
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191 | Int tableStart = 0; |
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192 | |
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193 | // Source and FreqID |
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194 | |
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195 | String sourceName, oldSourceName, sourceNameStart; |
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196 | Vector<uInt> freqID, freqIDStart, oldFreqID; |
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197 | |
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198 | // Velocity Aligner. We need an aligner for each Direction and FreqID |
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199 | // combination. I don't think there is anyway to know how many |
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200 | // directions there are. |
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201 | // For now, assume all Tables have the same Frequency Table |
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202 | |
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203 | /* |
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204 | { |
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205 | MEpoch::Ref timeRef(MEpoch::UTC); // Should be in header |
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206 | MDirection::Types dirRef(MDirection::J2000); // Should be in header |
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207 | // |
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208 | SDHeader sh = in[0].getSDHeader(); |
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209 | const uInt nChan = sh.nchan; |
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210 | // |
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211 | const SDFrequencyTable freqTab = in[0]->getSDFreqTable(); |
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212 | const uInt nFreqID = freqTab.length(); |
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213 | PtrBlock<const VelocityAligner<Float>* > vA(nFreqID); |
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214 | |
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215 | // Get first time from first table |
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216 | |
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217 | const Table& tabIn0 = in[0]->table(); |
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218 | mjdCol.attach(tabIn0, "TIME"); |
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219 | Double dTmp; |
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220 | mjdCol.get(0, dTmp); |
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221 | MVEpoch tmp2(Quantum<Double>(dTmp, Unit(String("d")))); |
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222 | MEpoch epoch(tmp2, timeRef); |
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223 | // |
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224 | for (uInt freqID=0; freqID<nFreqID; freqID++) { |
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225 | SpectralCoordinate sC = in[0]->getCoordinate(freqID); |
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226 | vA[freqID] = new VelocityAligner<Float>(sC, nChan, epoch, const MDirection& dir, |
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227 | const MPosition& pos, const String& velUnit, |
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228 | MDoppler::Types velType, MFrequency::Types velFreqSystem) |
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229 | } |
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230 | } |
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231 | */ |
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232 | |
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233 | // Loop over tables |
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234 | |
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235 | Float fac = 1.0; |
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236 | const uInt nTables = in.nelements(); |
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237 | for (uInt iTab=0; iTab<nTables; iTab++) { |
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238 | |
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239 | // Should check that the frequency tables don't change if doing VelocityAlignment |
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240 | |
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241 | // Attach columns to Table |
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242 | |
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243 | const Table& tabIn = in[iTab]->table(); |
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244 | tSysCol.attach(tabIn, "TSYS"); |
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245 | mjdCol.attach(tabIn, "TIME"); |
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246 | srcNameCol.attach(tabIn, "SRCNAME"); |
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247 | intCol.attach(tabIn, "INTERVAL"); |
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248 | fqIDCol.attach(tabIn, "FREQID"); |
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249 | |
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250 | // Loop over rows in Table |
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251 | |
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252 | const uInt nRows = in[iTab]->nRow(); |
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253 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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254 | |
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255 | // Check conformance |
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256 | |
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257 | IPosition shp2 = in[iTab]->rowAsMaskedArray(iRow).shape(); |
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258 | if (!shp.isEqual(shp2)) { |
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259 | throw (AipsError("Shapes for all rows must be the same")); |
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260 | } |
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261 | |
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262 | // If we are not doing scan averages, make checks for source and |
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263 | // frequency setup and warn if averaging across them |
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264 | |
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265 | // Get copy of Scan Container for this row |
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266 | |
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267 | SDContainer sc = in[iTab]->getSDContainer(iRow); |
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268 | scanID = sc.scanid; |
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269 | |
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270 | // Get quantities from columns |
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271 | |
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272 | srcNameCol.getScalar(iRow, sourceName); |
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273 | mjdCol.get(iRow, time); |
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274 | tSysCol.get(iRow, tSys); |
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275 | intCol.get(iRow, interval); |
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276 | fqIDCol.get(iRow, freqID); |
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277 | |
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278 | // Initialize first source and freqID |
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279 | |
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280 | if (iRow==0 && iTab==0) { |
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281 | sourceNameStart = sourceName; |
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282 | freqIDStart = freqID; |
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283 | } |
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284 | |
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285 | // If we are doing scan averages, see if we are at the end of an |
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286 | // accumulation period (scan). We must check soutce names too, |
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287 | // since we might have two tables with one scan each but different |
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288 | // source names; we shouldn't average different sources together |
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289 | |
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290 | if (scanAv && ( (scanID != oldScanID) || |
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291 | (iRow==0 && iTab>0 && sourceName!=oldSourceName))) { |
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292 | |
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293 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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294 | |
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295 | normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub); |
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296 | |
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297 | // Fill scan container. The source and freqID come from the |
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298 | // first row of the first table that went into this average ( |
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299 | // should be the same for all rows in the scan average) |
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300 | |
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301 | Float nR(nAccum); |
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302 | fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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303 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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304 | |
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305 | // Write container out to Table |
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306 | |
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307 | pTabOut->putSDContainer(sc); |
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308 | |
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309 | // Reset accumulators |
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310 | |
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311 | sum = 0.0; |
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312 | sumSq = 0.0; |
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313 | nAccum = 0; |
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314 | // |
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315 | tSysSum =0.0; |
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316 | timeSum = 0.0; |
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317 | intSum = 0.0; |
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318 | nPts = 0.0; |
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319 | |
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320 | // Increment |
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321 | |
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322 | rowStart = iRow; // First row for next accumulation |
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323 | tableStart = iTab; // First table for next accumulation |
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324 | sourceNameStart = sourceName; // First source name for next accumulation |
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325 | freqIDStart = freqID; // First FreqID for next accumulation |
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326 | // |
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327 | oldScanID = scanID; |
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328 | outScanID += 1; // Scan ID for next accumulation period |
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329 | |
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330 | } |
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331 | |
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332 | // Accumulate |
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333 | |
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334 | accumulate(timeSum, intSum, nAccum, sum, sumSq, nPts, tSysSum, |
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335 | tSys, nInc, mask, time, interval, in, iTab, iRow, asap::ChanAxis, |
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336 | nAxesSub, useMask, wtType); |
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337 | // |
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338 | oldSourceName = sourceName; |
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339 | oldFreqID = freqID; |
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340 | } |
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341 | } |
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342 | |
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343 | // OK at this point we have accumulation data which is either |
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344 | // - accumulated from all tables into one row |
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345 | // or |
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346 | // - accumulated from the last scan average |
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347 | // |
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348 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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349 | normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub); |
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350 | |
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351 | // Create and fill container. The container we clone will be from |
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352 | // the last Table and the first row that went into the current |
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353 | // accumulation. It probably doesn't matter that much really... |
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354 | |
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355 | Float nR(nAccum); |
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356 | SDContainer sc = in[tableStart]->getSDContainer(rowStart); |
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357 | fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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358 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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359 | pTabOut->putSDContainer(sc); |
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360 | // |
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361 | return CountedPtr<SDMemTable>(pTabOut); |
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362 | } |
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363 | |
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364 | |
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365 | |
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366 | CountedPtr<SDMemTable> |
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367 | SDMath::quotient(const CountedPtr<SDMemTable>& on, |
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368 | const CountedPtr<SDMemTable>& off) |
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369 | { |
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370 | // |
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371 | // Compute quotient spectrum |
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372 | // |
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373 | const uInt nRows = on->nRow(); |
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374 | if (off->nRow() != nRows) { |
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375 | throw (AipsError("Input Scan Tables must have the same number of rows")); |
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376 | } |
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377 | |
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378 | // Input Tables and columns |
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379 | |
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380 | Table ton = on->table(); |
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381 | Table toff = off->table(); |
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382 | ROArrayColumn<Float> tsys(toff, "TSYS"); |
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383 | ROScalarColumn<Double> mjd(ton, "TIME"); |
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384 | ROScalarColumn<Double> integr(ton, "INTERVAL"); |
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385 | ROScalarColumn<String> srcn(ton, "SRCNAME"); |
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386 | ROArrayColumn<uInt> freqidc(ton, "FREQID"); |
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387 | |
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388 | // Output Table cloned from input |
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389 | |
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390 | SDMemTable* pTabOut = new SDMemTable(*on, True); |
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391 | |
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392 | // Loop over rows |
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393 | |
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394 | for (uInt i=0; i<nRows; i++) { |
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395 | MaskedArray<Float> mon(on->rowAsMaskedArray(i)); |
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396 | MaskedArray<Float> moff(off->rowAsMaskedArray(i)); |
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397 | IPosition ipon = mon.shape(); |
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398 | IPosition ipoff = moff.shape(); |
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399 | // |
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400 | Array<Float> tsarr; |
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401 | tsys.get(i, tsarr); |
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402 | if (ipon != ipoff && ipon != tsarr.shape()) { |
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403 | throw(AipsError("on/off not conformant")); |
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404 | } |
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405 | |
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406 | // Compute quotient |
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407 | |
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408 | MaskedArray<Float> tmp = (mon-moff); |
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409 | Array<Float> out(tmp.getArray()); |
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410 | out /= moff; |
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411 | out *= tsarr; |
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412 | Array<Bool> outflagsb = mon.getMask() && moff.getMask(); |
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413 | |
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414 | // Fill container for this row |
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415 | |
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416 | SDContainer sc = on->getSDContainer(i); |
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417 | // |
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418 | putDataInSDC(sc, out, outflagsb); |
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419 | sc.putTsys(tsarr); |
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420 | sc.scanid = i; |
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421 | |
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422 | // Put new row in output Table |
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423 | |
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424 | pTabOut->putSDContainer(sc); |
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425 | } |
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426 | // |
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427 | return CountedPtr<SDMemTable>(pTabOut); |
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428 | } |
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429 | |
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430 | |
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431 | |
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432 | std::vector<float> SDMath::statistic(const CountedPtr<SDMemTable>& in, |
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433 | const std::vector<bool>& mask, |
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434 | const String& which) |
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435 | // |
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436 | // Perhaps iteration over pol/beam/if should be in here |
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437 | // and inside the nrow iteration ? |
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438 | // |
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439 | { |
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440 | const uInt nRow = in->nRow(); |
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441 | std::vector<float> result(nRow); |
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442 | Vector<Bool> msk(mask); |
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443 | |
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444 | // Specify cursor location |
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445 | |
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446 | IPosition start, end; |
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447 | getCursorLocation(start, end, *in); |
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448 | |
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449 | // Loop over rows |
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450 | |
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451 | const uInt nEl = msk.nelements(); |
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452 | for (uInt ii=0; ii < in->nRow(); ++ii) { |
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453 | |
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454 | // Get row and deconstruct |
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455 | |
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456 | MaskedArray<Float> marr(in->rowAsMaskedArray(ii)); |
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457 | Array<Float> arr = marr.getArray(); |
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458 | Array<Bool> barr = marr.getMask(); |
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459 | |
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460 | // Access desired piece of data |
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461 | |
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462 | Array<Float> v((arr(start,end)).nonDegenerate()); |
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463 | Array<Bool> m((barr(start,end)).nonDegenerate()); |
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464 | |
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465 | // Apply OTF mask |
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466 | |
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467 | MaskedArray<Float> tmp; |
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468 | if (m.nelements()==nEl) { |
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469 | tmp.setData(v,m&&msk); |
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470 | } else { |
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471 | tmp.setData(v,m); |
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472 | } |
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473 | |
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474 | // Get statistic |
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475 | |
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476 | result[ii] = mathutil::statistics(which, tmp); |
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477 | } |
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478 | // |
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479 | return result; |
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480 | } |
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481 | |
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482 | |
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483 | SDMemTable* SDMath::bin(const SDMemTable& in, Int width) |
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484 | { |
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485 | SDHeader sh = in.getSDHeader(); |
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486 | SDMemTable* pTabOut = new SDMemTable(in, True); |
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487 | |
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488 | // Bin up SpectralCoordinates |
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489 | |
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490 | IPosition factors(1); |
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491 | factors(0) = width; |
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492 | for (uInt j=0; j<in.nCoordinates(); ++j) { |
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493 | CoordinateSystem cSys; |
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494 | cSys.addCoordinate(in.getCoordinate(j)); |
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495 | CoordinateSystem cSysBin = |
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496 | CoordinateUtil::makeBinnedCoordinateSystem(factors, cSys, False); |
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497 | // |
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498 | SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0); |
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499 | pTabOut->setCoordinate(sCBin, j); |
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500 | } |
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501 | |
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502 | // Use RebinLattice to find shape |
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503 | |
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504 | IPosition shapeIn(1,sh.nchan); |
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505 | IPosition shapeOut = RebinLattice<Float>::rebinShape(shapeIn, factors); |
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506 | sh.nchan = shapeOut(0); |
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507 | pTabOut->putSDHeader(sh); |
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508 | |
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509 | |
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510 | // Loop over rows and bin along channel axis |
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511 | |
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512 | for (uInt i=0; i < in.nRow(); ++i) { |
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513 | SDContainer sc = in.getSDContainer(i); |
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514 | // |
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515 | Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape |
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516 | |
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517 | // Bin up spectrum |
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518 | |
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519 | MaskedArray<Float> marr(in.rowAsMaskedArray(i)); |
---|
520 | MaskedArray<Float> marrout; |
---|
521 | LatticeUtilities::bin(marrout, marr, asap::ChanAxis, width); |
---|
522 | |
---|
523 | // Put back the binned data and flags |
---|
524 | |
---|
525 | IPosition ip2 = marrout.shape(); |
---|
526 | sc.resize(ip2); |
---|
527 | // |
---|
528 | putDataInSDC(sc, marrout.getArray(), marrout.getMask()); |
---|
529 | |
---|
530 | // Bin up Tsys. |
---|
531 | |
---|
532 | Array<Bool> allGood(tSys.shape(),True); |
---|
533 | MaskedArray<Float> tSysIn(tSys, allGood, True); |
---|
534 | // |
---|
535 | MaskedArray<Float> tSysOut; |
---|
536 | LatticeUtilities::bin(tSysOut, tSysIn, asap::ChanAxis, width); |
---|
537 | sc.putTsys(tSysOut.getArray()); |
---|
538 | // |
---|
539 | pTabOut->putSDContainer(sc); |
---|
540 | } |
---|
541 | return pTabOut; |
---|
542 | } |
---|
543 | |
---|
544 | SDMemTable* SDMath::simpleOperate(const SDMemTable& in, Float val, Bool doAll, |
---|
545 | uInt what) |
---|
546 | // |
---|
547 | // what = 0 Multiply |
---|
548 | // 1 Add |
---|
549 | { |
---|
550 | SDMemTable* pOut = new SDMemTable(in,False); |
---|
551 | const Table& tOut = pOut->table(); |
---|
552 | ArrayColumn<Float> spec(tOut,"SPECTRA"); |
---|
553 | // |
---|
554 | if (doAll) { |
---|
555 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
556 | |
---|
557 | // Get |
---|
558 | |
---|
559 | MaskedArray<Float> marr(pOut->rowAsMaskedArray(i)); |
---|
560 | |
---|
561 | // Operate |
---|
562 | |
---|
563 | if (what==0) { |
---|
564 | marr *= val; |
---|
565 | } else if (what==1) { |
---|
566 | marr += val; |
---|
567 | } |
---|
568 | |
---|
569 | // Put |
---|
570 | |
---|
571 | spec.put(i, marr.getArray()); |
---|
572 | } |
---|
573 | } else { |
---|
574 | |
---|
575 | // Get cursor location |
---|
576 | |
---|
577 | IPosition start, end; |
---|
578 | getCursorLocation(start, end, in); |
---|
579 | // |
---|
580 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
581 | |
---|
582 | // Get |
---|
583 | |
---|
584 | MaskedArray<Float> dataIn(pOut->rowAsMaskedArray(i)); |
---|
585 | |
---|
586 | // Modify. More work than we would like to deal with the mask |
---|
587 | |
---|
588 | Array<Float>& values = dataIn.getRWArray(); |
---|
589 | Array<Bool> mask(dataIn.getMask()); |
---|
590 | // |
---|
591 | Array<Float> values2 = values(start,end); |
---|
592 | Array<Bool> mask2 = mask(start,end); |
---|
593 | MaskedArray<Float> t(values2,mask2); |
---|
594 | if (what==0) { |
---|
595 | t *= val; |
---|
596 | } else if (what==1) { |
---|
597 | t += val; |
---|
598 | } |
---|
599 | values(start, end) = t.getArray(); // Write back into 'dataIn' |
---|
600 | |
---|
601 | // Put |
---|
602 | spec.put(i, dataIn.getArray()); |
---|
603 | } |
---|
604 | } |
---|
605 | // |
---|
606 | return pOut; |
---|
607 | } |
---|
608 | |
---|
609 | |
---|
610 | |
---|
611 | SDMemTable* SDMath::averagePol(const SDMemTable& in, const Vector<Bool>& mask) |
---|
612 | // |
---|
613 | // Average all polarizations together, weighted by variance |
---|
614 | // |
---|
615 | { |
---|
616 | // WeightType wtType = NONE; |
---|
617 | // convertWeightString(wtType, weight); |
---|
618 | |
---|
619 | const uInt nRows = in.nRow(); |
---|
620 | const uInt polAxis = asap::PolAxis; // Polarization axis |
---|
621 | const uInt chanAxis = asap::ChanAxis; // Spectrum axis |
---|
622 | |
---|
623 | // Create output Table and reshape number of polarizations |
---|
624 | |
---|
625 | Bool clear=True; |
---|
626 | SDMemTable* pTabOut = new SDMemTable(in, clear); |
---|
627 | SDHeader header = pTabOut->getSDHeader(); |
---|
628 | header.npol = 1; |
---|
629 | pTabOut->putSDHeader(header); |
---|
630 | |
---|
631 | // Shape of input and output data |
---|
632 | |
---|
633 | const IPosition& shapeIn = in.rowAsMaskedArray(0u, False).shape(); |
---|
634 | IPosition shapeOut(shapeIn); |
---|
635 | shapeOut(polAxis) = 1; // Average all polarizations |
---|
636 | // |
---|
637 | const uInt nChan = shapeIn(chanAxis); |
---|
638 | const IPosition vecShapeOut(4,1,1,1,nChan); // A multi-dim form of a Vector shape |
---|
639 | IPosition start(4), end(4); |
---|
640 | |
---|
641 | // Output arrays |
---|
642 | |
---|
643 | Array<Float> outData(shapeOut, 0.0); |
---|
644 | Array<Bool> outMask(shapeOut, True); |
---|
645 | const IPosition axes(2, 2, 3); // pol-channel plane |
---|
646 | // |
---|
647 | const Bool useMask = (mask.nelements() == shapeIn(chanAxis)); |
---|
648 | |
---|
649 | // Loop over rows |
---|
650 | |
---|
651 | for (uInt iRow=0; iRow<nRows; iRow++) { |
---|
652 | |
---|
653 | // Get data for this row |
---|
654 | |
---|
655 | MaskedArray<Float> marr(in.rowAsMaskedArray(iRow)); |
---|
656 | Array<Float>& arr = marr.getRWArray(); |
---|
657 | const Array<Bool>& barr = marr.getMask(); |
---|
658 | |
---|
659 | // Make iterators to iterate by pol-channel planes |
---|
660 | |
---|
661 | ReadOnlyArrayIterator<Float> itDataPlane(arr, axes); |
---|
662 | ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes); |
---|
663 | |
---|
664 | // Accumulations |
---|
665 | |
---|
666 | Float fac = 1.0; |
---|
667 | Vector<Float> vecSum(nChan,0.0); |
---|
668 | |
---|
669 | // Iterate through data by pol-channel planes |
---|
670 | |
---|
671 | while (!itDataPlane.pastEnd()) { |
---|
672 | |
---|
673 | // Iterate through plane by polarization and accumulate Vectors |
---|
674 | |
---|
675 | Vector<Float> t1(nChan); t1 = 0.0; |
---|
676 | Vector<Bool> t2(nChan); t2 = True; |
---|
677 | MaskedArray<Float> vecSum(t1,t2); |
---|
678 | Float varSum = 0.0; |
---|
679 | { |
---|
680 | ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1); |
---|
681 | ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1); |
---|
682 | while (!itDataVec.pastEnd()) { |
---|
683 | |
---|
684 | // Create MA of data & mask (optionally including OTF mask) and get variance |
---|
685 | |
---|
686 | if (useMask) { |
---|
687 | const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector()); |
---|
688 | fac = 1.0 / variance(spec); |
---|
689 | } else { |
---|
690 | const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector()); |
---|
691 | fac = 1.0 / variance(spec); |
---|
692 | } |
---|
693 | |
---|
694 | // Normalize spectrum (without OTF mask) and accumulate |
---|
695 | |
---|
696 | const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector()); |
---|
697 | vecSum += spec; |
---|
698 | varSum += fac; |
---|
699 | |
---|
700 | // Next |
---|
701 | |
---|
702 | itDataVec.next(); |
---|
703 | itMaskVec.next(); |
---|
704 | } |
---|
705 | } |
---|
706 | |
---|
707 | // Normalize summed spectrum |
---|
708 | |
---|
709 | vecSum /= varSum; |
---|
710 | |
---|
711 | // FInd position in input data array. We are iterating by pol-channel |
---|
712 | // plane so all that will change is beam and IF and that's what we want. |
---|
713 | |
---|
714 | IPosition pos = itDataPlane.pos(); |
---|
715 | |
---|
716 | // Write out data. This is a bit messy. We have to reform the Vector |
---|
717 | // accumulator into an Array of shape (1,1,1,nChan) |
---|
718 | |
---|
719 | start = pos; |
---|
720 | end = pos; |
---|
721 | end(chanAxis) = nChan-1; |
---|
722 | outData(start,end) = vecSum.getArray().reform(vecShapeOut); |
---|
723 | outMask(start,end) = vecSum.getMask().reform(vecShapeOut); |
---|
724 | |
---|
725 | // Step to next beam/IF combination |
---|
726 | |
---|
727 | itDataPlane.next(); |
---|
728 | itMaskPlane.next(); |
---|
729 | } |
---|
730 | |
---|
731 | // Generate output container and write it to output table |
---|
732 | |
---|
733 | SDContainer sc = in.getSDContainer(); |
---|
734 | sc.resize(shapeOut); |
---|
735 | // |
---|
736 | putDataInSDC(sc, outData, outMask); |
---|
737 | pTabOut->putSDContainer(sc); |
---|
738 | } |
---|
739 | // |
---|
740 | return pTabOut; |
---|
741 | } |
---|
742 | |
---|
743 | |
---|
744 | SDMemTable* SDMath::smooth(const SDMemTable& in, |
---|
745 | const casa::String& kernelType, |
---|
746 | casa::Float width, Bool doAll) |
---|
747 | { |
---|
748 | |
---|
749 | // Number of channels |
---|
750 | |
---|
751 | const uInt chanAxis = asap::ChanAxis; // Spectral axis |
---|
752 | SDHeader sh = in.getSDHeader(); |
---|
753 | const uInt nChan = sh.nchan; |
---|
754 | |
---|
755 | // Generate Kernel |
---|
756 | |
---|
757 | VectorKernel::KernelTypes type = VectorKernel::toKernelType(kernelType); |
---|
758 | Vector<Float> kernel = VectorKernel::make(type, width, nChan, True, False); |
---|
759 | |
---|
760 | // Generate Convolver |
---|
761 | |
---|
762 | IPosition shape(1,nChan); |
---|
763 | Convolver<Float> conv(kernel, shape); |
---|
764 | |
---|
765 | // New Table |
---|
766 | |
---|
767 | SDMemTable* pTabOut = new SDMemTable(in,True); |
---|
768 | |
---|
769 | // Get cursor location |
---|
770 | |
---|
771 | IPosition start, end; |
---|
772 | getCursorLocation(start, end, in); |
---|
773 | // |
---|
774 | IPosition shapeOut(4,1); |
---|
775 | |
---|
776 | // Output Vectors |
---|
777 | |
---|
778 | Vector<Float> valuesOut(nChan); |
---|
779 | Vector<Bool> maskOut(nChan); |
---|
780 | |
---|
781 | // Loop over rows in Table |
---|
782 | |
---|
783 | for (uInt ri=0; ri < in.nRow(); ++ri) { |
---|
784 | |
---|
785 | // Get copy of data |
---|
786 | |
---|
787 | const MaskedArray<Float>& dataIn(in.rowAsMaskedArray(ri)); |
---|
788 | AlwaysAssert(dataIn.shape()(chanAxis)==nChan, AipsError); |
---|
789 | // |
---|
790 | Array<Float> valuesIn = dataIn.getArray(); |
---|
791 | Array<Bool> maskIn = dataIn.getMask(); |
---|
792 | |
---|
793 | // Branch depending on whether we smooth all locations or just |
---|
794 | // those pointed at by the current selection cursor |
---|
795 | |
---|
796 | if (doAll) { |
---|
797 | uInt axis = asap::ChanAxis; |
---|
798 | VectorIterator<Float> itValues(valuesIn, axis); |
---|
799 | VectorIterator<Bool> itMask(maskIn, axis); |
---|
800 | while (!itValues.pastEnd()) { |
---|
801 | |
---|
802 | // Smooth |
---|
803 | if (kernelType==VectorKernel::HANNING) { |
---|
804 | mathutil::hanning(valuesOut, maskOut, itValues.vector(), itMask.vector()); |
---|
805 | itMask.vector() = maskOut; |
---|
806 | } else { |
---|
807 | mathutil::replaceMaskByZero(itValues.vector(), itMask.vector()); |
---|
808 | conv.linearConv(valuesOut, itValues.vector()); |
---|
809 | } |
---|
810 | // |
---|
811 | itValues.vector() = valuesOut; |
---|
812 | // |
---|
813 | itValues.next(); |
---|
814 | itMask.next(); |
---|
815 | } |
---|
816 | } else { |
---|
817 | |
---|
818 | // Set multi-dim Vector shape |
---|
819 | |
---|
820 | shapeOut(chanAxis) = valuesIn.shape()(chanAxis); |
---|
821 | |
---|
822 | // Stuff about with shapes so that we don't have conformance run-time errors |
---|
823 | |
---|
824 | Vector<Float> valuesIn2 = valuesIn(start,end).nonDegenerate(); |
---|
825 | Vector<Bool> maskIn2 = maskIn(start,end).nonDegenerate(); |
---|
826 | |
---|
827 | // Smooth |
---|
828 | |
---|
829 | if (kernelType==VectorKernel::HANNING) { |
---|
830 | mathutil::hanning(valuesOut, maskOut, valuesIn2, maskIn2); |
---|
831 | maskIn(start,end) = maskOut.reform(shapeOut); |
---|
832 | } else { |
---|
833 | mathutil::replaceMaskByZero(valuesIn2, maskIn2); |
---|
834 | conv.linearConv(valuesOut, valuesIn2); |
---|
835 | } |
---|
836 | // |
---|
837 | valuesIn(start,end) = valuesOut.reform(shapeOut); |
---|
838 | } |
---|
839 | |
---|
840 | // Create and put back |
---|
841 | |
---|
842 | SDContainer sc = in.getSDContainer(ri); |
---|
843 | putDataInSDC(sc, valuesIn, maskIn); |
---|
844 | // |
---|
845 | pTabOut->putSDContainer(sc); |
---|
846 | } |
---|
847 | // |
---|
848 | return pTabOut; |
---|
849 | } |
---|
850 | |
---|
851 | |
---|
852 | SDMemTable* SDMath::convertFlux (const SDMemTable& in, Float a, Float eta, Bool doAll) |
---|
853 | // |
---|
854 | // As it is, this function could be implemented with 'simpleOperate' |
---|
855 | // However, I anticipate that eventually we will look the conversion |
---|
856 | // values up in a Table and apply them in a frequency dependent way, |
---|
857 | // so I have implemented it fully here |
---|
858 | // |
---|
859 | { |
---|
860 | SDHeader sh = in.getSDHeader(); |
---|
861 | SDMemTable* pTabOut = new SDMemTable(in, True); |
---|
862 | |
---|
863 | // FInd out how to convert values into Jy and K (e.g. units might be mJy or mK) |
---|
864 | // Also automatically find out what we are converting to according to the |
---|
865 | // flux unit |
---|
866 | |
---|
867 | Unit fluxUnit(sh.fluxunit); |
---|
868 | Unit K(String("K")); |
---|
869 | Unit JY(String("Jy")); |
---|
870 | // |
---|
871 | Bool toKelvin = True; |
---|
872 | Double inFac = 1.0; |
---|
873 | if (fluxUnit==JY) { |
---|
874 | cerr << "Converting to K" << endl; |
---|
875 | // |
---|
876 | Quantum<Double> t(1.0,fluxUnit); |
---|
877 | Quantum<Double> t2 = t.get(JY); |
---|
878 | inFac = (t2 / t).getValue(); |
---|
879 | // |
---|
880 | toKelvin = True; |
---|
881 | sh.fluxunit = "K"; |
---|
882 | } else if (fluxUnit==K) { |
---|
883 | cerr << "Converting to Jy" << endl; |
---|
884 | // |
---|
885 | Quantum<Double> t(1.0,fluxUnit); |
---|
886 | Quantum<Double> t2 = t.get(K); |
---|
887 | inFac = (t2 / t).getValue(); |
---|
888 | // |
---|
889 | toKelvin = False; |
---|
890 | sh.fluxunit = "Jy"; |
---|
891 | } else { |
---|
892 | throw AipsError("Unrecognized brightness units in Table - must be consistent with Jy or K"); |
---|
893 | } |
---|
894 | pTabOut->putSDHeader(sh); |
---|
895 | |
---|
896 | // Compute conversion factor. 'a' and 'eta' are really frequency, time and |
---|
897 | // telescope dependent and should be looked// up in a table |
---|
898 | |
---|
899 | Float factor = 2.0 * inFac * 1.0e-7 * 1.0e26 * QC::k.getValue(Unit(String("erg/K"))) / a / eta; |
---|
900 | if (toKelvin) { |
---|
901 | factor = 1.0 / factor; |
---|
902 | } |
---|
903 | cerr << "Applying conversion factor = " << factor << endl; |
---|
904 | |
---|
905 | // For operations only on specified cursor location |
---|
906 | |
---|
907 | IPosition start, end; |
---|
908 | getCursorLocation(start, end, in); |
---|
909 | |
---|
910 | // Loop over rows and apply factor to spectra |
---|
911 | |
---|
912 | const uInt axis = asap::ChanAxis; |
---|
913 | for (uInt i=0; i < in.nRow(); ++i) { |
---|
914 | |
---|
915 | // Get data |
---|
916 | |
---|
917 | MaskedArray<Float> dataIn(in.rowAsMaskedArray(i)); |
---|
918 | Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference |
---|
919 | const Array<Bool>& maskIn = dataIn.getMask(); |
---|
920 | |
---|
921 | // Need to apply correct conversion factor (frequency and time dependent) |
---|
922 | // which should be sourced from a Table. For now we just apply the given |
---|
923 | // factor to everything |
---|
924 | |
---|
925 | if (doAll) { |
---|
926 | VectorIterator<Float> itValues(valuesIn, asap::ChanAxis); |
---|
927 | while (!itValues.pastEnd()) { |
---|
928 | itValues.vector() *= factor; // Writes back into dataIn |
---|
929 | // |
---|
930 | itValues.next(); |
---|
931 | } |
---|
932 | } else { |
---|
933 | Array<Float> valuesIn2 = valuesIn(start,end); |
---|
934 | valuesIn2 *= factor; |
---|
935 | valuesIn(start,end) = valuesIn2; |
---|
936 | } |
---|
937 | |
---|
938 | // Write out |
---|
939 | |
---|
940 | SDContainer sc = in.getSDContainer(i); |
---|
941 | putDataInSDC(sc, valuesIn, maskIn); |
---|
942 | // |
---|
943 | pTabOut->putSDContainer(sc); |
---|
944 | } |
---|
945 | return pTabOut; |
---|
946 | } |
---|
947 | |
---|
948 | |
---|
949 | |
---|
950 | // 'private' functions |
---|
951 | |
---|
952 | void SDMath::fillSDC(SDContainer& sc, |
---|
953 | const Array<Bool>& mask, |
---|
954 | const Array<Float>& data, |
---|
955 | const Array<Float>& tSys, |
---|
956 | Int scanID, Double timeStamp, |
---|
957 | Double interval, const String& sourceName, |
---|
958 | const Vector<uInt>& freqID) |
---|
959 | { |
---|
960 | // Data and mask |
---|
961 | |
---|
962 | putDataInSDC(sc, data, mask); |
---|
963 | |
---|
964 | // TSys |
---|
965 | |
---|
966 | sc.putTsys(tSys); |
---|
967 | |
---|
968 | // Time things |
---|
969 | |
---|
970 | sc.timestamp = timeStamp; |
---|
971 | sc.interval = interval; |
---|
972 | sc.scanid = scanID; |
---|
973 | // |
---|
974 | sc.sourcename = sourceName; |
---|
975 | sc.putFreqMap(freqID); |
---|
976 | } |
---|
977 | |
---|
978 | void SDMath::normalize(MaskedArray<Float>& sum, |
---|
979 | const Array<Float>& sumSq, |
---|
980 | const Array<Float>& nPts, |
---|
981 | WeightType wtType, Int axis, |
---|
982 | Int nAxesSub) |
---|
983 | { |
---|
984 | IPosition pos2(nAxesSub,0); |
---|
985 | // |
---|
986 | if (wtType==NONE) { |
---|
987 | |
---|
988 | // We just average by the number of points accumulated. |
---|
989 | // We need to make a MA out of nPts so that no divide by |
---|
990 | // zeros occur |
---|
991 | |
---|
992 | MaskedArray<Float> t(nPts, (nPts>Float(0.0))); |
---|
993 | sum /= t; |
---|
994 | } else if (wtType==VAR) { |
---|
995 | |
---|
996 | // Normalize each spectrum by sum(1/var) where the variance |
---|
997 | // is worked out for each spectrum |
---|
998 | |
---|
999 | Array<Float>& data = sum.getRWArray(); |
---|
1000 | VectorIterator<Float> itData(data, axis); |
---|
1001 | while (!itData.pastEnd()) { |
---|
1002 | pos2 = itData.pos().getFirst(nAxesSub); |
---|
1003 | itData.vector() /= sumSq(pos2); |
---|
1004 | itData.next(); |
---|
1005 | } |
---|
1006 | } else if (wtType==TSYS) { |
---|
1007 | } |
---|
1008 | } |
---|
1009 | |
---|
1010 | |
---|
1011 | void SDMath::accumulate(Double& timeSum, Double& intSum, Int& nAccum, |
---|
1012 | MaskedArray<Float>& sum, Array<Float>& sumSq, |
---|
1013 | Array<Float>& nPts, Array<Float>& tSysSum, |
---|
1014 | const Array<Float>& tSys, const Array<Float>& nInc, |
---|
1015 | const Vector<Bool>& mask, Double time, Double interval, |
---|
1016 | const Block<CountedPtr<SDMemTable> >& in, |
---|
1017 | uInt iTab, uInt iRow, uInt axis, |
---|
1018 | uInt nAxesSub, Bool useMask, |
---|
1019 | WeightType wtType) |
---|
1020 | { |
---|
1021 | |
---|
1022 | // Get data |
---|
1023 | |
---|
1024 | MaskedArray<Float> dataIn(in[iTab]->rowAsMaskedArray(iRow)); |
---|
1025 | Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference |
---|
1026 | const Array<Bool>& maskIn = dataIn.getMask(); // RO reference |
---|
1027 | // |
---|
1028 | if (wtType==NONE) { |
---|
1029 | const MaskedArray<Float> n(nInc,dataIn.getMask()); |
---|
1030 | nPts += n; // Only accumulates where mask==T |
---|
1031 | } else if (wtType==VAR) { |
---|
1032 | |
---|
1033 | // We are going to average the data, weighted by the noise for each pol, beam and IF. |
---|
1034 | // So therefore we need to iterate through by spectrum (axis 3) |
---|
1035 | |
---|
1036 | VectorIterator<Float> itData(valuesIn, axis); |
---|
1037 | ReadOnlyVectorIterator<Bool> itMask(maskIn, axis); |
---|
1038 | Float fac = 1.0; |
---|
1039 | IPosition pos(nAxesSub,0); |
---|
1040 | // |
---|
1041 | while (!itData.pastEnd()) { |
---|
1042 | |
---|
1043 | // Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor |
---|
1044 | |
---|
1045 | if (useMask) { |
---|
1046 | MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector()); |
---|
1047 | fac = 1.0/variance(tmp); |
---|
1048 | } else { |
---|
1049 | MaskedArray<Float> tmp(itData.vector(),itMask.vector()); |
---|
1050 | fac = 1.0/variance(tmp); |
---|
1051 | } |
---|
1052 | |
---|
1053 | // Scale data |
---|
1054 | |
---|
1055 | itData.vector() *= fac; // Writes back into 'dataIn' |
---|
1056 | // |
---|
1057 | // Accumulate variance per if/pol/beam averaged over spectrum |
---|
1058 | // This method to get pos2 from itData.pos() is only valid |
---|
1059 | // because the spectral axis is the last one (so we can just |
---|
1060 | // copy the first nAXesSub positions out) |
---|
1061 | |
---|
1062 | pos = itData.pos().getFirst(nAxesSub); |
---|
1063 | sumSq(pos) += fac; |
---|
1064 | // |
---|
1065 | itData.next(); |
---|
1066 | itMask.next(); |
---|
1067 | } |
---|
1068 | } else if (wtType==TSYS) { |
---|
1069 | } |
---|
1070 | |
---|
1071 | // Accumulate sum of (possibly scaled) data |
---|
1072 | |
---|
1073 | sum += dataIn; |
---|
1074 | |
---|
1075 | // Accumulate Tsys, time, and interval |
---|
1076 | |
---|
1077 | tSysSum += tSys; |
---|
1078 | timeSum += time; |
---|
1079 | intSum += interval; |
---|
1080 | nAccum += 1; |
---|
1081 | } |
---|
1082 | |
---|
1083 | |
---|
1084 | |
---|
1085 | |
---|
1086 | void SDMath::getCursorLocation(IPosition& start, IPosition& end, |
---|
1087 | const SDMemTable& in) |
---|
1088 | { |
---|
1089 | const uInt nDim = 4; |
---|
1090 | const uInt i = in.getBeam(); |
---|
1091 | const uInt j = in.getIF(); |
---|
1092 | const uInt k = in.getPol(); |
---|
1093 | const uInt n = in.nChan(); |
---|
1094 | // |
---|
1095 | start.resize(nDim); |
---|
1096 | start(0) = i; |
---|
1097 | start(1) = j; |
---|
1098 | start(2) = k; |
---|
1099 | start(3) = 0; |
---|
1100 | // |
---|
1101 | end.resize(nDim); |
---|
1102 | end(0) = i; |
---|
1103 | end(1) = j; |
---|
1104 | end(2) = k; |
---|
1105 | end(3) = n-1; |
---|
1106 | } |
---|
1107 | |
---|
1108 | |
---|
1109 | void SDMath::convertWeightString(WeightType& wtType, const std::string& weightStr) |
---|
1110 | { |
---|
1111 | String tStr(weightStr); |
---|
1112 | tStr.upcase(); |
---|
1113 | if (tStr.contains(String("NONE"))) { |
---|
1114 | wtType = NONE; |
---|
1115 | } else if (tStr.contains(String("VAR"))) { |
---|
1116 | wtType = VAR; |
---|
1117 | } else if (tStr.contains(String("TSYS"))) { |
---|
1118 | wtType = TSYS; |
---|
1119 | throw(AipsError("T_sys weighting not yet implemented")); |
---|
1120 | } else { |
---|
1121 | throw(AipsError("Unrecognized weighting type")); |
---|
1122 | } |
---|
1123 | } |
---|
1124 | |
---|
1125 | void SDMath::putDataInSDC(SDContainer& sc, const Array<Float>& data, |
---|
1126 | const Array<Bool>& mask) |
---|
1127 | { |
---|
1128 | sc.putSpectrum(data); |
---|
1129 | // |
---|
1130 | Array<uChar> outflags(data.shape()); |
---|
1131 | convertArray(outflags,!mask); |
---|
1132 | sc.putFlags(outflags); |
---|
1133 | } |
---|