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