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/Exceptions.h> |
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45 | |
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46 | #include <tables/Tables/Table.h> |
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47 | #include <tables/Tables/ScalarColumn.h> |
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48 | #include <tables/Tables/ArrayColumn.h> |
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49 | |
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50 | #include <lattices/Lattices/LatticeUtilities.h> |
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51 | #include <lattices/Lattices/RebinLattice.h> |
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52 | #include <coordinates/Coordinates/SpectralCoordinate.h> |
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53 | #include <coordinates/Coordinates/CoordinateSystem.h> |
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54 | #include <coordinates/Coordinates/CoordinateUtil.h> |
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55 | |
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56 | #include "MathUtils.h" |
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57 | #include "SDContainer.h" |
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58 | #include "SDMemTable.h" |
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59 | |
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60 | #include "SDMath.h" |
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61 | |
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62 | using namespace casa; |
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63 | using namespace asap; |
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64 | |
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65 | CountedPtr<SDMemTable> SDMath::average (const Block<CountedPtr<SDMemTable> >& in, |
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66 | const Vector<Bool>& mask, bool scanAv, |
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67 | const std::string& weightStr) |
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68 | // |
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69 | // Weighted averaging of spectra from one or more Tables. |
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70 | // |
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71 | { |
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72 | weightType wtType = NONE; |
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73 | String tStr(weightStr); |
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74 | tStr.upcase(); |
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75 | if (tStr.contains(String("NONE"))) { |
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76 | wtType = NONE; |
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77 | } else if (tStr.contains(String("VAR"))) { |
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78 | wtType = VAR; |
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79 | } else if (tStr.contains(String("TSYS"))) { |
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80 | wtType = TSYS; |
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81 | throw (AipsError("T_sys weighting not yet implemented")); |
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82 | } else { |
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83 | throw (AipsError("Unrecognized weighting type")); |
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84 | } |
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85 | |
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86 | // Create output Table by cloning from the first table |
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87 | |
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88 | SDMemTable* pTabOut = new SDMemTable(*in[0],True); |
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89 | |
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90 | // Setup |
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91 | |
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92 | const uInt axis = 3; // Spectral axis |
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93 | IPosition shp = in[0]->rowAsMaskedArray(0).shape(); // Must not change |
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94 | Array<Float> arr(shp); |
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95 | Array<Bool> barr(shp); |
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96 | const Bool useMask = (mask.nelements() == shp(axis)); |
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97 | |
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98 | // Columns from Tables |
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99 | |
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100 | ROArrayColumn<Float> tSysCol; |
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101 | ROScalarColumn<Double> mjdCol; |
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102 | ROScalarColumn<String> srcNameCol; |
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103 | ROScalarColumn<Double> intCol; |
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104 | ROArrayColumn<uInt> fqIDCol; |
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105 | |
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106 | // Create accumulation MaskedArray. We accumulate for each channel,if,pol,beam |
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107 | // Note that the mask of the accumulation array will ALWAYS remain ALL True. |
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108 | // The MA is only used so that when data which is masked Bad is added to it, |
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109 | // that data does not contribute. |
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110 | |
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111 | Array<Float> zero(shp); |
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112 | zero=0.0; |
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113 | Array<Bool> good(shp); |
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114 | good = True; |
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115 | MaskedArray<Float> sum(zero,good); |
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116 | |
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117 | // Counter arrays |
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118 | |
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119 | Array<Float> nPts(shp); // Number of points |
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120 | nPts = 0.0; |
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121 | Array<Float> nInc(shp); // Increment |
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122 | nInc = 1.0; |
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123 | |
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124 | // Create accumulation Array for variance. We accumulate for |
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125 | // each if,pol,beam, but average over channel. So we need |
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126 | // a shape with one less axis dropping channels. |
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127 | |
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128 | const uInt nAxesSub = shp.nelements() - 1; |
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129 | IPosition shp2(nAxesSub); |
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130 | for (uInt i=0,j=0; i<(nAxesSub+1); i++) { |
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131 | if (i!=axis) { |
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132 | shp2(j) = shp(i); |
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133 | j++; |
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134 | } |
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135 | } |
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136 | Array<Float> sumSq(shp2); |
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137 | sumSq = 0.0; |
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138 | IPosition pos2(nAxesSub,0); // For indexing |
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139 | |
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140 | // Time-related accumulators |
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141 | |
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142 | Double time; |
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143 | Double timeSum = 0.0; |
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144 | Double intSum = 0.0; |
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145 | Double interval = 0.0; |
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146 | |
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147 | // To get the right shape for the Tsys accumulator we need to |
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148 | // access a column from the first table. The shape of this |
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149 | // array must not change |
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150 | |
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151 | Array<Float> tSysSum; |
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152 | { |
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153 | const Table& tabIn = in[0]->table(); |
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154 | tSysCol.attach(tabIn,"TSYS"); |
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155 | tSysSum.resize(tSysCol.shape(0)); |
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156 | } |
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157 | tSysSum =0.0; |
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158 | Array<Float> tSys; |
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159 | |
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160 | // Scan and row tracking |
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161 | |
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162 | Int oldScanID = 0; |
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163 | Int outScanID = 0; |
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164 | Int scanID = 0; |
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165 | Int rowStart = 0; |
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166 | Int nAccum = 0; |
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167 | Int tableStart = 0; |
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168 | |
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169 | // Source and FreqID |
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170 | |
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171 | String sourceName, oldSourceName, sourceNameStart; |
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172 | Vector<uInt> freqID, freqIDStart, oldFreqID; |
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173 | |
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174 | // Loop over tables |
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175 | |
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176 | Float fac = 1.0; |
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177 | const uInt nTables = in.nelements(); |
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178 | for (uInt iTab=0; iTab<nTables; iTab++) { |
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179 | |
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180 | // Attach columns to Table |
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181 | |
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182 | const Table& tabIn = in[iTab]->table(); |
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183 | tSysCol.attach(tabIn, "TSYS"); |
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184 | mjdCol.attach(tabIn, "TIME"); |
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185 | srcNameCol.attach(tabIn, "SRCNAME"); |
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186 | intCol.attach(tabIn, "INTERVAL"); |
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187 | fqIDCol.attach(tabIn, "FREQID"); |
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188 | |
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189 | // Loop over rows in Table |
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190 | |
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191 | const uInt nRows = in[iTab]->nRow(); |
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192 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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193 | |
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194 | // Check conformance |
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195 | |
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196 | IPosition shp2 = in[iTab]->rowAsMaskedArray(iRow).shape(); |
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197 | if (!shp.isEqual(shp2)) { |
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198 | throw (AipsError("Shapes for all rows must be the same")); |
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199 | } |
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200 | |
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201 | // If we are not doing scan averages, make checks for source and |
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202 | // frequency setup and warn if averaging across them |
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203 | |
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204 | // Get copy of Scan Container for this row |
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205 | |
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206 | SDContainer sc = in[iTab]->getSDContainer(iRow); |
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207 | scanID = sc.scanid; |
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208 | |
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209 | // Get quantities from columns |
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210 | |
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211 | srcNameCol.getScalar(iRow, sourceName); |
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212 | mjdCol.get(iRow, time); |
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213 | tSysCol.get(iRow, tSys); |
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214 | intCol.get(iRow, interval); |
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215 | fqIDCol.get(iRow, freqID); |
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216 | |
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217 | // Initialize first source and freqID |
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218 | |
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219 | if (iRow==0 && iTab==0) { |
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220 | sourceNameStart = sourceName; |
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221 | freqIDStart = freqID; |
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222 | } |
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223 | |
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224 | // If we are doing scan averages, see if we are at the end of an |
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225 | // accumulation period (scan). We must check soutce names too, |
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226 | // since we might have two tables with one scan each but different |
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227 | // source names; we shouldn't average different sources together |
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228 | |
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229 | if (scanAv && ( (scanID != oldScanID) || |
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230 | (iRow==0 && iTab>0 && sourceName!=oldSourceName))) { |
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231 | |
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232 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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233 | |
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234 | normalize (sum, sumSq, nPts, wtType, axis, nAxesSub); |
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235 | |
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236 | // Fill scan container. The source and freqID come from the |
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237 | // first row of the first table that went into this average ( |
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238 | // should be the same for all rows in the scan average) |
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239 | |
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240 | Float nR(nAccum); |
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241 | fillSDC (sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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242 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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243 | |
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244 | // Write container out to Table |
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245 | |
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246 | pTabOut->putSDContainer(sc); |
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247 | |
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248 | // Reset accumulators |
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249 | |
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250 | sum = 0.0; |
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251 | sumSq = 0.0; |
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252 | nAccum = 0; |
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253 | // |
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254 | tSysSum =0.0; |
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255 | timeSum = 0.0; |
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256 | intSum = 0.0; |
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257 | |
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258 | // Increment |
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259 | |
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260 | rowStart = iRow; // First row for next accumulation |
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261 | tableStart = iTab; // First table for next accumulation |
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262 | sourceNameStart = sourceName; // First source name for next accumulation |
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263 | freqIDStart = freqID; // First FreqID for next accumulation |
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264 | // |
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265 | oldScanID = scanID; |
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266 | outScanID += 1; // Scan ID for next accumulation period |
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267 | } |
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268 | |
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269 | // Accumulate |
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270 | |
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271 | accumulate (timeSum, intSum, nAccum, sum, sumSq, nPts, tSysSum, |
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272 | tSys, nInc, mask, time, interval, in, iTab, iRow, axis, |
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273 | nAxesSub, useMask, wtType); |
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274 | // |
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275 | oldSourceName = sourceName; |
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276 | oldFreqID = freqID; |
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277 | } |
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278 | } |
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279 | |
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280 | // OK at this point we have accumulation data which is either |
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281 | // - accumulated from all tables into one row |
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282 | // or |
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283 | // - accumulated from the last scan average |
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284 | // |
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285 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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286 | |
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287 | normalize (sum, sumSq, nPts, wtType, axis, nAxesSub); |
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288 | |
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289 | // Create and fill container. The container we clone will be from |
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290 | // the last Table and the first row that went into the current |
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291 | // accumulation. It probably doesn't matter that much really... |
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292 | |
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293 | Float nR(nAccum); |
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294 | SDContainer sc = in[tableStart]->getSDContainer(rowStart); |
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295 | fillSDC (sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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296 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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297 | // |
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298 | pTabOut->putSDContainer(sc); |
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299 | /* |
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300 | cout << endl; |
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301 | cout << "Last accumulation for output scan ID " << outScanID << endl; |
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302 | cout << " The first row in this accumulation is " << rowStart << endl; |
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303 | cout << " The number of rows accumulated is " << nAccum << endl; |
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304 | cout << " The first table in this accumulation is " << tableStart << endl; |
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305 | cout << " The first source in this accumulation is " << sourceNameStart << endl; |
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306 | cout << " The first freqID in this accumulation is " << freqIDStart << endl; |
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307 | cout << " Average time stamp = " << timeSum/nR << endl; |
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308 | cout << " Integrated time = " << intSum << endl; |
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309 | */ |
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310 | return CountedPtr<SDMemTable>(pTabOut); |
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311 | } |
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312 | |
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313 | |
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314 | |
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315 | CountedPtr<SDMemTable> |
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316 | SDMath::quotient(const CountedPtr<SDMemTable>& on, |
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317 | const CountedPtr<SDMemTable>& off) |
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318 | // |
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319 | // Compute quotient spectrum |
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320 | // |
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321 | { |
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322 | const uInt nRows = on->nRow(); |
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323 | if (off->nRow() != nRows) { |
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324 | throw (AipsError("Input Scan Tables must have the same number of rows")); |
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325 | } |
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326 | |
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327 | // Input Tables and columns |
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328 | |
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329 | Table ton = on->table(); |
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330 | Table toff = off->table(); |
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331 | ROArrayColumn<Float> tsys(toff, "TSYS"); |
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332 | ROScalarColumn<Double> mjd(ton, "TIME"); |
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333 | ROScalarColumn<Double> integr(ton, "INTERVAL"); |
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334 | ROScalarColumn<String> srcn(ton, "SRCNAME"); |
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335 | ROArrayColumn<uInt> freqidc(ton, "FREQID"); |
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336 | |
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337 | // Output Table cloned from input |
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338 | |
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339 | SDMemTable* sdmt = new SDMemTable(*on, True); |
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340 | |
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341 | // Loop over rows |
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342 | |
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343 | for (uInt i=0; i<nRows; i++) { |
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344 | MaskedArray<Float> mon(on->rowAsMaskedArray(i)); |
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345 | MaskedArray<Float> moff(off->rowAsMaskedArray(i)); |
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346 | IPosition ipon = mon.shape(); |
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347 | IPosition ipoff = moff.shape(); |
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348 | // |
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349 | Array<Float> tsarr; |
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350 | tsys.get(i, tsarr); |
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351 | if (ipon != ipoff && ipon != tsarr.shape()) { |
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352 | throw(AipsError("on/off not conformant")); |
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353 | } |
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354 | |
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355 | // Compute quotient |
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356 | |
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357 | MaskedArray<Float> tmp = (mon-moff); |
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358 | Array<Float> out(tmp.getArray()); |
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359 | out /= moff; |
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360 | out *= tsarr; |
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361 | Array<Bool> outflagsb = !(mon.getMask() && moff.getMask()); |
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362 | Array<uChar> outflags(outflagsb.shape()); |
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363 | convertArray(outflags,outflagsb); |
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364 | |
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365 | // Fill container for this row |
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366 | |
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367 | SDContainer sc = on->getSDContainer(); |
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368 | sc.putTsys(tsarr); |
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369 | sc.scanid = 0; |
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370 | sc.putSpectrum(out); |
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371 | sc.putFlags(outflags); |
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372 | |
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373 | // Put new row in output Table |
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374 | |
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375 | sdmt->putSDContainer(sc); |
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376 | } |
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377 | // |
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378 | return CountedPtr<SDMemTable>(sdmt); |
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379 | } |
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380 | |
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381 | void SDMath::multiplyInSitu(SDMemTable* pIn, Float factor, Bool doAll) |
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382 | { |
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383 | const uInt what = 0; |
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384 | SDMemTable* pOut = localOperate (*pIn, factor, doAll, what); |
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385 | *pIn = *pOut; |
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386 | delete pOut; |
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387 | } |
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388 | |
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389 | |
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390 | CountedPtr<SDMemTable> |
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391 | SDMath::multiply(const CountedPtr<SDMemTable>& in, Float factor, Bool doAll) |
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392 | { |
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393 | const uInt what = 0; |
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394 | return CountedPtr<SDMemTable>(localOperate (*in, factor, doAll, what)); |
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395 | } |
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396 | |
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397 | |
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398 | void SDMath::addInSitu (SDMemTable* pIn, Float offset, Bool doAll) |
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399 | { |
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400 | const uInt what = 1; |
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401 | SDMemTable* pOut = localOperate (*pIn, offset, doAll, what); |
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402 | *pIn = *pOut; |
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403 | delete pOut; |
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404 | } |
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405 | |
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406 | |
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407 | CountedPtr<SDMemTable> |
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408 | SDMath::add(const CountedPtr<SDMemTable>& in, Float offset, Bool doAll) |
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409 | { |
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410 | const uInt what = 1; |
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411 | return CountedPtr<SDMemTable>(localOperate(*in, offset, doAll, what)); |
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412 | } |
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413 | |
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414 | |
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415 | CountedPtr<SDMemTable> |
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416 | SDMath::hanning(const CountedPtr<SDMemTable>& in) |
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417 | // |
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418 | // Hanning smooth each row |
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419 | // Should Tsys be smoothed ? |
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420 | // |
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421 | { |
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422 | SDMemTable* sdmt = new SDMemTable(*in,True); |
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423 | |
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424 | // Loop over rows in Table |
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425 | |
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426 | for (uInt ri=0; ri < in->nRow(); ++ri) { |
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427 | |
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428 | // Get data |
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429 | |
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430 | const MaskedArray<Float>& marr(in->rowAsMaskedArray(ri)); |
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431 | Array<Float> arr = marr.getArray(); |
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432 | Array<Bool> barr = marr.getMask(); |
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433 | |
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434 | // Smooth along the channels axis |
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435 | |
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436 | uInt axis = 3; |
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437 | VectorIterator<Float> itData(arr, axis); |
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438 | VectorIterator<Bool> itMask(barr, axis); |
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439 | Vector<Float> outv; |
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440 | Vector<Bool> outm; |
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441 | while (!itData.pastEnd()) { |
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442 | mathutil::hanning(outv, outm, itData.vector(), itMask.vector()); |
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443 | itData.vector() = outv; |
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444 | itMask.vector() = outm; |
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445 | // |
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446 | itData.next(); |
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447 | itMask.next(); |
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448 | } |
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449 | |
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450 | // Create and put back |
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451 | |
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452 | Array<uChar> outflags(barr.shape()); |
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453 | convertArray(outflags,!barr); |
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454 | SDContainer sc = in->getSDContainer(ri); |
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455 | sc.putSpectrum(arr); |
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456 | sc.putFlags(outflags); |
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457 | sdmt->putSDContainer(sc); |
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458 | } |
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459 | return CountedPtr<SDMemTable>(sdmt); |
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460 | } |
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461 | |
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462 | |
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463 | |
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464 | |
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465 | CountedPtr<SDMemTable> |
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466 | SDMath::averagePol(const CountedPtr<SDMemTable>& in, |
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467 | const Vector<Bool>& mask) |
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468 | { |
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469 | const uInt nRows = in->nRow(); |
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470 | const uInt axis = 3; // Spectrum |
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471 | const IPosition axes(2, 2, 3); // pol-channel plane |
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472 | |
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473 | // Create output Table |
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474 | |
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475 | SDMemTable* sdmt = new SDMemTable(*in, True); |
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476 | |
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477 | // Loop over rows |
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478 | |
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479 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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480 | |
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481 | // Get data for this row |
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482 | |
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483 | MaskedArray<Float> marr(in->rowAsMaskedArray(iRow)); |
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484 | Array<Float>& arr = marr.getRWArray(); |
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485 | const Array<Bool>& barr = marr.getMask(); |
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486 | // |
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487 | IPosition shp = marr.shape(); |
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488 | const Bool useMask = (mask.nelements() == shp(axis)); |
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489 | const uInt nChan = shp(axis); |
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490 | |
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491 | // Make iterators to iterate by pol-channel planes |
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492 | |
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493 | ArrayIterator<Float> itDataPlane(arr, axes); |
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494 | ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes); |
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495 | |
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496 | // Accumulations |
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497 | |
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498 | Float fac = 0.0; |
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499 | Vector<Float> vecSum(nChan,0.0); |
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500 | |
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501 | // Iterate by plane |
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502 | |
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503 | while (!itDataPlane.pastEnd()) { |
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504 | |
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505 | // Iterate through pol-channel plane by spectrum |
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506 | |
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507 | Vector<Float> t1(nChan); t1 = 0.0; |
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508 | Vector<Bool> t2(nChan); t2 = True; |
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509 | MaskedArray<Float> vecSum(t1,t2); |
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510 | Float varSum = 0.0; |
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511 | { |
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512 | ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1); |
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513 | ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1); |
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514 | while (!itDataVec.pastEnd()) { |
---|
515 | |
---|
516 | // Create MA of data & mask (optionally including OTF mask) and get variance |
---|
517 | |
---|
518 | if (useMask) { |
---|
519 | const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector()); |
---|
520 | fac = 1.0 / variance(spec); |
---|
521 | } else { |
---|
522 | const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector()); |
---|
523 | fac = 1.0 / variance(spec); |
---|
524 | } |
---|
525 | |
---|
526 | // Normalize spectrum (without OTF mask) and accumulate |
---|
527 | |
---|
528 | const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector()); |
---|
529 | vecSum += spec; |
---|
530 | varSum += fac; |
---|
531 | |
---|
532 | // Next |
---|
533 | |
---|
534 | itDataVec.next(); |
---|
535 | itMaskVec.next(); |
---|
536 | } |
---|
537 | } |
---|
538 | |
---|
539 | // Normalize summed spectrum |
---|
540 | |
---|
541 | vecSum /= varSum; |
---|
542 | |
---|
543 | // We have formed the weighted averaged spectrum from all polarizations |
---|
544 | // for this beam and IF. Now replicate the spectrum to all polarizations |
---|
545 | |
---|
546 | { |
---|
547 | VectorIterator<Float> itDataVec(itDataPlane.array(), 1); // Writes back into 'arr' |
---|
548 | const Vector<Float>& vecSumData = vecSum.getArray(); // It *is* a Vector |
---|
549 | // |
---|
550 | while (!itDataVec.pastEnd()) { |
---|
551 | itDataVec.vector() = vecSumData; |
---|
552 | itDataVec.next(); |
---|
553 | } |
---|
554 | } |
---|
555 | |
---|
556 | // Step to next beam/IF combination |
---|
557 | |
---|
558 | itDataPlane.next(); |
---|
559 | itMaskPlane.next(); |
---|
560 | } |
---|
561 | |
---|
562 | // Generate output container and write it to output table |
---|
563 | |
---|
564 | SDContainer sc = in->getSDContainer(); |
---|
565 | Array<uChar> outflags(barr.shape()); |
---|
566 | convertArray(outflags,!barr); |
---|
567 | sc.putSpectrum(arr); |
---|
568 | sc.putFlags(outflags); |
---|
569 | sdmt->putSDContainer(sc); |
---|
570 | } |
---|
571 | // |
---|
572 | return CountedPtr<SDMemTable>(sdmt); |
---|
573 | } |
---|
574 | |
---|
575 | |
---|
576 | CountedPtr<SDMemTable> SDMath::bin(const CountedPtr<SDMemTable>& in, |
---|
577 | Int width) |
---|
578 | { |
---|
579 | SDHeader sh = in->getSDHeader(); |
---|
580 | SDMemTable* sdmt = new SDMemTable(*in,True); |
---|
581 | |
---|
582 | // Bin up SpectralCoordinates |
---|
583 | |
---|
584 | IPosition factors(1); |
---|
585 | factors(0) = width; |
---|
586 | for (uInt j=0; j<in->nCoordinates(); ++j) { |
---|
587 | CoordinateSystem cSys; |
---|
588 | cSys.addCoordinate(in->getCoordinate(j)); |
---|
589 | CoordinateSystem cSysBin = |
---|
590 | CoordinateUtil::makeBinnedCoordinateSystem (factors, cSys, False); |
---|
591 | // |
---|
592 | SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0); |
---|
593 | sdmt->setCoordinate(sCBin, j); |
---|
594 | } |
---|
595 | |
---|
596 | // Use RebinLattice to find shape |
---|
597 | |
---|
598 | IPosition shapeIn(1,sh.nchan); |
---|
599 | IPosition shapeOut = RebinLattice<Float>::rebinShape (shapeIn, factors); |
---|
600 | sh.nchan = shapeOut(0); |
---|
601 | sdmt->putSDHeader(sh); |
---|
602 | |
---|
603 | |
---|
604 | // Loop over rows and bin along channel axis |
---|
605 | |
---|
606 | const uInt axis = 3; |
---|
607 | for (uInt i=0; i < in->nRow(); ++i) { |
---|
608 | SDContainer sc = in->getSDContainer(i); |
---|
609 | // |
---|
610 | Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape |
---|
611 | |
---|
612 | // Bin up spectrum |
---|
613 | |
---|
614 | MaskedArray<Float> marr(in->rowAsMaskedArray(i)); |
---|
615 | MaskedArray<Float> marrout; |
---|
616 | LatticeUtilities::bin(marrout, marr, axis, width); |
---|
617 | |
---|
618 | // Put back the binned data and flags |
---|
619 | |
---|
620 | IPosition ip2 = marrout.shape(); |
---|
621 | sc.resize(ip2); |
---|
622 | sc.putSpectrum(marrout.getArray()); |
---|
623 | // |
---|
624 | Array<uChar> outflags(ip2); |
---|
625 | convertArray(outflags,!(marrout.getMask())); |
---|
626 | sc.putFlags(outflags); |
---|
627 | |
---|
628 | // Bin up Tsys. |
---|
629 | |
---|
630 | Array<Bool> allGood(tSys.shape(),True); |
---|
631 | MaskedArray<Float> tSysIn(tSys, allGood, True); |
---|
632 | // |
---|
633 | MaskedArray<Float> tSysOut; |
---|
634 | LatticeUtilities::bin(tSysOut, tSysIn, axis, width); |
---|
635 | sc.putTsys(tSysOut.getArray()); |
---|
636 | sdmt->putSDContainer(sc); |
---|
637 | } |
---|
638 | return CountedPtr<SDMemTable>(sdmt); |
---|
639 | } |
---|
640 | |
---|
641 | |
---|
642 | |
---|
643 | std::vector<float> SDMath::statistic (const CountedPtr<SDMemTable>& in, |
---|
644 | const std::vector<bool>& mask, |
---|
645 | const std::string& which) |
---|
646 | // |
---|
647 | // Perhaps iteration over pol/beam/if should be in here |
---|
648 | // and inside the nrow iteration ? |
---|
649 | // |
---|
650 | { |
---|
651 | const uInt nRow = in->nRow(); |
---|
652 | std::vector<float> result(nRow); |
---|
653 | Vector<Bool> msk(mask); |
---|
654 | |
---|
655 | // Specify cursor location |
---|
656 | |
---|
657 | IPosition start, end; |
---|
658 | getCursorLocation (start, end, *in); |
---|
659 | |
---|
660 | // Loop over rows |
---|
661 | |
---|
662 | const uInt nEl = msk.nelements(); |
---|
663 | for (uInt ii=0; ii < in->nRow(); ++ii) { |
---|
664 | |
---|
665 | // Get row and deconstruct |
---|
666 | |
---|
667 | MaskedArray<Float> marr(in->rowAsMaskedArray(ii)); |
---|
668 | Array<Float> arr = marr.getArray(); |
---|
669 | Array<Bool> barr = marr.getMask(); |
---|
670 | |
---|
671 | // Access desired piece of data |
---|
672 | |
---|
673 | Array<Float> v((arr(start,end)).nonDegenerate()); |
---|
674 | Array<Bool> m((barr(start,end)).nonDegenerate()); |
---|
675 | |
---|
676 | // Apply OTF mask |
---|
677 | |
---|
678 | MaskedArray<Float> tmp; |
---|
679 | if (m.nelements()==nEl) { |
---|
680 | tmp.setData(v,m&&msk); |
---|
681 | } else { |
---|
682 | tmp.setData(v,m); |
---|
683 | } |
---|
684 | |
---|
685 | // Get statistic |
---|
686 | |
---|
687 | result[ii] = mathutil::statistics(which, tmp); |
---|
688 | } |
---|
689 | // |
---|
690 | return result; |
---|
691 | } |
---|
692 | |
---|
693 | |
---|
694 | |
---|
695 | // 'private' functions |
---|
696 | |
---|
697 | void SDMath::fillSDC (SDContainer& sc, |
---|
698 | const Array<Bool>& mask, |
---|
699 | const Array<Float>& data, |
---|
700 | const Array<Float>& tSys, |
---|
701 | Int scanID, Double timeStamp, |
---|
702 | Double interval, const String& sourceName, |
---|
703 | const Vector<uInt>& freqID) |
---|
704 | { |
---|
705 | sc.putSpectrum(data); |
---|
706 | // |
---|
707 | Array<uChar> outflags(mask.shape()); |
---|
708 | convertArray(outflags,!mask); |
---|
709 | sc.putFlags(outflags); |
---|
710 | // |
---|
711 | sc.putTsys(tSys); |
---|
712 | |
---|
713 | // Time things |
---|
714 | |
---|
715 | sc.timestamp = timeStamp; |
---|
716 | sc.interval = interval; |
---|
717 | sc.scanid = scanID; |
---|
718 | // |
---|
719 | sc.sourcename = sourceName; |
---|
720 | sc.putFreqMap(freqID); |
---|
721 | } |
---|
722 | |
---|
723 | void SDMath::normalize (MaskedArray<Float>& sum, |
---|
724 | const Array<Float>& sumSq, |
---|
725 | const Array<Float>& nPts, |
---|
726 | weightType wtType, Int axis, |
---|
727 | Int nAxesSub) |
---|
728 | { |
---|
729 | IPosition pos2(nAxesSub,0); |
---|
730 | // |
---|
731 | if (wtType==NONE) { |
---|
732 | |
---|
733 | // We just average by the number of points accumulated. |
---|
734 | // We need to make a MA out of nPts so that no divide by |
---|
735 | // zeros occur |
---|
736 | |
---|
737 | MaskedArray<Float> t(nPts, (nPts>Float(0.0))); |
---|
738 | sum /= t; |
---|
739 | } else if (wtType==VAR) { |
---|
740 | |
---|
741 | // Normalize each spectrum by sum(1/var) where the variance |
---|
742 | // is worked out for each spectrum |
---|
743 | |
---|
744 | Array<Float>& data = sum.getRWArray(); |
---|
745 | VectorIterator<Float> itData(data, axis); |
---|
746 | while (!itData.pastEnd()) { |
---|
747 | pos2 = itData.pos().getFirst(nAxesSub); |
---|
748 | itData.vector() /= sumSq(pos2); |
---|
749 | itData.next(); |
---|
750 | } |
---|
751 | } else if (wtType==TSYS) { |
---|
752 | } |
---|
753 | } |
---|
754 | |
---|
755 | |
---|
756 | void SDMath::accumulate (Double& timeSum, Double& intSum, Int& nAccum, |
---|
757 | MaskedArray<Float>& sum, Array<Float>& sumSq, |
---|
758 | Array<Float>& nPts, Array<Float>& tSysSum, |
---|
759 | const Array<Float>& tSys, const Array<Float>& nInc, |
---|
760 | const Vector<Bool>& mask, Double time, Double interval, |
---|
761 | const Block<CountedPtr<SDMemTable> >& in, |
---|
762 | uInt iTab, uInt iRow, uInt axis, |
---|
763 | uInt nAxesSub, Bool useMask, |
---|
764 | weightType wtType) |
---|
765 | { |
---|
766 | |
---|
767 | // Get data |
---|
768 | |
---|
769 | MaskedArray<Float> dataIn(in[iTab]->rowAsMaskedArray(iRow)); |
---|
770 | Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference |
---|
771 | const Array<Bool>& maskIn = dataIn.getMask(); // RO reference |
---|
772 | // |
---|
773 | if (wtType==NONE) { |
---|
774 | const MaskedArray<Float> n(nInc,dataIn.getMask()); |
---|
775 | nPts += n; // Only accumulates where mask==T |
---|
776 | } else if (wtType==VAR) { |
---|
777 | |
---|
778 | // We are going to average the data, weighted by the noise for each pol, beam and IF. |
---|
779 | // So therefore we need to iterate through by spectrum (axis 3) |
---|
780 | |
---|
781 | VectorIterator<Float> itData(valuesIn, axis); |
---|
782 | ReadOnlyVectorIterator<Bool> itMask(maskIn, axis); |
---|
783 | Float fac = 1.0; |
---|
784 | IPosition pos(nAxesSub,0); |
---|
785 | // |
---|
786 | while (!itData.pastEnd()) { |
---|
787 | |
---|
788 | // Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor |
---|
789 | |
---|
790 | if (useMask) { |
---|
791 | MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector()); |
---|
792 | fac = 1.0/variance(tmp); |
---|
793 | } else { |
---|
794 | MaskedArray<Float> tmp(itData.vector(),itMask.vector()); |
---|
795 | fac = 1.0/variance(tmp); |
---|
796 | } |
---|
797 | |
---|
798 | // Scale data |
---|
799 | |
---|
800 | itData.vector() *= fac; // Writes back into 'dataIn' |
---|
801 | // |
---|
802 | // Accumulate variance per if/pol/beam averaged over spectrum |
---|
803 | // This method to get pos2 from itData.pos() is only valid |
---|
804 | // because the spectral axis is the last one (so we can just |
---|
805 | // copy the first nAXesSub positions out) |
---|
806 | |
---|
807 | pos = itData.pos().getFirst(nAxesSub); |
---|
808 | sumSq(pos) += fac; |
---|
809 | // |
---|
810 | itData.next(); |
---|
811 | itMask.next(); |
---|
812 | } |
---|
813 | } else if (wtType==TSYS) { |
---|
814 | } |
---|
815 | |
---|
816 | // Accumulate sum of (possibly scaled) data |
---|
817 | |
---|
818 | sum += dataIn; |
---|
819 | |
---|
820 | // Accumulate Tsys, time, and interval |
---|
821 | |
---|
822 | tSysSum += tSys; |
---|
823 | timeSum += time; |
---|
824 | intSum += interval; |
---|
825 | nAccum += 1; |
---|
826 | } |
---|
827 | |
---|
828 | SDMemTable* SDMath::localOperate (const SDMemTable& in, Float val, Bool doAll, |
---|
829 | uInt what) |
---|
830 | // |
---|
831 | // what = 0 Multiply |
---|
832 | // 1 Add |
---|
833 | { |
---|
834 | SDMemTable* pOut = new SDMemTable(in,False); |
---|
835 | const Table& tOut = pOut->table(); |
---|
836 | ArrayColumn<Float> spec(tOut,"SPECTRA"); |
---|
837 | // |
---|
838 | if (doAll) { |
---|
839 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
840 | |
---|
841 | // Get |
---|
842 | |
---|
843 | MaskedArray<Float> marr(pOut->rowAsMaskedArray(i)); |
---|
844 | |
---|
845 | // Operate |
---|
846 | |
---|
847 | if (what==0) { |
---|
848 | marr *= val; |
---|
849 | } else if (what==1) { |
---|
850 | marr += val; |
---|
851 | } |
---|
852 | |
---|
853 | // Put |
---|
854 | |
---|
855 | spec.put(i, marr.getArray()); |
---|
856 | } |
---|
857 | } else { |
---|
858 | |
---|
859 | // Get cursor location |
---|
860 | |
---|
861 | IPosition start, end; |
---|
862 | getCursorLocation (start, end, in); |
---|
863 | // |
---|
864 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
865 | |
---|
866 | // Get |
---|
867 | |
---|
868 | MaskedArray<Float> dataIn(pOut->rowAsMaskedArray(i)); |
---|
869 | |
---|
870 | // Modify. More work than we would like to deal with the mask |
---|
871 | |
---|
872 | Array<Float>& values = dataIn.getRWArray(); |
---|
873 | Array<Bool> mask(dataIn.getMask()); |
---|
874 | // |
---|
875 | Array<Float> values2 = values(start,end); |
---|
876 | Array<Bool> mask2 = mask(start,end); |
---|
877 | MaskedArray<Float> t(values2,mask2); |
---|
878 | if (what==0) { |
---|
879 | t *= val; |
---|
880 | } else if (what==1) { |
---|
881 | t += val; |
---|
882 | } |
---|
883 | values(start, end) = t.getArray(); // Write back into 'dataIn' |
---|
884 | |
---|
885 | // Put |
---|
886 | spec.put(i, dataIn.getArray()); |
---|
887 | } |
---|
888 | } |
---|
889 | // |
---|
890 | return pOut; |
---|
891 | } |
---|
892 | |
---|
893 | |
---|
894 | |
---|
895 | void SDMath::getCursorLocation (IPosition& start, IPosition& end, |
---|
896 | const SDMemTable& in) |
---|
897 | { |
---|
898 | const uInt nDim = 4; |
---|
899 | const uInt i = in.getBeam(); |
---|
900 | const uInt j = in.getIF(); |
---|
901 | const uInt k = in.getPol(); |
---|
902 | const uInt n = in.nChan(); |
---|
903 | // |
---|
904 | IPosition s(nDim,i,j,k,0); |
---|
905 | IPosition e(nDim,i,j,k,n-1); |
---|
906 | // |
---|
907 | start.resize(nDim); |
---|
908 | start = s; |
---|
909 | end.resize(nDim); |
---|
910 | end = e; |
---|
911 | } |
---|