[2] | 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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[125] | 5 | //# ATNF |
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[2] | 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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[38] | 31 | #include <vector> |
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| 32 | |
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[81] | 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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[130] | 37 | #include <casa/Arrays/ArrayIter.h> |
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| 38 | #include <casa/Arrays/VectorIter.h> |
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[81] | 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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[130] | 44 | #include <casa/Exceptions.h> |
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[2] | 45 | |
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[81] | 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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[2] | 49 | |
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[130] | 50 | #include <lattices/Lattices/LatticeUtilities.h> |
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| 51 | #include <lattices/Lattices/RebinLattice.h> |
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[81] | 52 | #include <coordinates/Coordinates/SpectralCoordinate.h> |
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[130] | 53 | #include <coordinates/Coordinates/CoordinateSystem.h> |
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| 54 | #include <coordinates/Coordinates/CoordinateUtil.h> |
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[38] | 55 | |
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| 56 | #include "MathUtils.h" |
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[2] | 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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[125] | 62 | using namespace casa; |
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[83] | 63 | using namespace asap; |
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| 64 | //using namespace asap::SDMath; |
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[2] | 65 | |
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[144] | 66 | CountedPtr<SDMemTable> SDMath::average (const Block<CountedPtr<SDMemTable> >& in, |
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| 67 | const Vector<Bool>& mask, bool scanAv, |
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| 68 | const std::string& weightStr) |
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[130] | 69 | // |
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[144] | 70 | // Weighted averaging of spectra from one or more Tables. |
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[130] | 71 | // |
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| 72 | { |
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[144] | 73 | weightType wtType = NONE; |
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| 74 | String tStr(weightStr); |
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| 75 | tStr.upcase(); |
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| 76 | if (tStr.contains(String("NONE"))) { |
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| 77 | wtType = NONE; |
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| 78 | } else if (tStr.contains(String("VAR"))) { |
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| 79 | wtType = VAR; |
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| 80 | } else if (tStr.contains(String("TSYS"))) { |
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| 81 | wtType = TSYS; |
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| 82 | throw (AipsError("T_sys weighting not yet implemented")); |
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| 83 | } else { |
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| 84 | throw (AipsError("Unrecognized weighting type")); |
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| 85 | } |
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[2] | 86 | |
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[144] | 87 | // Create output Table by cloning from the first table |
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[2] | 88 | |
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[144] | 89 | SDMemTable* pTabOut = new SDMemTable(*in[0],True); |
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[130] | 90 | |
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[144] | 91 | // Setup |
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[130] | 92 | |
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[144] | 93 | const uInt axis = 3; // Spectral axis |
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| 94 | IPosition shp = in[0]->rowAsMaskedArray(0).shape(); // Must not change |
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| 95 | Array<Float> arr(shp); |
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| 96 | Array<Bool> barr(shp); |
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| 97 | const Bool useMask = (mask.nelements() == shp(axis)); |
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[130] | 98 | |
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[144] | 99 | // Columns from Tables |
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[130] | 100 | |
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[144] | 101 | ROArrayColumn<Float> tSysCol; |
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| 102 | ROScalarColumn<Double> mjdCol; |
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| 103 | ROScalarColumn<String> srcNameCol; |
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| 104 | ROScalarColumn<Double> intCol; |
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| 105 | ROArrayColumn<uInt> fqIDCol; |
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[130] | 106 | |
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[144] | 107 | // Create accumulation MaskedArray. We accumulate for each channel,if,pol,beam |
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| 108 | // Note that the mask of the accumulation array will ALWAYS remain ALL True. |
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| 109 | // The MA is only used so that when data which is masked Bad is added to it, |
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| 110 | // that data does not contribute. |
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| 111 | |
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| 112 | Array<Float> zero(shp); |
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| 113 | zero=0.0; |
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| 114 | Array<Bool> good(shp); |
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| 115 | good = True; |
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| 116 | MaskedArray<Float> sum(zero,good); |
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| 117 | |
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| 118 | // Counter arrays |
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| 119 | |
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| 120 | Array<Float> nPts(shp); // Number of points |
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| 121 | nPts = 0.0; |
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| 122 | Array<Float> nInc(shp); // Increment |
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| 123 | nInc = 1.0; |
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| 124 | |
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| 125 | // Create accumulation Array for variance. We accumulate for |
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| 126 | // each if,pol,beam, but average over channel. So we need |
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| 127 | // a shape with one less axis dropping channels. |
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| 128 | |
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| 129 | const uInt nAxesSub = shp.nelements() - 1; |
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| 130 | IPosition shp2(nAxesSub); |
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| 131 | for (uInt i=0,j=0; i<(nAxesSub+1); i++) { |
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| 132 | if (i!=axis) { |
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| 133 | shp2(j) = shp(i); |
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| 134 | j++; |
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| 135 | } |
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[2] | 136 | } |
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[144] | 137 | Array<Float> sumSq(shp2); |
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| 138 | sumSq = 0.0; |
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| 139 | IPosition pos2(nAxesSub,0); // For indexing |
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[130] | 140 | |
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[144] | 141 | // Time-related accumulators |
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[130] | 142 | |
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[144] | 143 | Double time; |
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| 144 | Double timeSum = 0.0; |
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| 145 | Double intSum = 0.0; |
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| 146 | Double interval = 0.0; |
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[130] | 147 | |
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[144] | 148 | // To get the right shape for the Tsys accumulator we need to |
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| 149 | // access a column from the first table. The shape of this |
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| 150 | // array must not change |
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[130] | 151 | |
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[144] | 152 | Array<Float> tSysSum; |
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| 153 | { |
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| 154 | const Table& tabIn = in[0]->table(); |
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| 155 | tSysCol.attach(tabIn,"TSYS"); |
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| 156 | tSysSum.resize(tSysCol.shape(0)); |
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| 157 | } |
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| 158 | tSysSum =0.0; |
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| 159 | Array<Float> tSys; |
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| 160 | |
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| 161 | // Scan and row tracking |
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| 162 | |
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| 163 | Int oldScanID = 0; |
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| 164 | Int outScanID = 0; |
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| 165 | Int scanID = 0; |
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| 166 | Int rowStart = 0; |
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| 167 | Int nAccum = 0; |
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| 168 | Int tableStart = 0; |
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| 169 | |
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| 170 | // Source and FreqID |
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| 171 | |
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| 172 | String sourceName, oldSourceName, sourceNameStart; |
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| 173 | Vector<uInt> freqID, freqIDStart, oldFreqID; |
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| 174 | |
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| 175 | // Loop over tables |
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| 176 | |
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| 177 | Float fac = 1.0; |
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| 178 | const uInt nTables = in.nelements(); |
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| 179 | for (uInt iTab=0; iTab<nTables; iTab++) { |
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| 180 | |
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| 181 | // Attach columns to Table |
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| 182 | |
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| 183 | const Table& tabIn = in[iTab]->table(); |
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| 184 | tSysCol.attach(tabIn, "TSYS"); |
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| 185 | mjdCol.attach(tabIn, "TIME"); |
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| 186 | srcNameCol.attach(tabIn, "SRCNAME"); |
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| 187 | intCol.attach(tabIn, "INTERVAL"); |
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| 188 | fqIDCol.attach(tabIn, "FREQID"); |
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| 189 | |
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| 190 | // Loop over rows in Table |
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| 191 | |
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| 192 | const uInt nRows = in[iTab]->nRow(); |
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| 193 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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| 194 | |
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| 195 | // Check conformance |
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| 196 | |
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| 197 | IPosition shp2 = in[iTab]->rowAsMaskedArray(iRow).shape(); |
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| 198 | if (!shp.isEqual(shp2)) { |
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| 199 | throw (AipsError("Shapes for all rows must be the same")); |
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| 200 | } |
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| 201 | |
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| 202 | // If we are not doing scan averages, make checks for source and |
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| 203 | // frequency setup and warn if averaging across them |
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| 204 | |
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| 205 | // Get copy of Scan Container for this row |
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| 206 | |
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| 207 | SDContainer sc = in[iTab]->getSDContainer(iRow); |
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| 208 | scanID = sc.scanid; |
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| 209 | |
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| 210 | // Get quantities from columns |
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| 211 | |
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| 212 | srcNameCol.getScalar(iRow, sourceName); |
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| 213 | mjdCol.get(iRow, time); |
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| 214 | tSysCol.get(iRow, tSys); |
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| 215 | intCol.get(iRow, interval); |
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| 216 | fqIDCol.get(iRow, freqID); |
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| 217 | |
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| 218 | // Initialize first source and freqID |
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| 219 | |
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| 220 | if (iRow==0 && iTab==0) { |
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| 221 | sourceNameStart = sourceName; |
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| 222 | freqIDStart = freqID; |
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| 223 | } |
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| 224 | |
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| 225 | // If we are doing scan averages, see if we are at the end of an |
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| 226 | // accumulation period (scan). We must check soutce names too, |
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| 227 | // since we might have two tables with one scan each but different |
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| 228 | // source names; we shouldn't average different sources together |
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| 229 | |
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| 230 | if (scanAv && ( (scanID != oldScanID) || |
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| 231 | (iRow==0 && iTab>0 && sourceName!=oldSourceName))) { |
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| 232 | |
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| 233 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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| 234 | |
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| 235 | normalize (sum, sumSq, nPts, wtType, axis, nAxesSub); |
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| 236 | |
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| 237 | // Fill scan container. The source and freqID come from the |
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| 238 | // first row of the first table that went into this average ( |
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| 239 | // should be the same for all rows in the scan average) |
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| 240 | |
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| 241 | Float nR(nAccum); |
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| 242 | fillSDC (sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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| 243 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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| 244 | |
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| 245 | // Write container out to Table |
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| 246 | |
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| 247 | pTabOut->putSDContainer(sc); |
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| 248 | |
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| 249 | // Reset accumulators |
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| 250 | |
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| 251 | sum = 0.0; |
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| 252 | sumSq = 0.0; |
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| 253 | nAccum = 0; |
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| 254 | // |
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| 255 | tSysSum =0.0; |
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| 256 | timeSum = 0.0; |
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| 257 | intSum = 0.0; |
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| 258 | |
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| 259 | // Increment |
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| 260 | |
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| 261 | rowStart = iRow; // First row for next accumulation |
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| 262 | tableStart = iTab; // First table for next accumulation |
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| 263 | sourceNameStart = sourceName; // First source name for next accumulation |
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| 264 | freqIDStart = freqID; // First FreqID for next accumulation |
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| 265 | // |
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| 266 | oldScanID = scanID; |
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| 267 | outScanID += 1; // Scan ID for next accumulation period |
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| 268 | } |
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| 269 | |
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[146] | 270 | // Accumulate |
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[144] | 271 | |
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[146] | 272 | accumulate (timeSum, intSum, nAccum, sum, sumSq, nPts, tSysSum, |
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| 273 | tSys, nInc, mask, time, interval, in, iTab, iRow, axis, |
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| 274 | nAxesSub, useMask, wtType); |
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[144] | 275 | // |
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| 276 | oldSourceName = sourceName; |
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| 277 | oldFreqID = freqID; |
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| 278 | } |
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| 279 | } |
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| 280 | |
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| 281 | // OK at this point we have accumulation data which is either |
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| 282 | // - accumulated from all tables into one row |
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| 283 | // or |
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| 284 | // - accumulated from the last scan average |
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| 285 | // |
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| 286 | // Normalize data in 'sum' accumulation array according to weighting scheme |
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| 287 | |
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| 288 | normalize (sum, sumSq, nPts, wtType, axis, nAxesSub); |
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| 289 | |
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| 290 | // Create and fill container. The container we clone will be from |
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| 291 | // the last Table and the first row that went into the current |
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| 292 | // accumulation. It probably doesn't matter that much really... |
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| 293 | |
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| 294 | Float nR(nAccum); |
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| 295 | SDContainer sc = in[tableStart]->getSDContainer(rowStart); |
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| 296 | fillSDC (sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID, |
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| 297 | timeSum/nR, intSum, sourceNameStart, freqIDStart); |
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| 298 | // |
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| 299 | pTabOut->putSDContainer(sc); |
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| 300 | /* |
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| 301 | cout << endl; |
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| 302 | cout << "Last accumulation for output scan ID " << outScanID << endl; |
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| 303 | cout << " The first row in this accumulation is " << rowStart << endl; |
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| 304 | cout << " The number of rows accumulated is " << nAccum << endl; |
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| 305 | cout << " The first table in this accumulation is " << tableStart << endl; |
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| 306 | cout << " The first source in this accumulation is " << sourceNameStart << endl; |
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| 307 | cout << " The first freqID in this accumulation is " << freqIDStart << endl; |
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| 308 | cout << " Average time stamp = " << timeSum/nR << endl; |
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| 309 | cout << " Integrated time = " << intSum << endl; |
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| 310 | */ |
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| 311 | return CountedPtr<SDMemTable>(pTabOut); |
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[2] | 312 | } |
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[9] | 313 | |
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[144] | 314 | |
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| 315 | |
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[85] | 316 | CountedPtr<SDMemTable> |
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| 317 | SDMath::quotient(const CountedPtr<SDMemTable>& on, |
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[130] | 318 | const CountedPtr<SDMemTable>& off) |
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| 319 | // |
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| 320 | // Compute quotient spectrum |
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| 321 | // |
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| 322 | { |
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| 323 | const uInt nRows = on->nRow(); |
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| 324 | if (off->nRow() != nRows) { |
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| 325 | throw (AipsError("Input Scan Tables must have the same number of rows")); |
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| 326 | } |
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[85] | 327 | |
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[130] | 328 | // Input Tables and columns |
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| 329 | |
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[9] | 330 | Table ton = on->table(); |
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| 331 | Table toff = off->table(); |
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[85] | 332 | ROArrayColumn<Float> tsys(toff, "TSYS"); |
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[9] | 333 | ROScalarColumn<Double> mjd(ton, "TIME"); |
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[15] | 334 | ROScalarColumn<Double> integr(ton, "INTERVAL"); |
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[9] | 335 | ROScalarColumn<String> srcn(ton, "SRCNAME"); |
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[38] | 336 | ROArrayColumn<uInt> freqidc(ton, "FREQID"); |
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| 337 | |
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[130] | 338 | // Output Table cloned from input |
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[85] | 339 | |
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[15] | 340 | SDMemTable* sdmt = new SDMemTable(*on, True); |
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[130] | 341 | |
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| 342 | // Loop over rows |
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| 343 | |
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| 344 | for (uInt i=0; i<nRows; i++) { |
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| 345 | MaskedArray<Float> mon(on->rowAsMaskedArray(i)); |
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| 346 | MaskedArray<Float> moff(off->rowAsMaskedArray(i)); |
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| 347 | IPosition ipon = mon.shape(); |
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| 348 | IPosition ipoff = moff.shape(); |
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| 349 | // |
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| 350 | Array<Float> tsarr; |
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| 351 | tsys.get(i, tsarr); |
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| 352 | if (ipon != ipoff && ipon != tsarr.shape()) { |
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| 353 | throw(AipsError("on/off not conformant")); |
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| 354 | } |
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| 355 | |
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| 356 | // Compute quotient |
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| 357 | |
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| 358 | MaskedArray<Float> tmp = (mon-moff); |
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| 359 | Array<Float> out(tmp.getArray()); |
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| 360 | out /= moff; |
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| 361 | out *= tsarr; |
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| 362 | Array<Bool> outflagsb = !(mon.getMask() && moff.getMask()); |
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| 363 | Array<uChar> outflags(outflagsb.shape()); |
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| 364 | convertArray(outflags,outflagsb); |
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| 365 | |
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| 366 | // Fill container for this row |
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| 367 | |
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| 368 | SDContainer sc = on->getSDContainer(); |
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| 369 | sc.putTsys(tsarr); |
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| 370 | sc.scanid = 0; |
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| 371 | sc.putSpectrum(out); |
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| 372 | sc.putFlags(outflags); |
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| 373 | |
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| 374 | // Put new row in output Table |
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| 375 | |
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| 376 | sdmt->putSDContainer(sc); |
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| 377 | } |
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| 378 | // |
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[9] | 379 | return CountedPtr<SDMemTable>(sdmt); |
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| 380 | } |
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[48] | 381 | |
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[152] | 382 | void SDMath::multiplyInSitu(SDMemTable* pIn, Float factor, Bool doAll) |
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[146] | 383 | { |
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[152] | 384 | const uInt what = 0; |
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| 385 | SDMemTable* pOut = localOperate (*pIn, factor, doAll, what); |
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[146] | 386 | *pIn = *pOut; |
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| 387 | delete pOut; |
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| 388 | } |
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| 389 | |
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| 390 | |
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[85] | 391 | CountedPtr<SDMemTable> |
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[152] | 392 | SDMath::multiply(const CountedPtr<SDMemTable>& in, Float factor, Bool doAll) |
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[130] | 393 | { |
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[152] | 394 | const uInt what = 0; |
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| 395 | return CountedPtr<SDMemTable>(localOperate (*in, factor, doAll, what)); |
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[15] | 396 | } |
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[48] | 397 | |
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[152] | 398 | |
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| 399 | void SDMath::addInSitu (SDMemTable* pIn, Float offset, Bool doAll) |
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| 400 | { |
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| 401 | const uInt what = 1; |
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| 402 | SDMemTable* pOut = localOperate (*pIn, offset, doAll, what); |
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| 403 | *pIn = *pOut; |
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| 404 | delete pOut; |
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| 405 | } |
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| 406 | |
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| 407 | |
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[107] | 408 | CountedPtr<SDMemTable> |
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[152] | 409 | SDMath::add(const CountedPtr<SDMemTable>& in, Float offset, Bool doAll) |
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[130] | 410 | { |
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[152] | 411 | const uInt what = 1; |
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| 412 | return CountedPtr<SDMemTable>(localOperate(*in, offset, doAll, what)); |
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[107] | 413 | } |
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| 414 | |
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| 415 | |
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[130] | 416 | CountedPtr<SDMemTable> |
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| 417 | SDMath::hanning(const CountedPtr<SDMemTable>& in) |
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| 418 | // |
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| 419 | // Hanning smooth each row |
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| 420 | // Should Tsys be smoothed ? |
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| 421 | // |
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| 422 | { |
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| 423 | SDMemTable* sdmt = new SDMemTable(*in,True); |
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[107] | 424 | |
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[130] | 425 | // Loop over rows in Table |
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[48] | 426 | |
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[130] | 427 | for (uInt ri=0; ri < in->nRow(); ++ri) { |
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[38] | 428 | |
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[130] | 429 | // Get data |
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[125] | 430 | |
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[130] | 431 | const MaskedArray<Float>& marr(in->rowAsMaskedArray(ri)); |
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[85] | 432 | Array<Float> arr = marr.getArray(); |
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| 433 | Array<Bool> barr = marr.getMask(); |
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[130] | 434 | |
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| 435 | // Smooth along the channels axis |
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| 436 | |
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| 437 | uInt axis = 3; |
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| 438 | VectorIterator<Float> itData(arr, axis); |
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| 439 | VectorIterator<Bool> itMask(barr, axis); |
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| 440 | Vector<Float> outv; |
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| 441 | Vector<Bool> outm; |
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| 442 | while (!itData.pastEnd()) { |
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| 443 | mathutil::hanning(outv, outm, itData.vector(), itMask.vector()); |
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| 444 | itData.vector() = outv; |
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| 445 | itMask.vector() = outm; |
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| 446 | // |
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| 447 | itData.next(); |
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| 448 | itMask.next(); |
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[38] | 449 | } |
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[130] | 450 | |
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| 451 | // Create and put back |
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| 452 | |
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[85] | 453 | Array<uChar> outflags(barr.shape()); |
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| 454 | convertArray(outflags,!barr); |
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| 455 | SDContainer sc = in->getSDContainer(ri); |
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| 456 | sc.putSpectrum(arr); |
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| 457 | sc.putFlags(outflags); |
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| 458 | sdmt->putSDContainer(sc); |
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[38] | 459 | } |
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| 460 | return CountedPtr<SDMemTable>(sdmt); |
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| 461 | } |
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| 462 | |
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[85] | 463 | |
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[130] | 464 | |
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| 465 | |
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[85] | 466 | CountedPtr<SDMemTable> |
---|
| 467 | SDMath::averagePol(const CountedPtr<SDMemTable>& in, |
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[130] | 468 | const Vector<Bool>& mask) |
---|
| 469 | { |
---|
| 470 | const uInt nRows = in->nRow(); |
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| 471 | const uInt axis = 3; // Spectrum |
---|
| 472 | const IPosition axes(2, 2, 3); // pol-channel plane |
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| 473 | |
---|
| 474 | // Create output Table |
---|
| 475 | |
---|
| 476 | SDMemTable* sdmt = new SDMemTable(*in, True); |
---|
| 477 | |
---|
| 478 | // Loop over rows |
---|
| 479 | |
---|
| 480 | for (uInt iRow=0; iRow<nRows; iRow++) { |
---|
| 481 | |
---|
| 482 | // Get data for this row |
---|
| 483 | |
---|
| 484 | MaskedArray<Float> marr(in->rowAsMaskedArray(iRow)); |
---|
| 485 | Array<Float>& arr = marr.getRWArray(); |
---|
| 486 | const Array<Bool>& barr = marr.getMask(); |
---|
| 487 | // |
---|
| 488 | IPosition shp = marr.shape(); |
---|
| 489 | const Bool useMask = (mask.nelements() == shp(axis)); |
---|
| 490 | const uInt nChan = shp(axis); |
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| 491 | |
---|
| 492 | // Make iterators to iterate by pol-channel planes |
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| 493 | |
---|
| 494 | ArrayIterator<Float> itDataPlane(arr, axes); |
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| 495 | ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes); |
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| 496 | |
---|
| 497 | // Accumulations |
---|
| 498 | |
---|
| 499 | Float fac = 0.0; |
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| 500 | Vector<Float> vecSum(nChan,0.0); |
---|
| 501 | |
---|
| 502 | // Iterate by plane |
---|
| 503 | |
---|
| 504 | while (!itDataPlane.pastEnd()) { |
---|
| 505 | |
---|
| 506 | // Iterate through pol-channel plane by spectrum |
---|
| 507 | |
---|
| 508 | Vector<Float> t1(nChan); t1 = 0.0; |
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| 509 | Vector<Bool> t2(nChan); t2 = True; |
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| 510 | MaskedArray<Float> vecSum(t1,t2); |
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| 511 | Float varSum = 0.0; |
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| 512 | { |
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| 513 | ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1); |
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| 514 | ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1); |
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| 515 | while (!itDataVec.pastEnd()) { |
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| 516 | |
---|
| 517 | // Create MA of data & mask (optionally including OTF mask) and get variance |
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| 518 | |
---|
| 519 | if (useMask) { |
---|
| 520 | const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector()); |
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| 521 | fac = 1.0 / variance(spec); |
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| 522 | } else { |
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| 523 | const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector()); |
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| 524 | fac = 1.0 / variance(spec); |
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| 525 | } |
---|
| 526 | |
---|
| 527 | // Normalize spectrum (without OTF mask) and accumulate |
---|
| 528 | |
---|
| 529 | const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector()); |
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| 530 | vecSum += spec; |
---|
| 531 | varSum += fac; |
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| 532 | |
---|
| 533 | // Next |
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| 534 | |
---|
| 535 | itDataVec.next(); |
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| 536 | itMaskVec.next(); |
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| 537 | } |
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[85] | 538 | } |
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[48] | 539 | |
---|
[130] | 540 | // Normalize summed spectrum |
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[48] | 541 | |
---|
[130] | 542 | vecSum /= varSum; |
---|
[48] | 543 | |
---|
[130] | 544 | // We have formed the weighted averaged spectrum from all polarizations |
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| 545 | // for this beam and IF. Now replicate the spectrum to all polarizations |
---|
[48] | 546 | |
---|
[130] | 547 | { |
---|
| 548 | VectorIterator<Float> itDataVec(itDataPlane.array(), 1); // Writes back into 'arr' |
---|
| 549 | const Vector<Float>& vecSumData = vecSum.getArray(); // It *is* a Vector |
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| 550 | // |
---|
| 551 | while (!itDataVec.pastEnd()) { |
---|
| 552 | itDataVec.vector() = vecSumData; |
---|
| 553 | itDataVec.next(); |
---|
| 554 | } |
---|
| 555 | } |
---|
| 556 | |
---|
| 557 | // Step to next beam/IF combination |
---|
| 558 | |
---|
| 559 | itDataPlane.next(); |
---|
| 560 | itMaskPlane.next(); |
---|
| 561 | } |
---|
| 562 | |
---|
| 563 | // Generate output container and write it to output table |
---|
| 564 | |
---|
| 565 | SDContainer sc = in->getSDContainer(); |
---|
| 566 | Array<uChar> outflags(barr.shape()); |
---|
| 567 | convertArray(outflags,!barr); |
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| 568 | sc.putSpectrum(arr); |
---|
| 569 | sc.putFlags(outflags); |
---|
| 570 | sdmt->putSDContainer(sc); |
---|
| 571 | } |
---|
| 572 | // |
---|
| 573 | return CountedPtr<SDMemTable>(sdmt); |
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[48] | 574 | } |
---|
| 575 | |
---|
[130] | 576 | |
---|
[85] | 577 | CountedPtr<SDMemTable> SDMath::bin(const CountedPtr<SDMemTable>& in, |
---|
[130] | 578 | Int width) |
---|
| 579 | { |
---|
[48] | 580 | SDHeader sh = in->getSDHeader(); |
---|
[85] | 581 | SDMemTable* sdmt = new SDMemTable(*in,True); |
---|
| 582 | |
---|
[130] | 583 | // Bin up SpectralCoordinates |
---|
| 584 | |
---|
| 585 | IPosition factors(1); |
---|
| 586 | factors(0) = width; |
---|
[85] | 587 | for (uInt j=0; j<in->nCoordinates(); ++j) { |
---|
[130] | 588 | CoordinateSystem cSys; |
---|
| 589 | cSys.addCoordinate(in->getCoordinate(j)); |
---|
| 590 | CoordinateSystem cSysBin = |
---|
| 591 | CoordinateUtil::makeBinnedCoordinateSystem (factors, cSys, False); |
---|
| 592 | // |
---|
| 593 | SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0); |
---|
| 594 | sdmt->setCoordinate(sCBin, j); |
---|
[85] | 595 | } |
---|
[130] | 596 | |
---|
| 597 | // Use RebinLattice to find shape |
---|
| 598 | |
---|
| 599 | IPosition shapeIn(1,sh.nchan); |
---|
| 600 | IPosition shapeOut = RebinLattice<Float>::rebinShape (shapeIn, factors); |
---|
| 601 | sh.nchan = shapeOut(0); |
---|
[48] | 602 | sdmt->putSDHeader(sh); |
---|
[85] | 603 | |
---|
[130] | 604 | |
---|
| 605 | // Loop over rows and bin along channel axis |
---|
| 606 | |
---|
| 607 | const uInt axis = 3; |
---|
[85] | 608 | for (uInt i=0; i < in->nRow(); ++i) { |
---|
[130] | 609 | SDContainer sc = in->getSDContainer(i); |
---|
| 610 | // |
---|
| 611 | Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape |
---|
| 612 | |
---|
| 613 | // Bin up spectrum |
---|
| 614 | |
---|
[85] | 615 | MaskedArray<Float> marr(in->rowAsMaskedArray(i)); |
---|
| 616 | MaskedArray<Float> marrout; |
---|
[130] | 617 | LatticeUtilities::bin(marrout, marr, axis, width); |
---|
| 618 | |
---|
| 619 | // Put back the binned data and flags |
---|
| 620 | |
---|
[85] | 621 | IPosition ip2 = marrout.shape(); |
---|
| 622 | sc.resize(ip2); |
---|
| 623 | sc.putSpectrum(marrout.getArray()); |
---|
[130] | 624 | // |
---|
[85] | 625 | Array<uChar> outflags(ip2); |
---|
| 626 | convertArray(outflags,!(marrout.getMask())); |
---|
| 627 | sc.putFlags(outflags); |
---|
[130] | 628 | |
---|
| 629 | // Bin up Tsys. |
---|
| 630 | |
---|
| 631 | Array<Bool> allGood(tSys.shape(),True); |
---|
| 632 | MaskedArray<Float> tSysIn(tSys, allGood, True); |
---|
| 633 | // |
---|
| 634 | MaskedArray<Float> tSysOut; |
---|
| 635 | LatticeUtilities::bin(tSysOut, tSysIn, axis, width); |
---|
| 636 | sc.putTsys(tSysOut.getArray()); |
---|
[85] | 637 | sdmt->putSDContainer(sc); |
---|
| 638 | } |
---|
[48] | 639 | return CountedPtr<SDMemTable>(sdmt); |
---|
| 640 | } |
---|
[130] | 641 | |
---|
| 642 | |
---|
| 643 | |
---|
| 644 | std::vector<float> SDMath::statistic (const CountedPtr<SDMemTable>& in, |
---|
| 645 | const std::vector<bool>& mask, |
---|
| 646 | const std::string& which) |
---|
| 647 | // |
---|
| 648 | // Perhaps iteration over pol/beam/if should be in here |
---|
| 649 | // and inside the nrow iteration ? |
---|
| 650 | // |
---|
| 651 | { |
---|
| 652 | const uInt nRow = in->nRow(); |
---|
| 653 | std::vector<float> result(nRow); |
---|
| 654 | Vector<Bool> msk(mask); |
---|
| 655 | |
---|
| 656 | // Specify cursor location |
---|
| 657 | |
---|
[152] | 658 | IPosition start, end; |
---|
| 659 | getCursorLocation (start, end, *in); |
---|
[130] | 660 | |
---|
| 661 | // Loop over rows |
---|
| 662 | |
---|
| 663 | const uInt nEl = msk.nelements(); |
---|
| 664 | for (uInt ii=0; ii < in->nRow(); ++ii) { |
---|
| 665 | |
---|
| 666 | // Get row and deconstruct |
---|
| 667 | |
---|
| 668 | MaskedArray<Float> marr(in->rowAsMaskedArray(ii)); |
---|
| 669 | Array<Float> arr = marr.getArray(); |
---|
| 670 | Array<Bool> barr = marr.getMask(); |
---|
| 671 | |
---|
| 672 | // Access desired piece of data |
---|
| 673 | |
---|
| 674 | Array<Float> v((arr(start,end)).nonDegenerate()); |
---|
| 675 | Array<Bool> m((barr(start,end)).nonDegenerate()); |
---|
| 676 | |
---|
| 677 | // Apply OTF mask |
---|
| 678 | |
---|
| 679 | MaskedArray<Float> tmp; |
---|
| 680 | if (m.nelements()==nEl) { |
---|
| 681 | tmp.setData(v,m&&msk); |
---|
| 682 | } else { |
---|
| 683 | tmp.setData(v,m); |
---|
| 684 | } |
---|
| 685 | |
---|
| 686 | // Get statistic |
---|
| 687 | |
---|
[144] | 688 | result[ii] = mathutil::statistics(which, tmp); |
---|
[130] | 689 | } |
---|
| 690 | // |
---|
| 691 | return result; |
---|
| 692 | } |
---|
| 693 | |
---|
[146] | 694 | |
---|
| 695 | |
---|
| 696 | // 'private' functions |
---|
| 697 | |
---|
[144] | 698 | void SDMath::fillSDC (SDContainer& sc, |
---|
| 699 | const Array<Bool>& mask, |
---|
| 700 | const Array<Float>& data, |
---|
| 701 | const Array<Float>& tSys, |
---|
| 702 | Int scanID, Double timeStamp, |
---|
| 703 | Double interval, const String& sourceName, |
---|
| 704 | const Vector<uInt>& freqID) |
---|
| 705 | { |
---|
| 706 | sc.putSpectrum(data); |
---|
| 707 | // |
---|
| 708 | Array<uChar> outflags(mask.shape()); |
---|
| 709 | convertArray(outflags,!mask); |
---|
| 710 | sc.putFlags(outflags); |
---|
| 711 | // |
---|
| 712 | sc.putTsys(tSys); |
---|
[130] | 713 | |
---|
[144] | 714 | // Time things |
---|
| 715 | |
---|
| 716 | sc.timestamp = timeStamp; |
---|
| 717 | sc.interval = interval; |
---|
| 718 | sc.scanid = scanID; |
---|
| 719 | // |
---|
| 720 | sc.sourcename = sourceName; |
---|
| 721 | sc.putFreqMap(freqID); |
---|
| 722 | } |
---|
| 723 | |
---|
| 724 | void SDMath::normalize (MaskedArray<Float>& sum, |
---|
| 725 | const Array<Float>& sumSq, |
---|
| 726 | const Array<Float>& nPts, |
---|
| 727 | weightType wtType, Int axis, |
---|
| 728 | Int nAxesSub) |
---|
[130] | 729 | { |
---|
[144] | 730 | IPosition pos2(nAxesSub,0); |
---|
| 731 | // |
---|
| 732 | if (wtType==NONE) { |
---|
| 733 | |
---|
| 734 | // We just average by the number of points accumulated. |
---|
| 735 | // We need to make a MA out of nPts so that no divide by |
---|
| 736 | // zeros occur |
---|
| 737 | |
---|
| 738 | MaskedArray<Float> t(nPts, (nPts>Float(0.0))); |
---|
| 739 | sum /= t; |
---|
| 740 | } else if (wtType==VAR) { |
---|
| 741 | |
---|
| 742 | // Normalize each spectrum by sum(1/var) where the variance |
---|
| 743 | // is worked out for each spectrum |
---|
| 744 | |
---|
| 745 | Array<Float>& data = sum.getRWArray(); |
---|
| 746 | VectorIterator<Float> itData(data, axis); |
---|
| 747 | while (!itData.pastEnd()) { |
---|
| 748 | pos2 = itData.pos().getFirst(nAxesSub); |
---|
| 749 | itData.vector() /= sumSq(pos2); |
---|
| 750 | itData.next(); |
---|
| 751 | } |
---|
| 752 | } else if (wtType==TSYS) { |
---|
[130] | 753 | } |
---|
| 754 | } |
---|
[144] | 755 | |
---|
[146] | 756 | |
---|
| 757 | void SDMath::accumulate (Double& timeSum, Double& intSum, Int& nAccum, |
---|
| 758 | MaskedArray<Float>& sum, Array<Float>& sumSq, |
---|
| 759 | Array<Float>& nPts, Array<Float>& tSysSum, |
---|
| 760 | const Array<Float>& tSys, const Array<Float>& nInc, |
---|
| 761 | const Vector<Bool>& mask, Double time, Double interval, |
---|
| 762 | const Block<CountedPtr<SDMemTable> >& in, |
---|
| 763 | uInt iTab, uInt iRow, uInt axis, |
---|
| 764 | uInt nAxesSub, Bool useMask, |
---|
| 765 | weightType wtType) |
---|
| 766 | { |
---|
| 767 | |
---|
| 768 | // Get data |
---|
| 769 | |
---|
| 770 | MaskedArray<Float> dataIn(in[iTab]->rowAsMaskedArray(iRow)); |
---|
| 771 | Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference |
---|
| 772 | const Array<Bool>& maskIn = dataIn.getMask(); // RO reference |
---|
| 773 | // |
---|
| 774 | if (wtType==NONE) { |
---|
| 775 | const MaskedArray<Float> n(nInc,dataIn.getMask()); |
---|
| 776 | nPts += n; // Only accumulates where mask==T |
---|
| 777 | } else if (wtType==VAR) { |
---|
| 778 | |
---|
| 779 | // We are going to average the data, weighted by the noise for each pol, beam and IF. |
---|
| 780 | // So therefore we need to iterate through by spectrum (axis 3) |
---|
| 781 | |
---|
| 782 | VectorIterator<Float> itData(valuesIn, axis); |
---|
| 783 | ReadOnlyVectorIterator<Bool> itMask(maskIn, axis); |
---|
| 784 | Float fac = 1.0; |
---|
| 785 | IPosition pos(nAxesSub,0); |
---|
| 786 | // |
---|
| 787 | while (!itData.pastEnd()) { |
---|
| 788 | |
---|
| 789 | // Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor |
---|
| 790 | |
---|
| 791 | if (useMask) { |
---|
| 792 | MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector()); |
---|
| 793 | fac = 1.0/variance(tmp); |
---|
| 794 | } else { |
---|
| 795 | MaskedArray<Float> tmp(itData.vector(),itMask.vector()); |
---|
| 796 | fac = 1.0/variance(tmp); |
---|
| 797 | } |
---|
| 798 | |
---|
| 799 | // Scale data |
---|
| 800 | |
---|
| 801 | itData.vector() *= fac; // Writes back into 'dataIn' |
---|
| 802 | // |
---|
| 803 | // Accumulate variance per if/pol/beam averaged over spectrum |
---|
| 804 | // This method to get pos2 from itData.pos() is only valid |
---|
| 805 | // because the spectral axis is the last one (so we can just |
---|
| 806 | // copy the first nAXesSub positions out) |
---|
| 807 | |
---|
| 808 | pos = itData.pos().getFirst(nAxesSub); |
---|
| 809 | sumSq(pos) += fac; |
---|
| 810 | // |
---|
| 811 | itData.next(); |
---|
| 812 | itMask.next(); |
---|
| 813 | } |
---|
| 814 | } else if (wtType==TSYS) { |
---|
| 815 | } |
---|
| 816 | |
---|
| 817 | // Accumulate sum of (possibly scaled) data |
---|
| 818 | |
---|
| 819 | sum += dataIn; |
---|
| 820 | |
---|
| 821 | // Accumulate Tsys, time, and interval |
---|
| 822 | |
---|
| 823 | tSysSum += tSys; |
---|
| 824 | timeSum += time; |
---|
| 825 | intSum += interval; |
---|
| 826 | nAccum += 1; |
---|
| 827 | } |
---|
| 828 | |
---|
[152] | 829 | SDMemTable* SDMath::localOperate (const SDMemTable& in, Float val, Bool doAll, |
---|
| 830 | uInt what) |
---|
| 831 | // |
---|
| 832 | // what = 0 Multiply |
---|
| 833 | // 1 Add |
---|
[146] | 834 | { |
---|
[152] | 835 | SDMemTable* pOut = new SDMemTable(in,False); |
---|
| 836 | const Table& tOut = pOut->table(); |
---|
| 837 | ArrayColumn<Float> spec(tOut,"SPECTRA"); |
---|
[146] | 838 | // |
---|
[152] | 839 | if (doAll) { |
---|
| 840 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
| 841 | |
---|
| 842 | // Get |
---|
| 843 | |
---|
| 844 | MaskedArray<Float> marr(pOut->rowAsMaskedArray(i)); |
---|
| 845 | |
---|
| 846 | // Operate |
---|
| 847 | |
---|
| 848 | if (what==0) { |
---|
| 849 | marr *= val; |
---|
| 850 | } else if (what==1) { |
---|
| 851 | marr += val; |
---|
| 852 | } |
---|
| 853 | |
---|
| 854 | // Put |
---|
| 855 | |
---|
| 856 | spec.put(i, marr.getArray()); |
---|
| 857 | } |
---|
| 858 | } else { |
---|
| 859 | |
---|
| 860 | // Get cursor location |
---|
| 861 | |
---|
| 862 | IPosition start, end; |
---|
| 863 | getCursorLocation (start, end, in); |
---|
| 864 | // |
---|
| 865 | for (uInt i=0; i < tOut.nrow(); i++) { |
---|
| 866 | |
---|
| 867 | // Get |
---|
| 868 | |
---|
| 869 | MaskedArray<Float> dataIn(pOut->rowAsMaskedArray(i)); |
---|
| 870 | |
---|
| 871 | // Modify. More work than we would like to deal with the mask |
---|
| 872 | |
---|
| 873 | Array<Float>& values = dataIn.getRWArray(); |
---|
| 874 | Array<Bool> mask(dataIn.getMask()); |
---|
| 875 | // |
---|
| 876 | Array<Float> values2 = values(start,end); |
---|
| 877 | Array<Bool> mask2 = mask(start,end); |
---|
| 878 | MaskedArray<Float> t(values2,mask2); |
---|
| 879 | if (what==0) { |
---|
| 880 | t *= val; |
---|
| 881 | } else if (what==1) { |
---|
| 882 | t += val; |
---|
| 883 | } |
---|
| 884 | values(start, end) = t.getArray(); // Write back into 'dataIn' |
---|
| 885 | |
---|
| 886 | // Put |
---|
| 887 | spec.put(i, dataIn.getArray()); |
---|
| 888 | } |
---|
| 889 | } |
---|
| 890 | // |
---|
[146] | 891 | return pOut; |
---|
| 892 | } |
---|
| 893 | |
---|
| 894 | |
---|
[152] | 895 | |
---|
| 896 | void SDMath::getCursorLocation (IPosition& start, IPosition& end, |
---|
| 897 | const SDMemTable& in) |
---|
| 898 | { |
---|
| 899 | const uInt nDim = 4; |
---|
| 900 | const uInt i = in.getBeam(); |
---|
| 901 | const uInt j = in.getIF(); |
---|
| 902 | const uInt k = in.getPol(); |
---|
| 903 | const uInt n = in.nChan(); |
---|
| 904 | // |
---|
| 905 | IPosition s(nDim,i,j,k,0); |
---|
| 906 | IPosition e(nDim,i,j,k,n-1); |
---|
| 907 | // |
---|
| 908 | start.resize(nDim); |
---|
| 909 | start = s; |
---|
| 910 | end.resize(nDim); |
---|
| 911 | end = e; |
---|
| 912 | } |
---|