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/BasicMath/Math.h> |
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45 | #include <casa/Containers/Block.h> |
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46 | #include <casa/Quanta/QC.h> |
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47 | #include <casa/Utilities/Assert.h> |
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48 | #include <casa/Exceptions.h> |
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49 | |
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50 | #include <scimath/Mathematics/VectorKernel.h> |
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51 | #include <scimath/Mathematics/Convolver.h> |
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52 | #include <scimath/Mathematics/InterpolateArray1D.h> |
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53 | #include <scimath/Functionals/Polynomial.h> |
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54 | |
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55 | #include <tables/Tables/Table.h> |
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56 | #include <tables/Tables/ScalarColumn.h> |
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57 | #include <tables/Tables/ArrayColumn.h> |
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58 | #include <tables/Tables/ReadAsciiTable.h> |
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59 | |
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60 | #include <lattices/Lattices/LatticeUtilities.h> |
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61 | #include <lattices/Lattices/RebinLattice.h> |
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62 | #include <coordinates/Coordinates/SpectralCoordinate.h> |
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63 | #include <coordinates/Coordinates/CoordinateSystem.h> |
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64 | #include <coordinates/Coordinates/CoordinateUtil.h> |
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65 | #include <coordinates/Coordinates/VelocityAligner.h> |
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66 | |
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67 | #include "MathUtils.h" |
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68 | #include "SDDefs.h" |
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69 | #include "SDContainer.h" |
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70 | #include "SDMemTable.h" |
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71 | |
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72 | #include "SDMath.h" |
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73 | |
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74 | using namespace casa; |
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75 | using namespace asap; |
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76 | |
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77 | |
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78 | SDMath::SDMath() |
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79 | {;} |
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80 | |
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81 | SDMath::SDMath(const SDMath& other) |
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82 | { |
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83 | |
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84 | // No state |
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85 | |
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86 | } |
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87 | |
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88 | SDMath& SDMath::operator=(const SDMath& other) |
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89 | { |
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90 | if (this != &other) { |
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91 | // No state |
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92 | } |
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93 | return *this; |
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94 | } |
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95 | |
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96 | SDMath::~SDMath() |
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97 | {;} |
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98 | |
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99 | |
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100 | CountedPtr<SDMemTable> SDMath::average(const Block<CountedPtr<SDMemTable> >& in, |
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101 | const Vector<Bool>& mask, Bool scanAv, |
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102 | const String& weightStr) const |
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103 | //Bool alignVelocity) |
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104 | // |
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105 | // Weighted averaging of spectra from one or more Tables. |
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106 | // |
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107 | { |
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108 | Bool alignVelocity = False; |
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109 | |
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110 | // Convert weight type |
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111 | |
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112 | WeightType wtType = NONE; |
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113 | convertWeightString(wtType, weightStr); |
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114 | |
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115 | // Create output Table by cloning from the first table |
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116 | |
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117 | SDMemTable* pTabOut = new SDMemTable(*in[0],True); |
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118 | |
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119 | // Setup |
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120 | |
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121 | IPosition shp = in[0]->rowAsMaskedArray(0).shape(); // Must not change |
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122 | Array<Float> arr(shp); |
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123 | Array<Bool> barr(shp); |
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124 | const Bool useMask = (mask.nelements() == shp(asap::ChanAxis)); |
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125 | |
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126 | // Columns from Tables |
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127 | |
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128 | ROArrayColumn<Float> tSysCol; |
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129 | ROScalarColumn<Double> mjdCol; |
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130 | ROScalarColumn<String> srcNameCol; |
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131 | ROScalarColumn<Double> intCol; |
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132 | ROArrayColumn<uInt> fqIDCol; |
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133 | |
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134 | // Create accumulation MaskedArray. We accumulate for each channel,if,pol,beam |
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135 | // Note that the mask of the accumulation array will ALWAYS remain ALL True. |
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136 | // The MA is only used so that when data which is masked Bad is added to it, |
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137 | // that data does not contribute. |
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138 | |
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139 | Array<Float> zero(shp); |
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140 | zero=0.0; |
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141 | Array<Bool> good(shp); |
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142 | good = True; |
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143 | MaskedArray<Float> sum(zero,good); |
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144 | |
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145 | // Counter arrays |
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146 | |
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147 | Array<Float> nPts(shp); // Number of points |
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148 | nPts = 0.0; |
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149 | Array<Float> nInc(shp); // Increment |
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150 | nInc = 1.0; |
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151 | |
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152 | // Create accumulation Array for variance. We accumulate for |
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153 | // each if,pol,beam, but average over channel. So we need |
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154 | // a shape with one less axis dropping channels. |
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155 | |
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156 | const uInt nAxesSub = shp.nelements() - 1; |
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157 | IPosition shp2(nAxesSub); |
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158 | for (uInt i=0,j=0; i<(nAxesSub+1); i++) { |
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159 | if (i!=asap::ChanAxis) { |
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160 | shp2(j) = shp(i); |
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161 | j++; |
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162 | } |
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163 | } |
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164 | Array<Float> sumSq(shp2); |
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165 | sumSq = 0.0; |
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166 | IPosition pos2(nAxesSub,0); // For indexing |
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167 | |
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168 | // Time-related accumulators |
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169 | |
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170 | Double time; |
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171 | Double timeSum = 0.0; |
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172 | Double intSum = 0.0; |
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173 | Double interval = 0.0; |
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174 | |
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175 | // To get the right shape for the Tsys accumulator we need to |
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176 | // access a column from the first table. The shape of this |
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177 | // array must not change |
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178 | |
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179 | Array<Float> tSysSum; |
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180 | { |
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181 | const Table& tabIn = in[0]->table(); |
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182 | tSysCol.attach(tabIn,"TSYS"); |
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183 | tSysSum.resize(tSysCol.shape(0)); |
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184 | } |
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185 | tSysSum =0.0; |
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186 | Array<Float> tSys; |
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187 | |
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188 | // Scan and row tracking |
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189 | |
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190 | Int oldScanID = 0; |
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191 | Int outScanID = 0; |
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192 | Int scanID = 0; |
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193 | Int rowStart = 0; |
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194 | Int nAccum = 0; |
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195 | Int tableStart = 0; |
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196 | |
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197 | // Source and FreqID |
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198 | |
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199 | String sourceName, oldSourceName, sourceNameStart; |
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200 | Vector<uInt> freqID, freqIDStart, oldFreqID; |
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201 | |
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202 | // Velocity Aligner. We need an aligner for each Direction and FreqID |
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203 | // combination. I don't think there is anyway to know how many |
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204 | // directions there are. |
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205 | // For now, assume all Tables have the same Frequency Table |
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206 | |
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207 | /* |
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208 | { |
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209 | MEpoch::Ref timeRef(MEpoch::UTC); // Should be in header |
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210 | MDirection::Types dirRef(MDirection::J2000); // Should be in header |
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211 | // |
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212 | SDHeader sh = in[0].getSDHeader(); |
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213 | const uInt nChan = sh.nchan; |
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214 | // |
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215 | const SDFrequencyTable freqTab = in[0]->getSDFreqTable(); |
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216 | const uInt nFreqID = freqTab.length(); |
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217 | PtrBlock<const VelocityAligner<Float>* > vA(nFreqID); |
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218 | |
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219 | // Get first time from first table |
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220 | |
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221 | const Table& tabIn0 = in[0]->table(); |
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222 | mjdCol.attach(tabIn0, "TIME"); |
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223 | Double dTmp; |
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224 | mjdCol.get(0, dTmp); |
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225 | MVEpoch tmp2(Quantum<Double>(dTmp, Unit(String("d")))); |
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226 | MEpoch epoch(tmp2, timeRef); |
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227 | // |
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228 | for (uInt freqID=0; freqID<nFreqID; freqID++) { |
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229 | SpectralCoordinate sC = in[0]->getCoordinate(freqID); |
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230 | vA[freqID] = new VelocityAligner<Float>(sC, nChan, epoch, const MDirection& dir, |
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231 | const MPosition& pos, const String& velUnit, |
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232 | MDoppler::Types velType, MFrequency::Types velFreqSystem) |
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233 | } |
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234 | } |
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235 | */ |
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236 | |
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237 | // Loop over tables |
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238 | |
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239 | Float fac = 1.0; |
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240 | const uInt nTables = in.nelements(); |
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241 | for (uInt iTab=0; iTab<nTables; iTab++) { |
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242 | |
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243 | // Should check that the frequency tables don't change if doing VelocityAlignment |
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244 | |
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245 | // Attach columns to Table |
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246 | |
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247 | const Table& tabIn = in[iTab]->table(); |
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248 | tSysCol.attach(tabIn, "TSYS"); |
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249 | mjdCol.attach(tabIn, "TIME"); |
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250 | srcNameCol.attach(tabIn, "SRCNAME"); |
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251 | intCol.attach(tabIn, "INTERVAL"); |
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252 | fqIDCol.attach(tabIn, "FREQID"); |
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253 | |
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254 | // Loop over rows in Table |
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255 | |
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256 | const uInt nRows = in[iTab]->nRow(); |
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257 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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258 | |
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259 | // Check conformance |
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260 | |
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261 | IPosition shp2 = in[iTab]->rowAsMaskedArray(iRow).shape(); |
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262 | if (!shp.isEqual(shp2)) { |
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263 | throw (AipsError("Shapes for all rows must be the same")); |
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264 | } |
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265 | |
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266 | // If we are not doing scan averages, make checks for source and |
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267 | // frequency setup and warn if averaging across them |
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268 | |
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269 | // Get copy of Scan Container for this row |
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270 | |
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271 | SDContainer sc = in[iTab]->getSDContainer(iRow); |
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272 | scanID = sc.scanid; |
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273 | |
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274 | // Get quantities from columns |
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275 | |
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276 | srcNameCol.getScalar(iRow, sourceName); |
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277 | mjdCol.get(iRow, time); |
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278 | tSysCol.get(iRow, tSys); |
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279 | intCol.get(iRow, interval); |
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280 | fqIDCol.get(iRow, freqID); |
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281 | |
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282 | // Initialize first source and freqID |
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283 | |
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284 | if (iRow==0 && iTab==0) { |
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285 | sourceNameStart = sourceName; |
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286 | freqIDStart = freqID; |
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287 | } |
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288 | |
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289 | // If we are doing scan averages, see if we are at the end of an |
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290 | // accumulation period (scan). We must check soutce names too, |
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291 | // since we might have two tables with one scan each but different |
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292 | // source names; we shouldn't average different sources together |
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293 | |
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294 | if (scanAv && ( (scanID != oldScanID) || |
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295 | (iRow==0 && iTab>0 && sourceName!=oldSourceName))) { |
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296 | |
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297 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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298 | |
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299 | normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub); |
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300 | |
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301 | // Fill scan container. The source and freqID come from the |
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302 | // first row of the first table that went into this average ( |
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303 | // should be the same for all rows in the scan average) |
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304 | |
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305 | Float nR(nAccum); |
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306 | fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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307 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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308 | |
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309 | // Write container out to Table |
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310 | |
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311 | pTabOut->putSDContainer(sc); |
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312 | |
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313 | // Reset accumulators |
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314 | |
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315 | sum = 0.0; |
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316 | sumSq = 0.0; |
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317 | nAccum = 0; |
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318 | // |
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319 | tSysSum =0.0; |
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320 | timeSum = 0.0; |
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321 | intSum = 0.0; |
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322 | nPts = 0.0; |
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323 | |
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324 | // Increment |
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325 | |
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326 | rowStart = iRow; // First row for next accumulation |
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327 | tableStart = iTab; // First table for next accumulation |
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328 | sourceNameStart = sourceName; // First source name for next accumulation |
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329 | freqIDStart = freqID; // First FreqID for next accumulation |
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330 | // |
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331 | oldScanID = scanID; |
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332 | outScanID += 1; // Scan ID for next accumulation period |
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333 | } |
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334 | |
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335 | // Accumulate |
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336 | |
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337 | accumulate(timeSum, intSum, nAccum, sum, sumSq, nPts, tSysSum, |
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338 | tSys, nInc, mask, time, interval, in, iTab, iRow, asap::ChanAxis, |
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339 | nAxesSub, useMask, wtType); |
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340 | // |
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341 | oldSourceName = sourceName; |
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342 | oldFreqID = freqID; |
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343 | } |
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344 | } |
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345 | |
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346 | // OK at this point we have accumulation data which is either |
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347 | // - accumulated from all tables into one row |
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348 | // or |
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349 | // - accumulated from the last scan average |
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350 | // |
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351 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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352 | normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub); |
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353 | |
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354 | // Create and fill container. The container we clone will be from |
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355 | // the last Table and the first row that went into the current |
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356 | // accumulation. It probably doesn't matter that much really... |
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357 | |
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358 | Float nR(nAccum); |
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359 | SDContainer sc = in[tableStart]->getSDContainer(rowStart); |
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360 | fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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361 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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362 | pTabOut->putSDContainer(sc); |
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363 | // |
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364 | return CountedPtr<SDMemTable>(pTabOut); |
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365 | } |
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366 | |
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367 | |
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368 | |
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369 | CountedPtr<SDMemTable> SDMath::quotient(const CountedPtr<SDMemTable>& on, |
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370 | const CountedPtr<SDMemTable>& off, |
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371 | Bool preserveContinuum) const |
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372 | { |
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373 | const uInt nRowOn = on->nRow(); |
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374 | const uInt nRowOff = off->nRow(); |
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375 | Bool ok = (nRowOff==1&&nRowOn>0) || |
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376 | (nRowOn>0&&nRowOn==nRowOff); |
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377 | if (!ok) { |
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378 | throw (AipsError("The reference Scan Table can have one row or the same number of rows as the source Scan Table")); |
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379 | } |
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380 | |
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381 | // Input Tables and columns |
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382 | |
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383 | Table tabOn = on->table(); |
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384 | Table tabOff = off->table(); |
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385 | ROArrayColumn<Float> tSysOn(tabOn, "TSYS"); |
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386 | ROArrayColumn<Float> tSysOff(tabOff, "TSYS"); |
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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 | MaskedArray<Float>* pMOff = new MaskedArray<Float>(off->rowAsMaskedArray(0)); |
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395 | IPosition shpOff = pMOff->shape(); |
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396 | // |
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397 | Array<Float> tSysOnArr, tSysOffArr; |
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398 | tSysOn.get(0, tSysOnArr); |
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399 | tSysOff.get(0, tSysOffArr); |
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400 | // |
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401 | for (uInt i=0; i<nRowOn; i++) { |
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402 | MaskedArray<Float> mOn(on->rowAsMaskedArray(i)); |
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403 | IPosition shpOn = mOn.shape(); |
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404 | // |
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405 | if (nRowOff>1) { |
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406 | delete pMOff; |
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407 | pMOff = new MaskedArray<Float>(off->rowAsMaskedArray(i)); |
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408 | shpOff = pMOff->shape(); |
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409 | if (!shpOn.isEqual(shpOff)) { |
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410 | throw(AipsError("on/off data are not conformant")); |
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411 | } |
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412 | // |
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413 | tSysOff.get(i, tSysOffArr); |
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414 | tSysOn.get(i, tSysOnArr); |
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415 | if (!tSysOnArr.shape().isEqual(tSysOffArr.shape())) { |
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416 | throw(AipsError("on/off Tsys data are not conformant")); |
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417 | } |
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418 | // |
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419 | if (!shpOn.isEqual(tSysOnArr.shape())) { |
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420 | throw(AipsError("Correlation and Tsys data are not conformant")); |
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421 | } |
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422 | } |
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423 | |
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424 | // Compute quotient |
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425 | |
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426 | MaskedArray<Float> tmp = (mOn-*pMOff); |
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427 | Array<Float> out(tmp.getArray()); |
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428 | out /= *pMOff; |
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429 | out *= tSysOffArr; |
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430 | |
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431 | // MaskedArray<Float> tmp2 = (tSysOnArr * mOn / *pMOff) - tSysOffArr; |
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432 | |
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433 | |
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434 | // Fill container for this row |
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435 | |
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436 | SDContainer sc = on->getSDContainer(i); |
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437 | // |
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438 | putDataInSDC(sc, out, tmp.getMask()); |
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439 | sc.putTsys(tSysOffArr); |
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440 | sc.scanid = i; |
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441 | |
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442 | // Put new row in output Table |
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443 | |
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444 | pTabOut->putSDContainer(sc); |
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445 | } |
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446 | if (pMOff) delete pMOff; |
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447 | // |
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448 | return CountedPtr<SDMemTable>(pTabOut); |
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449 | } |
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450 | |
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451 | |
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452 | CountedPtr<SDMemTable> SDMath::simpleBinaryOperate (const CountedPtr<SDMemTable>& left, |
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453 | const CountedPtr<SDMemTable>& right, |
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454 | const String& op) const |
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455 | // |
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456 | // Simple binary Table operators. add, subtract, multiply, divide (what=0,1,2,3) |
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457 | // |
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458 | { |
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459 | |
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460 | // CHeck operator |
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461 | |
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462 | String op2(op); |
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463 | op2.upcase(); |
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464 | uInt what = 0; |
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465 | if (op2=="ADD") { |
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466 | what = 0; |
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467 | } else if (op2=="SUB") { |
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468 | what = 1; |
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469 | } else if (op2=="MUL") { |
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470 | what = 2; |
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471 | } else if (op2=="DIV") { |
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472 | what = 3; |
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473 | } else { |
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474 | throw AipsError("Unrecognized operation"); |
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475 | } |
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476 | |
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477 | // Check rows |
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478 | |
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479 | const uInt nRows = left->nRow(); |
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480 | if (right->nRow() != nRows) { |
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481 | throw (AipsError("Input Scan Tables must have the same number of rows")); |
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482 | } |
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483 | |
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484 | // Input Tables and columns |
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485 | |
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486 | const Table& tLeft = left->table(); |
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487 | const Table& tRight = right->table(); |
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488 | // |
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489 | ROArrayColumn<Float> tSysLeft(tLeft, "TSYS"); |
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490 | ROArrayColumn<Float> tSysRight(tRight, "TSYS"); |
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491 | |
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492 | // Output Table cloned from input |
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493 | |
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494 | SDMemTable* pTabOut = new SDMemTable(*left, True); |
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495 | |
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496 | // Loop over rows |
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497 | |
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498 | for (uInt i=0; i<nRows; i++) { |
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499 | |
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500 | // Get data |
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501 | MaskedArray<Float> mLeft(left->rowAsMaskedArray(i)); |
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502 | MaskedArray<Float> mRight(right->rowAsMaskedArray(i)); |
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503 | // |
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504 | IPosition shpLeft = mLeft.shape(); |
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505 | IPosition shpRight = mRight.shape(); |
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506 | if (!shpLeft.isEqual(shpRight)) { |
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507 | throw(AipsError("left/right Scan Tables are not conformant")); |
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508 | } |
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509 | |
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510 | // Get TSys |
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511 | |
---|
512 | Array<Float> tSysLeftArr, tSysRightArr; |
---|
513 | tSysLeft.get(i, tSysLeftArr); |
---|
514 | tSysRight.get(i, tSysRightArr); |
---|
515 | |
---|
516 | // Make container |
---|
517 | |
---|
518 | SDContainer sc = left->getSDContainer(i); |
---|
519 | |
---|
520 | // Operate on data and TSys |
---|
521 | |
---|
522 | if (what==0) { |
---|
523 | MaskedArray<Float> tmp = mLeft + mRight; |
---|
524 | putDataInSDC(sc, tmp.getArray(), tmp.getMask()); |
---|
525 | sc.putTsys(tSysLeftArr+tSysRightArr); |
---|
526 | } else if (what==1) { |
---|
527 | MaskedArray<Float> tmp = mLeft - mRight; |
---|
528 | putDataInSDC(sc, tmp.getArray(), tmp.getMask()); |
---|
529 | sc.putTsys(tSysLeftArr-tSysRightArr); |
---|
530 | } else if (what==2) { |
---|
531 | MaskedArray<Float> tmp = mLeft * mRight; |
---|
532 | putDataInSDC(sc, tmp.getArray(), tmp.getMask()); |
---|
533 | sc.putTsys(tSysLeftArr*tSysRightArr); |
---|
534 | } else if (what==3) { |
---|
535 | MaskedArray<Float> tmp = mLeft / mRight; |
---|
536 | putDataInSDC(sc, tmp.getArray(), tmp.getMask()); |
---|
537 | sc.putTsys(tSysLeftArr/tSysRightArr); |
---|
538 | } |
---|
539 | |
---|
540 | // Put new row in output Table |
---|
541 | |
---|
542 | pTabOut->putSDContainer(sc); |
---|
543 | } |
---|
544 | // |
---|
545 | return CountedPtr<SDMemTable>(pTabOut); |
---|
546 | } |
---|
547 | |
---|
548 | |
---|
549 | |
---|
550 | std::vector<float> SDMath::statistic(const CountedPtr<SDMemTable>& in, |
---|
551 | const Vector<Bool>& mask, |
---|
552 | const String& which, Int row) const |
---|
553 | // |
---|
554 | // Perhaps iteration over pol/beam/if should be in here |
---|
555 | // and inside the nrow iteration ? |
---|
556 | // |
---|
557 | { |
---|
558 | const uInt nRow = in->nRow(); |
---|
559 | |
---|
560 | // Specify cursor location |
---|
561 | |
---|
562 | IPosition start, end; |
---|
563 | getCursorLocation(start, end, *in); |
---|
564 | |
---|
565 | // Loop over rows |
---|
566 | |
---|
567 | const uInt nEl = mask.nelements(); |
---|
568 | uInt iStart = 0; |
---|
569 | uInt iEnd = in->nRow()-1; |
---|
570 | // |
---|
571 | if (row>=0) { |
---|
572 | iStart = row; |
---|
573 | iEnd = row; |
---|
574 | } |
---|
575 | // |
---|
576 | std::vector<float> result(iEnd-iStart+1); |
---|
577 | for (uInt ii=iStart; ii <= iEnd; ++ii) { |
---|
578 | |
---|
579 | // Get row and deconstruct |
---|
580 | |
---|
581 | MaskedArray<Float> marr(in->rowAsMaskedArray(ii)); |
---|
582 | Array<Float> arr = marr.getArray(); |
---|
583 | Array<Bool> barr = marr.getMask(); |
---|
584 | |
---|
585 | // Access desired piece of data |
---|
586 | |
---|
587 | Array<Float> v((arr(start,end)).nonDegenerate()); |
---|
588 | Array<Bool> m((barr(start,end)).nonDegenerate()); |
---|
589 | |
---|
590 | // Apply OTF mask |
---|
591 | |
---|
592 | MaskedArray<Float> tmp; |
---|
593 | if (m.nelements()==nEl) { |
---|
594 | tmp.setData(v,m&&mask); |
---|
595 | } else { |
---|
596 | tmp.setData(v,m); |
---|
597 | } |
---|
598 | |
---|
599 | // Get statistic |
---|
600 | |
---|
601 | result[ii-iStart] = mathutil::statistics(which, tmp); |
---|
602 | } |
---|
603 | // |
---|
604 | return result; |
---|
605 | } |
---|
606 | |
---|
607 | |
---|
608 | SDMemTable* SDMath::bin(const SDMemTable& in, Int width) const |
---|
609 | { |
---|
610 | SDHeader sh = in.getSDHeader(); |
---|
611 | SDMemTable* pTabOut = new SDMemTable(in, True); |
---|
612 | |
---|
613 | // Bin up SpectralCoordinates |
---|
614 | |
---|
615 | IPosition factors(1); |
---|
616 | factors(0) = width; |
---|
617 | for (uInt j=0; j<in.nCoordinates(); ++j) { |
---|
618 | CoordinateSystem cSys; |
---|
619 | cSys.addCoordinate(in.getCoordinate(j)); |
---|
620 | CoordinateSystem cSysBin = |
---|
621 | CoordinateUtil::makeBinnedCoordinateSystem(factors, cSys, False); |
---|
622 | // |
---|
623 | SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0); |
---|
624 | pTabOut->setCoordinate(sCBin, j); |
---|
625 | } |
---|
626 | |
---|
627 | // Use RebinLattice to find shape |
---|
628 | |
---|
629 | IPosition shapeIn(1,sh.nchan); |
---|
630 | IPosition shapeOut = RebinLattice<Float>::rebinShape(shapeIn, factors); |
---|
631 | sh.nchan = shapeOut(0); |
---|
632 | pTabOut->putSDHeader(sh); |
---|
633 | |
---|
634 | |
---|
635 | // Loop over rows and bin along channel axis |
---|
636 | |
---|
637 | for (uInt i=0; i < in.nRow(); ++i) { |
---|
638 | SDContainer sc = in.getSDContainer(i); |
---|
639 | // |
---|
640 | Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape |
---|
641 | |
---|
642 | // Bin up spectrum |
---|
643 | |
---|
644 | MaskedArray<Float> marr(in.rowAsMaskedArray(i)); |
---|
645 | MaskedArray<Float> marrout; |
---|
646 | LatticeUtilities::bin(marrout, marr, asap::ChanAxis, width); |
---|
647 | |
---|
648 | // Put back the binned data and flags |
---|
649 | |
---|
650 | IPosition ip2 = marrout.shape(); |
---|
651 | sc.resize(ip2); |
---|
652 | // |
---|
653 | putDataInSDC(sc, marrout.getArray(), marrout.getMask()); |
---|
654 | |
---|
655 | // Bin up Tsys. |
---|
656 | |
---|
657 | Array<Bool> allGood(tSys.shape(),True); |
---|
658 | MaskedArray<Float> tSysIn(tSys, allGood, True); |
---|
659 | // |
---|
660 | MaskedArray<Float> tSysOut; |
---|
661 | LatticeUtilities::bin(tSysOut, tSysIn, asap::ChanAxis, width); |
---|
662 | sc.putTsys(tSysOut.getArray()); |
---|
663 | // |
---|
664 | pTabOut->putSDContainer(sc); |
---|
665 | } |
---|
666 | return pTabOut; |
---|
667 | } |
---|
668 | |
---|
669 | SDMemTable* SDMath::simpleOperate(const SDMemTable& in, Float val, Bool doAll, |
---|
670 | uInt what) const |
---|
671 | // |
---|
672 | // what = 0 Multiply |
---|
673 | // 1 Add |
---|
674 | { |
---|
675 | SDMemTable* pOut = new SDMemTable(in,False); |
---|
676 | const Table& tOut = pOut->table(); |
---|
677 | ArrayColumn<Float> spec(tOut,"SPECTRA"); |
---|
678 | // |
---|
679 | if (doAll) { |
---|
680 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
681 | |
---|
682 | // Get |
---|
683 | |
---|
684 | MaskedArray<Float> marr(pOut->rowAsMaskedArray(i)); |
---|
685 | |
---|
686 | // Operate |
---|
687 | |
---|
688 | if (what==0) { |
---|
689 | marr *= val; |
---|
690 | } else if (what==1) { |
---|
691 | marr += val; |
---|
692 | } |
---|
693 | |
---|
694 | // Put |
---|
695 | |
---|
696 | spec.put(i, marr.getArray()); |
---|
697 | } |
---|
698 | } else { |
---|
699 | |
---|
700 | // Get cursor location |
---|
701 | |
---|
702 | IPosition start, end; |
---|
703 | getCursorLocation(start, end, in); |
---|
704 | // |
---|
705 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
706 | |
---|
707 | // Get |
---|
708 | |
---|
709 | MaskedArray<Float> dataIn(pOut->rowAsMaskedArray(i)); |
---|
710 | |
---|
711 | // Modify. More work than we would like to deal with the mask |
---|
712 | |
---|
713 | Array<Float>& values = dataIn.getRWArray(); |
---|
714 | Array<Bool> mask(dataIn.getMask()); |
---|
715 | // |
---|
716 | Array<Float> values2 = values(start,end); |
---|
717 | Array<Bool> mask2 = mask(start,end); |
---|
718 | MaskedArray<Float> t(values2,mask2); |
---|
719 | if (what==0) { |
---|
720 | t *= val; |
---|
721 | } else if (what==1) { |
---|
722 | t += val; |
---|
723 | } |
---|
724 | values(start, end) = t.getArray(); // Write back into 'dataIn' |
---|
725 | |
---|
726 | // Put |
---|
727 | spec.put(i, dataIn.getArray()); |
---|
728 | } |
---|
729 | } |
---|
730 | // |
---|
731 | return pOut; |
---|
732 | } |
---|
733 | |
---|
734 | |
---|
735 | |
---|
736 | SDMemTable* SDMath::averagePol(const SDMemTable& in, const Vector<Bool>& mask) const |
---|
737 | // |
---|
738 | // Average all polarizations together, weighted by variance |
---|
739 | // |
---|
740 | { |
---|
741 | // WeightType wtType = NONE; |
---|
742 | // convertWeightString(wtType, weight); |
---|
743 | |
---|
744 | const uInt nRows = in.nRow(); |
---|
745 | const uInt polAxis = asap::PolAxis; // Polarization axis |
---|
746 | const uInt chanAxis = asap::ChanAxis; // Spectrum axis |
---|
747 | |
---|
748 | // Create output Table and reshape number of polarizations |
---|
749 | |
---|
750 | Bool clear=True; |
---|
751 | SDMemTable* pTabOut = new SDMemTable(in, clear); |
---|
752 | SDHeader header = pTabOut->getSDHeader(); |
---|
753 | header.npol = 1; |
---|
754 | pTabOut->putSDHeader(header); |
---|
755 | |
---|
756 | // Shape of input and output data |
---|
757 | |
---|
758 | const IPosition& shapeIn = in.rowAsMaskedArray(0u, False).shape(); |
---|
759 | IPosition shapeOut(shapeIn); |
---|
760 | shapeOut(polAxis) = 1; // Average all polarizations |
---|
761 | // |
---|
762 | const uInt nChan = shapeIn(chanAxis); |
---|
763 | const IPosition vecShapeOut(4,1,1,1,nChan); // A multi-dim form of a Vector shape |
---|
764 | IPosition start(4), end(4); |
---|
765 | |
---|
766 | // Output arrays |
---|
767 | |
---|
768 | Array<Float> outData(shapeOut, 0.0); |
---|
769 | Array<Bool> outMask(shapeOut, True); |
---|
770 | const IPosition axes(2, 2, 3); // pol-channel plane |
---|
771 | // |
---|
772 | const Bool useMask = (mask.nelements() == shapeIn(chanAxis)); |
---|
773 | |
---|
774 | // Loop over rows |
---|
775 | |
---|
776 | for (uInt iRow=0; iRow<nRows; iRow++) { |
---|
777 | |
---|
778 | // Get data for this row |
---|
779 | |
---|
780 | MaskedArray<Float> marr(in.rowAsMaskedArray(iRow)); |
---|
781 | Array<Float>& arr = marr.getRWArray(); |
---|
782 | const Array<Bool>& barr = marr.getMask(); |
---|
783 | |
---|
784 | // Make iterators to iterate by pol-channel planes |
---|
785 | |
---|
786 | ReadOnlyArrayIterator<Float> itDataPlane(arr, axes); |
---|
787 | ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes); |
---|
788 | |
---|
789 | // Accumulations |
---|
790 | |
---|
791 | Float fac = 1.0; |
---|
792 | Vector<Float> vecSum(nChan,0.0); |
---|
793 | |
---|
794 | // Iterate through data by pol-channel planes |
---|
795 | |
---|
796 | while (!itDataPlane.pastEnd()) { |
---|
797 | |
---|
798 | // Iterate through plane by polarization and accumulate Vectors |
---|
799 | |
---|
800 | Vector<Float> t1(nChan); t1 = 0.0; |
---|
801 | Vector<Bool> t2(nChan); t2 = True; |
---|
802 | MaskedArray<Float> vecSum(t1,t2); |
---|
803 | Float varSum = 0.0; |
---|
804 | { |
---|
805 | ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1); |
---|
806 | ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1); |
---|
807 | while (!itDataVec.pastEnd()) { |
---|
808 | |
---|
809 | // Create MA of data & mask (optionally including OTF mask) and get variance |
---|
810 | |
---|
811 | if (useMask) { |
---|
812 | const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector()); |
---|
813 | fac = 1.0 / variance(spec); |
---|
814 | } else { |
---|
815 | const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector()); |
---|
816 | fac = 1.0 / variance(spec); |
---|
817 | } |
---|
818 | |
---|
819 | // Normalize spectrum (without OTF mask) and accumulate |
---|
820 | |
---|
821 | const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector()); |
---|
822 | vecSum += spec; |
---|
823 | varSum += fac; |
---|
824 | |
---|
825 | // Next |
---|
826 | |
---|
827 | itDataVec.next(); |
---|
828 | itMaskVec.next(); |
---|
829 | } |
---|
830 | } |
---|
831 | |
---|
832 | // Normalize summed spectrum |
---|
833 | |
---|
834 | vecSum /= varSum; |
---|
835 | |
---|
836 | // FInd position in input data array. We are iterating by pol-channel |
---|
837 | // plane so all that will change is beam and IF and that's what we want. |
---|
838 | |
---|
839 | IPosition pos = itDataPlane.pos(); |
---|
840 | |
---|
841 | // Write out data. This is a bit messy. We have to reform the Vector |
---|
842 | // accumulator into an Array of shape (1,1,1,nChan) |
---|
843 | |
---|
844 | start = pos; |
---|
845 | end = pos; |
---|
846 | end(chanAxis) = nChan-1; |
---|
847 | outData(start,end) = vecSum.getArray().reform(vecShapeOut); |
---|
848 | outMask(start,end) = vecSum.getMask().reform(vecShapeOut); |
---|
849 | |
---|
850 | // Step to next beam/IF combination |
---|
851 | |
---|
852 | itDataPlane.next(); |
---|
853 | itMaskPlane.next(); |
---|
854 | } |
---|
855 | |
---|
856 | // Generate output container and write it to output table |
---|
857 | |
---|
858 | SDContainer sc = in.getSDContainer(); |
---|
859 | sc.resize(shapeOut); |
---|
860 | // |
---|
861 | putDataInSDC(sc, outData, outMask); |
---|
862 | pTabOut->putSDContainer(sc); |
---|
863 | } |
---|
864 | // |
---|
865 | return pTabOut; |
---|
866 | } |
---|
867 | |
---|
868 | |
---|
869 | SDMemTable* SDMath::smooth(const SDMemTable& in, |
---|
870 | const casa::String& kernelType, |
---|
871 | casa::Float width, Bool doAll) const |
---|
872 | { |
---|
873 | |
---|
874 | // Number of channels |
---|
875 | |
---|
876 | const uInt chanAxis = asap::ChanAxis; // Spectral axis |
---|
877 | SDHeader sh = in.getSDHeader(); |
---|
878 | const uInt nChan = sh.nchan; |
---|
879 | |
---|
880 | // Generate Kernel |
---|
881 | |
---|
882 | VectorKernel::KernelTypes type = VectorKernel::toKernelType(kernelType); |
---|
883 | Vector<Float> kernel = VectorKernel::make(type, width, nChan, True, False); |
---|
884 | |
---|
885 | // Generate Convolver |
---|
886 | |
---|
887 | IPosition shape(1,nChan); |
---|
888 | Convolver<Float> conv(kernel, shape); |
---|
889 | |
---|
890 | // New Table |
---|
891 | |
---|
892 | SDMemTable* pTabOut = new SDMemTable(in,True); |
---|
893 | |
---|
894 | // Get cursor location |
---|
895 | |
---|
896 | IPosition start, end; |
---|
897 | getCursorLocation(start, end, in); |
---|
898 | // |
---|
899 | IPosition shapeOut(4,1); |
---|
900 | |
---|
901 | // Output Vectors |
---|
902 | |
---|
903 | Vector<Float> valuesOut(nChan); |
---|
904 | Vector<Bool> maskOut(nChan); |
---|
905 | |
---|
906 | // Loop over rows in Table |
---|
907 | |
---|
908 | for (uInt ri=0; ri < in.nRow(); ++ri) { |
---|
909 | |
---|
910 | // Get copy of data |
---|
911 | |
---|
912 | const MaskedArray<Float>& dataIn(in.rowAsMaskedArray(ri)); |
---|
913 | AlwaysAssert(dataIn.shape()(chanAxis)==nChan, AipsError); |
---|
914 | // |
---|
915 | Array<Float> valuesIn = dataIn.getArray(); |
---|
916 | Array<Bool> maskIn = dataIn.getMask(); |
---|
917 | |
---|
918 | // Branch depending on whether we smooth all locations or just |
---|
919 | // those pointed at by the current selection cursor |
---|
920 | |
---|
921 | if (doAll) { |
---|
922 | uInt axis = asap::ChanAxis; |
---|
923 | VectorIterator<Float> itValues(valuesIn, axis); |
---|
924 | VectorIterator<Bool> itMask(maskIn, axis); |
---|
925 | while (!itValues.pastEnd()) { |
---|
926 | |
---|
927 | // Smooth |
---|
928 | if (kernelType==VectorKernel::HANNING) { |
---|
929 | mathutil::hanning(valuesOut, maskOut, itValues.vector(), itMask.vector()); |
---|
930 | itMask.vector() = maskOut; |
---|
931 | } else { |
---|
932 | mathutil::replaceMaskByZero(itValues.vector(), itMask.vector()); |
---|
933 | conv.linearConv(valuesOut, itValues.vector()); |
---|
934 | } |
---|
935 | // |
---|
936 | itValues.vector() = valuesOut; |
---|
937 | // |
---|
938 | itValues.next(); |
---|
939 | itMask.next(); |
---|
940 | } |
---|
941 | } else { |
---|
942 | |
---|
943 | // Set multi-dim Vector shape |
---|
944 | |
---|
945 | shapeOut(chanAxis) = valuesIn.shape()(chanAxis); |
---|
946 | |
---|
947 | // Stuff about with shapes so that we don't have conformance run-time errors |
---|
948 | |
---|
949 | Vector<Float> valuesIn2 = valuesIn(start,end).nonDegenerate(); |
---|
950 | Vector<Bool> maskIn2 = maskIn(start,end).nonDegenerate(); |
---|
951 | |
---|
952 | // Smooth |
---|
953 | |
---|
954 | if (kernelType==VectorKernel::HANNING) { |
---|
955 | mathutil::hanning(valuesOut, maskOut, valuesIn2, maskIn2); |
---|
956 | maskIn(start,end) = maskOut.reform(shapeOut); |
---|
957 | } else { |
---|
958 | mathutil::replaceMaskByZero(valuesIn2, maskIn2); |
---|
959 | conv.linearConv(valuesOut, valuesIn2); |
---|
960 | } |
---|
961 | // |
---|
962 | valuesIn(start,end) = valuesOut.reform(shapeOut); |
---|
963 | } |
---|
964 | |
---|
965 | // Create and put back |
---|
966 | |
---|
967 | SDContainer sc = in.getSDContainer(ri); |
---|
968 | putDataInSDC(sc, valuesIn, maskIn); |
---|
969 | // |
---|
970 | pTabOut->putSDContainer(sc); |
---|
971 | } |
---|
972 | // |
---|
973 | return pTabOut; |
---|
974 | } |
---|
975 | |
---|
976 | |
---|
977 | SDMemTable* SDMath::convertFlux (const SDMemTable& in, Float a, Float eta, Bool doAll) const |
---|
978 | // |
---|
979 | // As it is, this function could be implemented with 'simpleOperate' |
---|
980 | // However, I anticipate that eventually we will look the conversion |
---|
981 | // values up in a Table and apply them in a frequency dependent way, |
---|
982 | // so I have implemented it fully here |
---|
983 | // |
---|
984 | { |
---|
985 | SDHeader sh = in.getSDHeader(); |
---|
986 | SDMemTable* pTabOut = new SDMemTable(in, True); |
---|
987 | |
---|
988 | // FInd out how to convert values into Jy and K (e.g. units might be mJy or mK) |
---|
989 | // Also automatically find out what we are converting to according to the |
---|
990 | // flux unit |
---|
991 | |
---|
992 | Unit fluxUnit(sh.fluxunit); |
---|
993 | Unit K(String("K")); |
---|
994 | Unit JY(String("Jy")); |
---|
995 | // |
---|
996 | Bool toKelvin = True; |
---|
997 | Double inFac = 1.0; |
---|
998 | if (fluxUnit==JY) { |
---|
999 | cerr << "Converting to K" << endl; |
---|
1000 | // |
---|
1001 | Quantum<Double> t(1.0,fluxUnit); |
---|
1002 | Quantum<Double> t2 = t.get(JY); |
---|
1003 | inFac = (t2 / t).getValue(); |
---|
1004 | // |
---|
1005 | toKelvin = True; |
---|
1006 | sh.fluxunit = "K"; |
---|
1007 | } else if (fluxUnit==K) { |
---|
1008 | cerr << "Converting to Jy" << endl; |
---|
1009 | // |
---|
1010 | Quantum<Double> t(1.0,fluxUnit); |
---|
1011 | Quantum<Double> t2 = t.get(K); |
---|
1012 | inFac = (t2 / t).getValue(); |
---|
1013 | // |
---|
1014 | toKelvin = False; |
---|
1015 | sh.fluxunit = "Jy"; |
---|
1016 | } else { |
---|
1017 | throw AipsError("Unrecognized brightness units in Table - must be consistent with Jy or K"); |
---|
1018 | } |
---|
1019 | pTabOut->putSDHeader(sh); |
---|
1020 | |
---|
1021 | // Compute conversion factor. 'a' and 'eta' are really frequency, time and |
---|
1022 | // telescope dependent and should be looked// up in a table |
---|
1023 | |
---|
1024 | Float factor = 2.0 * inFac * 1.0e-7 * 1.0e26 * |
---|
1025 | QC::k.getValue(Unit(String("erg/K"))) / a / eta; |
---|
1026 | if (toKelvin) { |
---|
1027 | factor = 1.0 / factor; |
---|
1028 | } |
---|
1029 | cerr << "Applying conversion factor = " << factor << endl; |
---|
1030 | |
---|
1031 | // For operations only on specified cursor location |
---|
1032 | |
---|
1033 | IPosition start, end; |
---|
1034 | getCursorLocation(start, end, in); |
---|
1035 | |
---|
1036 | // Loop over rows and apply factor to spectra |
---|
1037 | |
---|
1038 | const uInt axis = asap::ChanAxis; |
---|
1039 | for (uInt i=0; i < in.nRow(); ++i) { |
---|
1040 | |
---|
1041 | // Get data |
---|
1042 | |
---|
1043 | MaskedArray<Float> dataIn(in.rowAsMaskedArray(i)); |
---|
1044 | Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference |
---|
1045 | const Array<Bool>& maskIn = dataIn.getMask(); |
---|
1046 | |
---|
1047 | // Need to apply correct conversion factor (frequency and time dependent) |
---|
1048 | // which should be sourced from a Table. For now we just apply the given |
---|
1049 | // factor to everything |
---|
1050 | |
---|
1051 | if (doAll) { |
---|
1052 | VectorIterator<Float> itValues(valuesIn, asap::ChanAxis); |
---|
1053 | while (!itValues.pastEnd()) { |
---|
1054 | itValues.vector() *= factor; // Writes back into dataIn |
---|
1055 | // |
---|
1056 | itValues.next(); |
---|
1057 | } |
---|
1058 | } else { |
---|
1059 | Array<Float> valuesIn2 = valuesIn(start,end); |
---|
1060 | valuesIn2 *= factor; |
---|
1061 | valuesIn(start,end) = valuesIn2; |
---|
1062 | } |
---|
1063 | |
---|
1064 | // Write out |
---|
1065 | |
---|
1066 | SDContainer sc = in.getSDContainer(i); |
---|
1067 | putDataInSDC(sc, valuesIn, maskIn); |
---|
1068 | // |
---|
1069 | pTabOut->putSDContainer(sc); |
---|
1070 | } |
---|
1071 | return pTabOut; |
---|
1072 | } |
---|
1073 | |
---|
1074 | |
---|
1075 | |
---|
1076 | SDMemTable* SDMath::gainElevation (const SDMemTable& in, const Vector<Float>& coeffs, |
---|
1077 | const String& fileName, |
---|
1078 | const String& methodStr, Bool doAll) const |
---|
1079 | { |
---|
1080 | |
---|
1081 | // Get header and clone output table |
---|
1082 | |
---|
1083 | SDHeader sh = in.getSDHeader(); |
---|
1084 | SDMemTable* pTabOut = new SDMemTable(in, True); |
---|
1085 | |
---|
1086 | // Get elevation data from SDMemTable and convert to degrees |
---|
1087 | |
---|
1088 | const Table& tab = in.table(); |
---|
1089 | ROScalarColumn<Float> elev(tab, "ELEVATION"); |
---|
1090 | Vector<Float> x = elev.getColumn(); |
---|
1091 | x *= Float(180 / C::pi); |
---|
1092 | // |
---|
1093 | const uInt nC = coeffs.nelements(); |
---|
1094 | if (fileName.length()>0 && nC>0) { |
---|
1095 | throw AipsError("You must choose either polynomial coefficients or an ascii file, not both"); |
---|
1096 | } |
---|
1097 | |
---|
1098 | // Correct |
---|
1099 | |
---|
1100 | if (nC>0 || fileName.length()==0) { |
---|
1101 | |
---|
1102 | // Find instrument |
---|
1103 | |
---|
1104 | Bool throwIt = True; |
---|
1105 | Instrument inst = SDMemTable::convertInstrument (sh.antennaname, throwIt); |
---|
1106 | |
---|
1107 | // Set polynomial |
---|
1108 | |
---|
1109 | Polynomial<Float>* pPoly = 0; |
---|
1110 | Vector<Float> coeff; |
---|
1111 | String msg; |
---|
1112 | if (nC>0) { |
---|
1113 | pPoly = new Polynomial<Float>(nC); |
---|
1114 | coeff = coeffs; |
---|
1115 | msg = String("user"); |
---|
1116 | } else { |
---|
1117 | if (inst==PKSMULTIBEAM) { |
---|
1118 | } else if (inst==PKSSINGLEBEAM) { |
---|
1119 | } else if (inst==TIDBINBILLA) { |
---|
1120 | pPoly = new Polynomial<Float>(3); |
---|
1121 | coeff.resize(3); |
---|
1122 | coeff(0) = 3.58788e-1; |
---|
1123 | coeff(1) = 2.87243e-2; |
---|
1124 | coeff(2) = -3.219093e-4; |
---|
1125 | } else if (inst==MOPRA) { |
---|
1126 | } |
---|
1127 | msg = String("built in"); |
---|
1128 | } |
---|
1129 | // |
---|
1130 | if (coeff.nelements()>0) { |
---|
1131 | pPoly->setCoefficients(coeff); |
---|
1132 | } else { |
---|
1133 | throw AipsError("There is no known gain-el polynomial known for this instrument"); |
---|
1134 | } |
---|
1135 | // |
---|
1136 | cerr << "Making polynomial correction with " << msg << " coefficients" << endl; |
---|
1137 | const uInt nRow = in.nRow(); |
---|
1138 | Vector<Float> factor(nRow); |
---|
1139 | for (uInt i=0; i<nRow; i++) { |
---|
1140 | factor[i] = (*pPoly)(x[i]); |
---|
1141 | } |
---|
1142 | delete pPoly; |
---|
1143 | // |
---|
1144 | correctFromVector (pTabOut, in, doAll, factor); |
---|
1145 | } else { |
---|
1146 | |
---|
1147 | // Indicate which columns to read from ascii file |
---|
1148 | |
---|
1149 | String col0("ELEVATION"); |
---|
1150 | String col1("FACTOR"); |
---|
1151 | |
---|
1152 | // Read and correct |
---|
1153 | |
---|
1154 | cerr << "Making correction from ascii Table" << endl; |
---|
1155 | correctFromAsciiTable (pTabOut, in, fileName, col0, col1, |
---|
1156 | methodStr, doAll, x); |
---|
1157 | } |
---|
1158 | // |
---|
1159 | return pTabOut; |
---|
1160 | } |
---|
1161 | |
---|
1162 | |
---|
1163 | |
---|
1164 | SDMemTable* SDMath::opacity (const SDMemTable& in, Float tau, Bool doAll) const |
---|
1165 | { |
---|
1166 | |
---|
1167 | // Get header and clone output table |
---|
1168 | |
---|
1169 | SDHeader sh = in.getSDHeader(); |
---|
1170 | SDMemTable* pTabOut = new SDMemTable(in, True); |
---|
1171 | |
---|
1172 | // Get elevation data from SDMemTable and convert to degrees |
---|
1173 | |
---|
1174 | const Table& tab = in.table(); |
---|
1175 | ROScalarColumn<Float> elev(tab, "ELEVATION"); |
---|
1176 | Vector<Float> zDist = elev.getColumn(); |
---|
1177 | zDist = Float(C::pi_2) - zDist; |
---|
1178 | |
---|
1179 | // Generate correction factor |
---|
1180 | |
---|
1181 | const uInt nRow = in.nRow(); |
---|
1182 | Vector<Float> factor(nRow); |
---|
1183 | Vector<Float> factor2(nRow); |
---|
1184 | for (uInt i=0; i<nRow; i++) { |
---|
1185 | factor[i] = exp(tau)/cos(zDist[i]); |
---|
1186 | } |
---|
1187 | |
---|
1188 | // Correct |
---|
1189 | |
---|
1190 | correctFromVector (pTabOut, in, doAll, factor); |
---|
1191 | // |
---|
1192 | return pTabOut; |
---|
1193 | } |
---|
1194 | |
---|
1195 | |
---|
1196 | |
---|
1197 | |
---|
1198 | // 'private' functions |
---|
1199 | |
---|
1200 | void SDMath::fillSDC(SDContainer& sc, |
---|
1201 | const Array<Bool>& mask, |
---|
1202 | const Array<Float>& data, |
---|
1203 | const Array<Float>& tSys, |
---|
1204 | Int scanID, Double timeStamp, |
---|
1205 | Double interval, const String& sourceName, |
---|
1206 | const Vector<uInt>& freqID) const |
---|
1207 | { |
---|
1208 | // Data and mask |
---|
1209 | |
---|
1210 | putDataInSDC(sc, data, mask); |
---|
1211 | |
---|
1212 | // TSys |
---|
1213 | |
---|
1214 | sc.putTsys(tSys); |
---|
1215 | |
---|
1216 | // Time things |
---|
1217 | |
---|
1218 | sc.timestamp = timeStamp; |
---|
1219 | sc.interval = interval; |
---|
1220 | sc.scanid = scanID; |
---|
1221 | // |
---|
1222 | sc.sourcename = sourceName; |
---|
1223 | sc.putFreqMap(freqID); |
---|
1224 | } |
---|
1225 | |
---|
1226 | void SDMath::normalize(MaskedArray<Float>& sum, |
---|
1227 | const Array<Float>& sumSq, |
---|
1228 | const Array<Float>& nPts, |
---|
1229 | WeightType wtType, Int axis, |
---|
1230 | Int nAxesSub) const |
---|
1231 | { |
---|
1232 | IPosition pos2(nAxesSub,0); |
---|
1233 | // |
---|
1234 | if (wtType==NONE) { |
---|
1235 | |
---|
1236 | // We just average by the number of points accumulated. |
---|
1237 | // We need to make a MA out of nPts so that no divide by |
---|
1238 | // zeros occur |
---|
1239 | |
---|
1240 | MaskedArray<Float> t(nPts, (nPts>Float(0.0))); |
---|
1241 | sum /= t; |
---|
1242 | } else if (wtType==VAR) { |
---|
1243 | |
---|
1244 | // Normalize each spectrum by sum(1/var) where the variance |
---|
1245 | // is worked out for each spectrum |
---|
1246 | |
---|
1247 | Array<Float>& data = sum.getRWArray(); |
---|
1248 | VectorIterator<Float> itData(data, axis); |
---|
1249 | while (!itData.pastEnd()) { |
---|
1250 | pos2 = itData.pos().getFirst(nAxesSub); |
---|
1251 | itData.vector() /= sumSq(pos2); |
---|
1252 | itData.next(); |
---|
1253 | } |
---|
1254 | } else if (wtType==TSYS) { |
---|
1255 | } |
---|
1256 | } |
---|
1257 | |
---|
1258 | |
---|
1259 | void SDMath::accumulate(Double& timeSum, Double& intSum, Int& nAccum, |
---|
1260 | MaskedArray<Float>& sum, Array<Float>& sumSq, |
---|
1261 | Array<Float>& nPts, Array<Float>& tSysSum, |
---|
1262 | const Array<Float>& tSys, const Array<Float>& nInc, |
---|
1263 | const Vector<Bool>& mask, Double time, Double interval, |
---|
1264 | const Block<CountedPtr<SDMemTable> >& in, |
---|
1265 | uInt iTab, uInt iRow, uInt axis, |
---|
1266 | uInt nAxesSub, Bool useMask, |
---|
1267 | WeightType wtType) const |
---|
1268 | { |
---|
1269 | |
---|
1270 | // Get data |
---|
1271 | |
---|
1272 | MaskedArray<Float> dataIn(in[iTab]->rowAsMaskedArray(iRow)); |
---|
1273 | Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference |
---|
1274 | const Array<Bool>& maskIn = dataIn.getMask(); // RO reference |
---|
1275 | // |
---|
1276 | if (wtType==NONE) { |
---|
1277 | const MaskedArray<Float> n(nInc,dataIn.getMask()); |
---|
1278 | nPts += n; // Only accumulates where mask==T |
---|
1279 | } else if (wtType==VAR) { |
---|
1280 | |
---|
1281 | // We are going to average the data, weighted by the noise for each pol, beam and IF. |
---|
1282 | // So therefore we need to iterate through by spectrum (axis 3) |
---|
1283 | |
---|
1284 | VectorIterator<Float> itData(valuesIn, axis); |
---|
1285 | ReadOnlyVectorIterator<Bool> itMask(maskIn, axis); |
---|
1286 | Float fac = 1.0; |
---|
1287 | IPosition pos(nAxesSub,0); |
---|
1288 | // |
---|
1289 | while (!itData.pastEnd()) { |
---|
1290 | |
---|
1291 | // Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor |
---|
1292 | |
---|
1293 | if (useMask) { |
---|
1294 | MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector()); |
---|
1295 | fac = 1.0/variance(tmp); |
---|
1296 | } else { |
---|
1297 | MaskedArray<Float> tmp(itData.vector(),itMask.vector()); |
---|
1298 | fac = 1.0/variance(tmp); |
---|
1299 | } |
---|
1300 | |
---|
1301 | // Scale data |
---|
1302 | |
---|
1303 | itData.vector() *= fac; // Writes back into 'dataIn' |
---|
1304 | // |
---|
1305 | // Accumulate variance per if/pol/beam averaged over spectrum |
---|
1306 | // This method to get pos2 from itData.pos() is only valid |
---|
1307 | // because the spectral axis is the last one (so we can just |
---|
1308 | // copy the first nAXesSub positions out) |
---|
1309 | |
---|
1310 | pos = itData.pos().getFirst(nAxesSub); |
---|
1311 | sumSq(pos) += fac; |
---|
1312 | // |
---|
1313 | itData.next(); |
---|
1314 | itMask.next(); |
---|
1315 | } |
---|
1316 | } else if (wtType==TSYS) { |
---|
1317 | } |
---|
1318 | |
---|
1319 | // Accumulate sum of (possibly scaled) data |
---|
1320 | |
---|
1321 | sum += dataIn; |
---|
1322 | |
---|
1323 | // Accumulate Tsys, time, and interval |
---|
1324 | |
---|
1325 | tSysSum += tSys; |
---|
1326 | timeSum += time; |
---|
1327 | intSum += interval; |
---|
1328 | nAccum += 1; |
---|
1329 | } |
---|
1330 | |
---|
1331 | |
---|
1332 | |
---|
1333 | |
---|
1334 | void SDMath::getCursorLocation(IPosition& start, IPosition& end, |
---|
1335 | const SDMemTable& in) const |
---|
1336 | { |
---|
1337 | const uInt nDim = 4; |
---|
1338 | const uInt i = in.getBeam(); |
---|
1339 | const uInt j = in.getIF(); |
---|
1340 | const uInt k = in.getPol(); |
---|
1341 | const uInt n = in.nChan(); |
---|
1342 | // |
---|
1343 | start.resize(nDim); |
---|
1344 | start(0) = i; |
---|
1345 | start(1) = j; |
---|
1346 | start(2) = k; |
---|
1347 | start(3) = 0; |
---|
1348 | // |
---|
1349 | end.resize(nDim); |
---|
1350 | end(0) = i; |
---|
1351 | end(1) = j; |
---|
1352 | end(2) = k; |
---|
1353 | end(3) = n-1; |
---|
1354 | } |
---|
1355 | |
---|
1356 | |
---|
1357 | void SDMath::convertWeightString(WeightType& wtType, const String& weightStr) const |
---|
1358 | { |
---|
1359 | String tStr(weightStr); |
---|
1360 | tStr.upcase(); |
---|
1361 | if (tStr.contains(String("NONE"))) { |
---|
1362 | wtType = NONE; |
---|
1363 | } else if (tStr.contains(String("VAR"))) { |
---|
1364 | wtType = VAR; |
---|
1365 | } else if (tStr.contains(String("TSYS"))) { |
---|
1366 | wtType = TSYS; |
---|
1367 | throw(AipsError("T_sys weighting not yet implemented")); |
---|
1368 | } else { |
---|
1369 | throw(AipsError("Unrecognized weighting type")); |
---|
1370 | } |
---|
1371 | } |
---|
1372 | |
---|
1373 | void SDMath::convertInterpString(Int& type, const String& interp) const |
---|
1374 | { |
---|
1375 | String tStr(interp); |
---|
1376 | tStr.upcase(); |
---|
1377 | if (tStr.contains(String("NEAR"))) { |
---|
1378 | type = InterpolateArray1D<Float,Float>::nearestNeighbour; |
---|
1379 | } else if (tStr.contains(String("LIN"))) { |
---|
1380 | type = InterpolateArray1D<Float,Float>::linear; |
---|
1381 | } else if (tStr.contains(String("CUB"))) { |
---|
1382 | type = InterpolateArray1D<Float,Float>::cubic; |
---|
1383 | } else if (tStr.contains(String("SPL"))) { |
---|
1384 | type = InterpolateArray1D<Float,Float>::spline; |
---|
1385 | } else { |
---|
1386 | throw(AipsError("Unrecognized interpolation type")); |
---|
1387 | } |
---|
1388 | } |
---|
1389 | |
---|
1390 | void SDMath::putDataInSDC(SDContainer& sc, const Array<Float>& data, |
---|
1391 | const Array<Bool>& mask) const |
---|
1392 | { |
---|
1393 | sc.putSpectrum(data); |
---|
1394 | // |
---|
1395 | Array<uChar> outflags(data.shape()); |
---|
1396 | convertArray(outflags,!mask); |
---|
1397 | sc.putFlags(outflags); |
---|
1398 | } |
---|
1399 | |
---|
1400 | Table SDMath::readAsciiFile (const String& fileName) const |
---|
1401 | { |
---|
1402 | String formatString; |
---|
1403 | Table tbl = readAsciiTable (formatString, Table::Memory, fileName, "", "", False); |
---|
1404 | return tbl; |
---|
1405 | } |
---|
1406 | |
---|
1407 | |
---|
1408 | |
---|
1409 | void SDMath::correctFromAsciiTable(SDMemTable* pTabOut, |
---|
1410 | const SDMemTable& in, const String& fileName, |
---|
1411 | const String& col0, const String& col1, |
---|
1412 | const String& methodStr, Bool doAll, |
---|
1413 | const Vector<Float>& xOut) const |
---|
1414 | { |
---|
1415 | |
---|
1416 | // Read gain-elevation ascii file data into a Table. |
---|
1417 | |
---|
1418 | Table geTable = readAsciiFile (fileName); |
---|
1419 | // |
---|
1420 | correctFromTable (pTabOut, in, geTable, col0, col1, methodStr, doAll, xOut); |
---|
1421 | } |
---|
1422 | |
---|
1423 | void SDMath::correctFromTable(SDMemTable* pTabOut, const SDMemTable& in, |
---|
1424 | const Table& tTable, const String& col0, |
---|
1425 | const String& col1, |
---|
1426 | const String& methodStr, Bool doAll, |
---|
1427 | const Vector<Float>& xOut) const |
---|
1428 | { |
---|
1429 | |
---|
1430 | // Get data from Table |
---|
1431 | |
---|
1432 | ROScalarColumn<Float> geElCol(tTable, col0); |
---|
1433 | ROScalarColumn<Float> geFacCol(tTable, col1); |
---|
1434 | Vector<Float> xIn = geElCol.getColumn(); |
---|
1435 | Vector<Float> yIn = geFacCol.getColumn(); |
---|
1436 | Vector<Bool> maskIn(xIn.nelements(),True); |
---|
1437 | |
---|
1438 | // Interpolate (and extrapolate) with desired method |
---|
1439 | |
---|
1440 | Int method = 0; |
---|
1441 | convertInterpString(method, methodStr); |
---|
1442 | // |
---|
1443 | Vector<Float> yOut; |
---|
1444 | Vector<Bool> maskOut; |
---|
1445 | InterpolateArray1D<Float,Float>::interpolate(yOut, maskOut, xOut, |
---|
1446 | xIn, yIn, maskIn, method, |
---|
1447 | True, True); |
---|
1448 | // Apply |
---|
1449 | |
---|
1450 | correctFromVector (pTabOut, in, doAll, yOut); |
---|
1451 | } |
---|
1452 | |
---|
1453 | |
---|
1454 | void SDMath::correctFromVector (SDMemTable* pTabOut, const SDMemTable& in, |
---|
1455 | Bool doAll, const Vector<Float>& factor) const |
---|
1456 | { |
---|
1457 | // For operations only on specified cursor location |
---|
1458 | |
---|
1459 | IPosition start, end; |
---|
1460 | getCursorLocation(start, end, in); |
---|
1461 | |
---|
1462 | // Loop over rows and interpolate correction factor |
---|
1463 | |
---|
1464 | const uInt axis = asap::ChanAxis; |
---|
1465 | for (uInt i=0; i < in.nRow(); ++i) { |
---|
1466 | |
---|
1467 | // Get data |
---|
1468 | |
---|
1469 | MaskedArray<Float> dataIn(in.rowAsMaskedArray(i)); |
---|
1470 | Array<Float>& valuesIn = dataIn.getRWArray(); |
---|
1471 | const Array<Bool>& maskIn = dataIn.getMask(); |
---|
1472 | |
---|
1473 | // Apply factor |
---|
1474 | |
---|
1475 | if (doAll) { |
---|
1476 | VectorIterator<Float> itValues(valuesIn, asap::ChanAxis); |
---|
1477 | while (!itValues.pastEnd()) { |
---|
1478 | itValues.vector() *= factor(i); |
---|
1479 | itValues.next(); |
---|
1480 | } |
---|
1481 | } else { |
---|
1482 | Array<Float> valuesIn2 = valuesIn(start,end); |
---|
1483 | valuesIn2 *= factor(i); |
---|
1484 | valuesIn(start,end) = valuesIn2; |
---|
1485 | } |
---|
1486 | |
---|
1487 | // Write out |
---|
1488 | |
---|
1489 | SDContainer sc = in.getSDContainer(i); |
---|
1490 | putDataInSDC(sc, valuesIn, maskIn); |
---|
1491 | // |
---|
1492 | pTabOut->putSDContainer(sc); |
---|
1493 | } |
---|
1494 | } |
---|
1495 | |
---|
1496 | |
---|