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 |
|
---|
460 | // Access desired piece of data
|
---|
461 |
|
---|
462 | Array<Float> v((arr(start,end)).nonDegenerate());
|
---|
463 | Array<Bool> m((barr(start,end)).nonDegenerate());
|
---|
464 |
|
---|
465 | // Apply OTF mask
|
---|
466 |
|
---|
467 | MaskedArray<Float> tmp;
|
---|
468 | if (m.nelements()==nEl) {
|
---|
469 | tmp.setData(v,m&&msk);
|
---|
470 | } else {
|
---|
471 | tmp.setData(v,m);
|
---|
472 | }
|
---|
473 |
|
---|
474 | // Get statistic
|
---|
475 |
|
---|
476 | result[ii] = mathutil::statistics(which, tmp);
|
---|
477 | }
|
---|
478 | //
|
---|
479 | return result;
|
---|
480 | }
|
---|
481 |
|
---|
482 |
|
---|
483 | SDMemTable* SDMath::bin(const SDMemTable& in, Int width)
|
---|
484 | {
|
---|
485 | SDHeader sh = in.getSDHeader();
|
---|
486 | SDMemTable* pTabOut = new SDMemTable(in, True);
|
---|
487 |
|
---|
488 | // Bin up SpectralCoordinates
|
---|
489 |
|
---|
490 | IPosition factors(1);
|
---|
491 | factors(0) = width;
|
---|
492 | for (uInt j=0; j<in.nCoordinates(); ++j) {
|
---|
493 | CoordinateSystem cSys;
|
---|
494 | cSys.addCoordinate(in.getCoordinate(j));
|
---|
495 | CoordinateSystem cSysBin =
|
---|
496 | CoordinateUtil::makeBinnedCoordinateSystem(factors, cSys, False);
|
---|
497 | //
|
---|
498 | SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0);
|
---|
499 | pTabOut->setCoordinate(sCBin, j);
|
---|
500 | }
|
---|
501 |
|
---|
502 | // Use RebinLattice to find shape
|
---|
503 |
|
---|
504 | IPosition shapeIn(1,sh.nchan);
|
---|
505 | IPosition shapeOut = RebinLattice<Float>::rebinShape(shapeIn, factors);
|
---|
506 | sh.nchan = shapeOut(0);
|
---|
507 | pTabOut->putSDHeader(sh);
|
---|
508 |
|
---|
509 |
|
---|
510 | // Loop over rows and bin along channel axis
|
---|
511 |
|
---|
512 | for (uInt i=0; i < in.nRow(); ++i) {
|
---|
513 | SDContainer sc = in.getSDContainer(i);
|
---|
514 | //
|
---|
515 | Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape
|
---|
516 |
|
---|
517 | // Bin up spectrum
|
---|
518 |
|
---|
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 | }
|
---|