[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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[130] | 66 | CountedPtr<SDMemTable> SDMath::average(const CountedPtr<SDMemTable>& in) |
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| 67 | // |
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| 68 | // Average all rows in Table in time |
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| 69 | // |
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| 70 | { |
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[2] | 71 | Table t = in->table(); |
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[85] | 72 | ROArrayColumn<Float> tsys(t, "TSYS"); |
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[2] | 73 | ROScalarColumn<Double> mjd(t, "TIME"); |
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| 74 | ROScalarColumn<String> srcn(t, "SRCNAME"); |
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[15] | 75 | ROScalarColumn<Double> integr(t, "INTERVAL"); |
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[38] | 76 | ROArrayColumn<uInt> freqidc(t, "FREQID"); |
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[2] | 77 | IPosition ip = in->rowAsMaskedArray(0).shape(); |
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| 78 | Array<Float> outarr(ip); outarr =0.0; |
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| 79 | Array<Float> narr(ip);narr = 0.0; |
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| 80 | Array<Float> narrinc(ip);narrinc = 1.0; |
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| 81 | |
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| 82 | Array<Float> tsarr(tsys.shape(0)); |
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| 83 | Array<Float> outtsarr(tsys.shape(0)); |
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[48] | 84 | outtsarr =0.0; |
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| 85 | tsys.get(0, tsarr);// this is probably unneccessary as tsys should |
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[2] | 86 | Double tme = 0.0; |
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[15] | 87 | Double inttime = 0.0; |
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[2] | 88 | |
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[130] | 89 | // Loop over rows |
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| 90 | |
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[2] | 91 | for (uInt i=0; i < t.nrow(); i++) { |
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[130] | 92 | |
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| 93 | // Get data and accumulate sums |
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| 94 | |
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[2] | 95 | MaskedArray<Float> marr(in->rowAsMaskedArray(i)); |
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| 96 | outarr += marr; |
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| 97 | MaskedArray<Float> n(narrinc,marr.getMask()); |
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| 98 | narr += n; |
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[130] | 99 | |
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| 100 | // Accumulkate Tsys |
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| 101 | |
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[2] | 102 | tsys.get(i, tsarr);// this is probably unneccessary as tsys should |
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| 103 | outtsarr += tsarr; // be constant |
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| 104 | Double tmp; |
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| 105 | mjd.get(i,tmp); |
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| 106 | tme += tmp;// average time |
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[15] | 107 | integr.get(i,tmp); |
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| 108 | inttime += tmp; |
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[2] | 109 | } |
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[130] | 110 | |
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| 111 | // Average |
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| 112 | |
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[9] | 113 | MaskedArray<Float> nma(narr,(narr > Float(0))); |
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[2] | 114 | outarr /= nma; |
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[130] | 115 | |
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| 116 | // Create container and put |
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| 117 | |
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[9] | 118 | Array<Bool> outflagsb = !(nma.getMask()); |
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| 119 | Array<uChar> outflags(outflagsb.shape()); |
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| 120 | convertArray(outflags,outflagsb); |
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[48] | 121 | SDContainer sc = in->getSDContainer(); |
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[2] | 122 | Int n = t.nrow(); |
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[48] | 123 | outtsarr /= Float(n); |
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| 124 | sc.timestamp = tme/Double(n); |
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| 125 | sc.interval = inttime; |
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[15] | 126 | String tstr; srcn.getScalar(0,tstr);// get sourcename of "mid" point |
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[2] | 127 | sc.sourcename = tstr; |
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[38] | 128 | Vector<uInt> tvec; |
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| 129 | freqidc.get(0,tvec); |
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| 130 | sc.putFreqMap(tvec); |
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[48] | 131 | sc.putTsys(outtsarr); |
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[38] | 132 | sc.scanid = 0; |
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[2] | 133 | sc.putSpectrum(outarr); |
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[85] | 134 | sc.putFlags(outflags); |
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[15] | 135 | SDMemTable* sdmt = new SDMemTable(*in,True); |
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[2] | 136 | sdmt->putSDContainer(sc); |
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| 137 | return CountedPtr<SDMemTable>(sdmt); |
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| 138 | } |
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[9] | 139 | |
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[85] | 140 | CountedPtr<SDMemTable> |
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| 141 | SDMath::quotient(const CountedPtr<SDMemTable>& on, |
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[130] | 142 | const CountedPtr<SDMemTable>& off) |
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| 143 | // |
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| 144 | // Compute quotient spectrum |
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| 145 | // |
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| 146 | { |
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| 147 | const uInt nRows = on->nRow(); |
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| 148 | if (off->nRow() != nRows) { |
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| 149 | throw (AipsError("Input Scan Tables must have the same number of rows")); |
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| 150 | } |
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[85] | 151 | |
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[130] | 152 | // Input Tables and columns |
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| 153 | |
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[9] | 154 | Table ton = on->table(); |
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| 155 | Table toff = off->table(); |
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[85] | 156 | ROArrayColumn<Float> tsys(toff, "TSYS"); |
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[9] | 157 | ROScalarColumn<Double> mjd(ton, "TIME"); |
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[15] | 158 | ROScalarColumn<Double> integr(ton, "INTERVAL"); |
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[9] | 159 | ROScalarColumn<String> srcn(ton, "SRCNAME"); |
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[38] | 160 | ROArrayColumn<uInt> freqidc(ton, "FREQID"); |
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| 161 | |
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[130] | 162 | // Output Table cloned from input |
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[85] | 163 | |
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[15] | 164 | SDMemTable* sdmt = new SDMemTable(*on, True); |
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[130] | 165 | |
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| 166 | // Loop over rows |
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| 167 | |
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| 168 | for (uInt i=0; i<nRows; i++) { |
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| 169 | MaskedArray<Float> mon(on->rowAsMaskedArray(i)); |
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| 170 | MaskedArray<Float> moff(off->rowAsMaskedArray(i)); |
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| 171 | IPosition ipon = mon.shape(); |
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| 172 | IPosition ipoff = moff.shape(); |
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| 173 | // |
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| 174 | Array<Float> tsarr; |
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| 175 | tsys.get(i, tsarr); |
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| 176 | if (ipon != ipoff && ipon != tsarr.shape()) { |
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| 177 | throw(AipsError("on/off not conformant")); |
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| 178 | } |
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| 179 | |
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| 180 | // Compute quotient |
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| 181 | |
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| 182 | MaskedArray<Float> tmp = (mon-moff); |
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| 183 | Array<Float> out(tmp.getArray()); |
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| 184 | out /= moff; |
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| 185 | out *= tsarr; |
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| 186 | Array<Bool> outflagsb = !(mon.getMask() && moff.getMask()); |
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| 187 | Array<uChar> outflags(outflagsb.shape()); |
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| 188 | convertArray(outflags,outflagsb); |
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| 189 | |
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| 190 | // Fill container for this row |
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| 191 | |
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| 192 | SDContainer sc = on->getSDContainer(); |
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| 193 | sc.putTsys(tsarr); |
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| 194 | sc.scanid = 0; |
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| 195 | sc.putSpectrum(out); |
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| 196 | sc.putFlags(outflags); |
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| 197 | |
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| 198 | // Put new row in output Table |
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| 199 | |
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| 200 | sdmt->putSDContainer(sc); |
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| 201 | } |
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| 202 | // |
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[9] | 203 | return CountedPtr<SDMemTable>(sdmt); |
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| 204 | } |
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[48] | 205 | |
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[85] | 206 | CountedPtr<SDMemTable> |
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[130] | 207 | SDMath::multiply(const CountedPtr<SDMemTable>& in, Float factor) |
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| 208 | // |
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| 209 | // Multiply values by factor |
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| 210 | // |
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| 211 | { |
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[15] | 212 | SDMemTable* sdmt = new SDMemTable(*in); |
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| 213 | Table t = sdmt->table(); |
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| 214 | ArrayColumn<Float> spec(t,"SPECTRA"); |
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[9] | 215 | |
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[15] | 216 | for (uInt i=0; i < t.nrow(); i++) { |
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| 217 | MaskedArray<Float> marr(sdmt->rowAsMaskedArray(i)); |
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| 218 | marr *= factor; |
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| 219 | spec.put(i, marr.getArray()); |
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| 220 | } |
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| 221 | return CountedPtr<SDMemTable>(sdmt); |
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| 222 | } |
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[48] | 223 | |
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[107] | 224 | CountedPtr<SDMemTable> |
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[130] | 225 | SDMath::add(const CountedPtr<SDMemTable>& in, Float offset) |
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| 226 | // |
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| 227 | // Add offset to values |
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| 228 | // |
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| 229 | { |
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[107] | 230 | SDMemTable* sdmt = new SDMemTable(*in); |
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[130] | 231 | |
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[107] | 232 | Table t = sdmt->table(); |
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| 233 | ArrayColumn<Float> spec(t,"SPECTRA"); |
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| 234 | |
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| 235 | for (uInt i=0; i < t.nrow(); i++) { |
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| 236 | MaskedArray<Float> marr(sdmt->rowAsMaskedArray(i)); |
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| 237 | marr += offset; |
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| 238 | spec.put(i, marr.getArray()); |
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| 239 | } |
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| 240 | return CountedPtr<SDMemTable>(sdmt); |
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| 241 | } |
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| 242 | |
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| 243 | |
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[130] | 244 | CountedPtr<SDMemTable> |
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| 245 | SDMath::hanning(const CountedPtr<SDMemTable>& in) |
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| 246 | // |
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| 247 | // Hanning smooth each row |
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| 248 | // Should Tsys be smoothed ? |
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| 249 | // |
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| 250 | { |
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| 251 | SDMemTable* sdmt = new SDMemTable(*in,True); |
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[107] | 252 | |
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[130] | 253 | // Loop over rows in Table |
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[48] | 254 | |
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[130] | 255 | for (uInt ri=0; ri < in->nRow(); ++ri) { |
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[38] | 256 | |
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[130] | 257 | // Get data |
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[125] | 258 | |
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[130] | 259 | const MaskedArray<Float>& marr(in->rowAsMaskedArray(ri)); |
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[85] | 260 | Array<Float> arr = marr.getArray(); |
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| 261 | Array<Bool> barr = marr.getMask(); |
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[130] | 262 | |
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| 263 | // Smooth along the channels axis |
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| 264 | |
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| 265 | uInt axis = 3; |
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| 266 | VectorIterator<Float> itData(arr, axis); |
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| 267 | VectorIterator<Bool> itMask(barr, axis); |
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| 268 | Vector<Float> outv; |
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| 269 | Vector<Bool> outm; |
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| 270 | while (!itData.pastEnd()) { |
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| 271 | mathutil::hanning(outv, outm, itData.vector(), itMask.vector()); |
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| 272 | itData.vector() = outv; |
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| 273 | itMask.vector() = outm; |
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| 274 | // |
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| 275 | itData.next(); |
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| 276 | itMask.next(); |
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[38] | 277 | } |
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[130] | 278 | |
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| 279 | // Create and put back |
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| 280 | |
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[85] | 281 | Array<uChar> outflags(barr.shape()); |
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| 282 | convertArray(outflags,!barr); |
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| 283 | SDContainer sc = in->getSDContainer(ri); |
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| 284 | sc.putSpectrum(arr); |
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| 285 | sc.putFlags(outflags); |
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| 286 | sdmt->putSDContainer(sc); |
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[38] | 287 | } |
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| 288 | return CountedPtr<SDMemTable>(sdmt); |
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| 289 | } |
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| 290 | |
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[85] | 291 | |
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[130] | 292 | |
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| 293 | CountedPtr<SDMemTable> SDMath::averages(const Block<CountedPtr<SDMemTable> >& in, |
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| 294 | const Vector<Bool>& mask) |
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| 295 | // |
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| 296 | // Noise weighted averaging of spectra from many Tables. Tables can have different |
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| 297 | // number of rows. |
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| 298 | // |
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| 299 | { |
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| 300 | |
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| 301 | // Setup |
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| 302 | |
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| 303 | const uInt axis = 3; // Spectral axis |
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| 304 | IPosition shp = in[0]->rowAsMaskedArray(0).shape(); |
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| 305 | Array<Float> arr(shp); |
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| 306 | Array<Bool> barr(shp); |
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| 307 | Double sumInterval = 0.0; |
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| 308 | const Bool useMask = (mask.nelements() == shp(axis)); |
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| 309 | |
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| 310 | // Create data accumulation MaskedArray. We accumulate for each |
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| 311 | // channel,if,pol,beam |
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| 312 | |
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| 313 | Array<Float> zero(shp); zero=0.0; |
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| 314 | Array<Bool> good(shp); good = True; |
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| 315 | MaskedArray<Float> sum(zero,good); |
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| 316 | |
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| 317 | // Create accumulation Array for variance. We accumulate for |
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| 318 | // each if,pol,beam, but average over channel |
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| 319 | |
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| 320 | const uInt nAxesSub = shp.nelements() - 1; |
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| 321 | IPosition shp2(nAxesSub); |
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| 322 | for (uInt i=0,j=0; i<(nAxesSub+1); i++) { |
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| 323 | if (i!=axis) { |
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| 324 | shp2(j) = shp(i); |
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| 325 | j++; |
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| 326 | } |
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| 327 | } |
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| 328 | Array<Float> sumSq(shp2); |
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| 329 | sumSq = 0.0; |
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| 330 | IPosition pos2(nAxesSub,0); // FOr indexing |
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| 331 | // |
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| 332 | Float fac = 1.0; |
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| 333 | const uInt nTables = in.nelements(); |
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| 334 | for (uInt iTab=0; iTab<nTables; iTab++) { |
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| 335 | const uInt nRows = in[iTab]->nRow(); |
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| 336 | sumInterval += nRows * in[iTab]->getInterval(); // Sum of time intervals |
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| 337 | // |
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| 338 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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| 339 | |
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| 340 | // Check conforms |
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| 341 | |
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| 342 | IPosition shp2 = in[iTab]->rowAsMaskedArray(iRow).shape(); |
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| 343 | if (!shp.isEqual(shp2)) { |
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| 344 | throw (AipsError("Shapes for all rows must be the same")); |
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[85] | 345 | } |
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[130] | 346 | |
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| 347 | // Get data and deconstruct |
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| 348 | |
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| 349 | MaskedArray<Float> marr(in[iTab]->rowAsMaskedArray(iRow)); |
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| 350 | Array<Float>& arr = marr.getRWArray(); // writable reference |
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| 351 | const Array<Bool>& barr = marr.getMask(); // RO reference |
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| 352 | |
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| 353 | // We are going to average the data, weighted by the noise for each |
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| 354 | // pol, beam and IF. So therefore we need to iterate through by |
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| 355 | // spectra (axis 3) |
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| 356 | |
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| 357 | VectorIterator<Float> itData(arr, axis); |
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| 358 | ReadOnlyVectorIterator<Bool> itMask(barr, axis); |
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| 359 | while (!itData.pastEnd()) { |
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| 360 | |
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| 361 | // Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor |
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| 362 | |
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| 363 | if (useMask) { |
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| 364 | MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector()); |
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| 365 | fac = 1.0/variance(tmp); |
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| 366 | } else { |
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| 367 | MaskedArray<Float> tmp(itData.vector(),itMask.vector()); |
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| 368 | fac = 1.0/variance(tmp); |
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| 369 | } |
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| 370 | |
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| 371 | // Scale data |
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| 372 | |
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| 373 | itData.vector() *= fac; |
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| 374 | |
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| 375 | // Accumulate variance per if/pol/beam averaged over spectrum |
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| 376 | // This method to get pos2 from itData.pos() is only valid |
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| 377 | // because the spectral axis is the last one (so we can just |
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| 378 | // copy the first nAXesSub positions out) |
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| 379 | |
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| 380 | pos2 = itData.pos().getFirst(nAxesSub); |
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| 381 | sumSq(pos2) += fac; |
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| 382 | // |
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| 383 | itData.next(); |
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| 384 | itMask.next(); |
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| 385 | } |
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| 386 | |
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| 387 | // Accumulate sums |
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| 388 | |
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| 389 | sum += marr; |
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[48] | 390 | } |
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| 391 | } |
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[130] | 392 | |
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| 393 | // Normalize by the sum of the 1/var. |
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| 394 | |
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| 395 | Array<Float>& data = sum.getRWArray(); |
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| 396 | VectorIterator<Float> itData(data, axis); |
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| 397 | while (!itData.pastEnd()) { |
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| 398 | pos2 = itData.pos().getFirst(nAxesSub); // See comments above |
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| 399 | itData.vector() /= sumSq(pos2); |
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| 400 | itData.next(); |
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| 401 | } |
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| 402 | |
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| 403 | // Create and fill output |
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| 404 | |
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| 405 | Array<uChar> outflags(shp); |
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| 406 | convertArray(outflags,!(sum.getMask())); |
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| 407 | // |
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| 408 | SDContainer sc = in[0]->getSDContainer(); // CLone from first container of first Table |
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| 409 | sc.putSpectrum(data); |
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[48] | 410 | sc.putFlags(outflags); |
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[130] | 411 | sc.interval = sumInterval; |
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| 412 | // |
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| 413 | SDMemTable* sdmt = new SDMemTable(*in[0],True); // CLone from first Table |
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[48] | 414 | sdmt->putSDContainer(sc); |
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| 415 | return CountedPtr<SDMemTable>(sdmt); |
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[15] | 416 | } |
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[48] | 417 | |
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[130] | 418 | |
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[85] | 419 | CountedPtr<SDMemTable> |
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| 420 | SDMath::averagePol(const CountedPtr<SDMemTable>& in, |
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[130] | 421 | const Vector<Bool>& mask) |
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| 422 | { |
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| 423 | const uInt nRows = in->nRow(); |
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| 424 | const uInt axis = 3; // Spectrum |
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| 425 | const IPosition axes(2, 2, 3); // pol-channel plane |
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| 426 | |
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| 427 | // Create output Table |
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| 428 | |
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| 429 | SDMemTable* sdmt = new SDMemTable(*in, True); |
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| 430 | |
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| 431 | // Loop over rows |
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| 432 | |
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| 433 | for (uInt iRow=0; iRow<nRows; iRow++) { |
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| 434 | |
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| 435 | // Get data for this row |
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| 436 | |
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| 437 | MaskedArray<Float> marr(in->rowAsMaskedArray(iRow)); |
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| 438 | Array<Float>& arr = marr.getRWArray(); |
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| 439 | const Array<Bool>& barr = marr.getMask(); |
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| 440 | // |
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| 441 | IPosition shp = marr.shape(); |
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| 442 | const Bool useMask = (mask.nelements() == shp(axis)); |
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| 443 | const uInt nChan = shp(axis); |
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| 444 | |
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| 445 | // Make iterators to iterate by pol-channel planes |
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| 446 | |
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| 447 | ArrayIterator<Float> itDataPlane(arr, axes); |
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| 448 | ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes); |
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| 449 | |
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| 450 | // Accumulations |
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| 451 | |
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| 452 | Float fac = 0.0; |
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| 453 | Vector<Float> vecSum(nChan,0.0); |
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| 454 | |
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| 455 | // Iterate by plane |
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| 456 | |
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| 457 | while (!itDataPlane.pastEnd()) { |
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| 458 | |
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| 459 | // Iterate through pol-channel plane by spectrum |
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| 460 | |
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| 461 | Vector<Float> t1(nChan); t1 = 0.0; |
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| 462 | Vector<Bool> t2(nChan); t2 = True; |
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| 463 | MaskedArray<Float> vecSum(t1,t2); |
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| 464 | Float varSum = 0.0; |
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| 465 | { |
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| 466 | ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1); |
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| 467 | ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1); |
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| 468 | while (!itDataVec.pastEnd()) { |
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| 469 | |
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| 470 | // Create MA of data & mask (optionally including OTF mask) and get variance |
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| 471 | |
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| 472 | if (useMask) { |
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| 473 | const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector()); |
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| 474 | fac = 1.0 / variance(spec); |
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| 475 | } else { |
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| 476 | const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector()); |
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| 477 | fac = 1.0 / variance(spec); |
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| 478 | } |
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| 479 | |
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| 480 | // Normalize spectrum (without OTF mask) and accumulate |
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| 481 | |
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| 482 | const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector()); |
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| 483 | vecSum += spec; |
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| 484 | varSum += fac; |
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| 485 | |
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| 486 | // Next |
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| 487 | |
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| 488 | itDataVec.next(); |
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| 489 | itMaskVec.next(); |
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| 490 | } |
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[85] | 491 | } |
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[48] | 492 | |
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[130] | 493 | // Normalize summed spectrum |
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[48] | 494 | |
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[130] | 495 | vecSum /= varSum; |
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[48] | 496 | |
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[130] | 497 | // We have formed the weighted averaged spectrum from all polarizations |
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| 498 | // for this beam and IF. Now replicate the spectrum to all polarizations |
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[48] | 499 | |
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[130] | 500 | { |
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| 501 | VectorIterator<Float> itDataVec(itDataPlane.array(), 1); // Writes back into 'arr' |
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| 502 | const Vector<Float>& vecSumData = vecSum.getArray(); // It *is* a Vector |
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| 503 | // |
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| 504 | while (!itDataVec.pastEnd()) { |
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| 505 | itDataVec.vector() = vecSumData; |
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| 506 | itDataVec.next(); |
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| 507 | } |
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| 508 | } |
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| 509 | |
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| 510 | // Step to next beam/IF combination |
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| 511 | |
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| 512 | itDataPlane.next(); |
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| 513 | itMaskPlane.next(); |
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| 514 | } |
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| 515 | |
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| 516 | // Generate output container and write it to output table |
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| 517 | |
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| 518 | SDContainer sc = in->getSDContainer(); |
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| 519 | Array<uChar> outflags(barr.shape()); |
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| 520 | convertArray(outflags,!barr); |
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| 521 | sc.putSpectrum(arr); |
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| 522 | sc.putFlags(outflags); |
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| 523 | sdmt->putSDContainer(sc); |
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| 524 | } |
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| 525 | // |
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| 526 | return CountedPtr<SDMemTable>(sdmt); |
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[48] | 527 | } |
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| 528 | |
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[130] | 529 | |
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[85] | 530 | CountedPtr<SDMemTable> SDMath::bin(const CountedPtr<SDMemTable>& in, |
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[130] | 531 | Int width) |
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| 532 | { |
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[48] | 533 | SDHeader sh = in->getSDHeader(); |
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[85] | 534 | SDMemTable* sdmt = new SDMemTable(*in,True); |
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| 535 | |
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[130] | 536 | // Bin up SpectralCoordinates |
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| 537 | |
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| 538 | IPosition factors(1); |
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| 539 | factors(0) = width; |
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[85] | 540 | for (uInt j=0; j<in->nCoordinates(); ++j) { |
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[130] | 541 | CoordinateSystem cSys; |
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| 542 | cSys.addCoordinate(in->getCoordinate(j)); |
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| 543 | CoordinateSystem cSysBin = |
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| 544 | CoordinateUtil::makeBinnedCoordinateSystem (factors, cSys, False); |
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| 545 | // |
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| 546 | SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0); |
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| 547 | sdmt->setCoordinate(sCBin, j); |
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[85] | 548 | } |
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[130] | 549 | |
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| 550 | // Use RebinLattice to find shape |
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| 551 | |
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| 552 | IPosition shapeIn(1,sh.nchan); |
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| 553 | IPosition shapeOut = RebinLattice<Float>::rebinShape (shapeIn, factors); |
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| 554 | sh.nchan = shapeOut(0); |
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[48] | 555 | sdmt->putSDHeader(sh); |
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[85] | 556 | |
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[130] | 557 | |
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| 558 | // Loop over rows and bin along channel axis |
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| 559 | |
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| 560 | const uInt axis = 3; |
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[85] | 561 | for (uInt i=0; i < in->nRow(); ++i) { |
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[130] | 562 | SDContainer sc = in->getSDContainer(i); |
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| 563 | // |
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| 564 | Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape |
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| 565 | |
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| 566 | // Bin up spectrum |
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| 567 | |
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[85] | 568 | MaskedArray<Float> marr(in->rowAsMaskedArray(i)); |
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| 569 | MaskedArray<Float> marrout; |
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[130] | 570 | LatticeUtilities::bin(marrout, marr, axis, width); |
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| 571 | |
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| 572 | // Put back the binned data and flags |
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| 573 | |
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[85] | 574 | IPosition ip2 = marrout.shape(); |
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| 575 | sc.resize(ip2); |
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| 576 | sc.putSpectrum(marrout.getArray()); |
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[130] | 577 | // |
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[85] | 578 | Array<uChar> outflags(ip2); |
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| 579 | convertArray(outflags,!(marrout.getMask())); |
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| 580 | sc.putFlags(outflags); |
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[130] | 581 | |
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| 582 | // Bin up Tsys. |
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| 583 | |
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| 584 | Array<Bool> allGood(tSys.shape(),True); |
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| 585 | MaskedArray<Float> tSysIn(tSys, allGood, True); |
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| 586 | // |
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| 587 | MaskedArray<Float> tSysOut; |
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| 588 | LatticeUtilities::bin(tSysOut, tSysIn, axis, width); |
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| 589 | sc.putTsys(tSysOut.getArray()); |
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[85] | 590 | sdmt->putSDContainer(sc); |
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| 591 | } |
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[48] | 592 | return CountedPtr<SDMemTable>(sdmt); |
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| 593 | } |
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[130] | 594 | |
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| 595 | |
---|
| 596 | |
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| 597 | std::vector<float> SDMath::statistic (const CountedPtr<SDMemTable>& in, |
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| 598 | const std::vector<bool>& mask, |
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| 599 | const std::string& which) |
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| 600 | // |
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| 601 | // Perhaps iteration over pol/beam/if should be in here |
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| 602 | // and inside the nrow iteration ? |
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| 603 | // |
---|
| 604 | { |
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| 605 | const uInt nRow = in->nRow(); |
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| 606 | std::vector<float> result(nRow); |
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| 607 | Vector<Bool> msk(mask); |
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| 608 | |
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| 609 | // Specify cursor location |
---|
| 610 | |
---|
| 611 | uInt i = in->getBeam(); |
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| 612 | uInt j = in->getIF(); |
---|
| 613 | uInt k = in->getPol(); |
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| 614 | IPosition start(4,i,j,k,0); |
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| 615 | IPosition end(4,i,j,k,in->nChan()-1); |
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| 616 | |
---|
| 617 | // Loop over rows |
---|
| 618 | |
---|
| 619 | const uInt nEl = msk.nelements(); |
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| 620 | for (uInt ii=0; ii < in->nRow(); ++ii) { |
---|
| 621 | |
---|
| 622 | // Get row and deconstruct |
---|
| 623 | |
---|
| 624 | MaskedArray<Float> marr(in->rowAsMaskedArray(ii)); |
---|
| 625 | Array<Float> arr = marr.getArray(); |
---|
| 626 | Array<Bool> barr = marr.getMask(); |
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| 627 | |
---|
| 628 | // Access desired piece of data |
---|
| 629 | |
---|
| 630 | Array<Float> v((arr(start,end)).nonDegenerate()); |
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| 631 | Array<Bool> m((barr(start,end)).nonDegenerate()); |
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| 632 | |
---|
| 633 | // Apply OTF mask |
---|
| 634 | |
---|
| 635 | MaskedArray<Float> tmp; |
---|
| 636 | if (m.nelements()==nEl) { |
---|
| 637 | tmp.setData(v,m&&msk); |
---|
| 638 | } else { |
---|
| 639 | tmp.setData(v,m); |
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| 640 | } |
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| 641 | |
---|
| 642 | // Get statistic |
---|
| 643 | |
---|
| 644 | result[ii] = SDMath::theStatistic(which, tmp); |
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| 645 | } |
---|
| 646 | // |
---|
| 647 | return result; |
---|
| 648 | } |
---|
| 649 | |
---|
| 650 | |
---|
| 651 | float SDMath::theStatistic(const std::string& which, const casa::MaskedArray<Float>& data) |
---|
| 652 | { |
---|
| 653 | String str(which); |
---|
| 654 | str.upcase(); |
---|
| 655 | if (str.contains(String("MIN"))) { |
---|
| 656 | return min(data); |
---|
| 657 | } else if (str.contains(String("MAX"))) { |
---|
| 658 | return max(data); |
---|
| 659 | } else if (str.contains(String("SUMSQ"))) { |
---|
| 660 | return sumsquares(data); |
---|
| 661 | } else if (str.contains(String("SUM"))) { |
---|
| 662 | return sum(data); |
---|
| 663 | } else if (str.contains(String("MEAN"))) { |
---|
| 664 | return mean(data); |
---|
| 665 | } else if (str.contains(String("VAR"))) { |
---|
| 666 | return variance(data); |
---|
| 667 | } else if (str.contains(String("STDDEV"))) { |
---|
| 668 | return stddev(data); |
---|
| 669 | } else if (str.contains(String("AVDEV"))) { |
---|
| 670 | return avdev(data); |
---|
| 671 | } else if (str.contains(String("RMS"))) { |
---|
| 672 | uInt n = data.nelementsValid(); |
---|
| 673 | return sqrt(sumsquares(data)/n); |
---|
| 674 | } else if (str.contains(String("MED"))) { |
---|
| 675 | return median(data); |
---|
| 676 | } |
---|
| 677 | } |
---|