source: trunk/src/SDMath.cc @ 247

Last change on this file since 247 was 247, checked in by kil064, 19 years ago

fix error in nRow test in function quotient

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1//#---------------------------------------------------------------------------
2//# SDMath.cc: A collection of single dish mathematical operations
3//#---------------------------------------------------------------------------
4//# Copyright (C) 2004
5//# ATNF
6//#
7//# This program is free software; you can redistribute it and/or modify it
8//# under the terms of the GNU General Public License as published by the Free
9//# Software Foundation; either version 2 of the License, or (at your option)
10//# any later version.
11//#
12//# This program is distributed in the hope that it will be useful, but
13//# WITHOUT ANY WARRANTY; without even the implied warranty of
14//# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General
15//# Public License for more details.
16//#
17//# You should have received a copy of the GNU General Public License along
18//# with this program; if not, write to the Free Software Foundation, Inc.,
19//# 675 Massachusetts Ave, Cambridge, MA 02139, USA.
20//#
21//# Correspondence concerning this software should be addressed as follows:
22//#        Internet email: Malte.Marquarding@csiro.au
23//#        Postal address: Malte Marquarding,
24//#                        Australia Telescope National Facility,
25//#                        P.O. Box 76,
26//#                        Epping, NSW, 2121,
27//#                        AUSTRALIA
28//#
29//# $Id:
30//#---------------------------------------------------------------------------
31#include <vector>
32
33#include <casa/aips.h>
34#include <casa/BasicSL/String.h>
35#include <casa/Arrays/IPosition.h>
36#include <casa/Arrays/Array.h>
37#include <casa/Arrays/ArrayIter.h>
38#include <casa/Arrays/VectorIter.h>
39#include <casa/Arrays/ArrayMath.h>
40#include <casa/Arrays/ArrayLogical.h>
41#include <casa/Arrays/MaskedArray.h>
42#include <casa/Arrays/MaskArrMath.h>
43#include <casa/Arrays/MaskArrLogi.h>
44#include <casa/BasicMath/Math.h>
45#include <casa/Containers/Block.h>
46#include <casa/Quanta/QC.h>
47#include <casa/Utilities/Assert.h>
48#include <casa/Exceptions.h>
49
50#include <scimath/Mathematics/VectorKernel.h>
51#include <scimath/Mathematics/Convolver.h>
52#include <scimath/Mathematics/InterpolateArray1D.h>
53#include <scimath/Functionals/Polynomial.h>
54
55#include <tables/Tables/Table.h>
56#include <tables/Tables/ScalarColumn.h>
57#include <tables/Tables/ArrayColumn.h>
58#include <tables/Tables/ReadAsciiTable.h>
59
60#include <lattices/Lattices/LatticeUtilities.h>
61#include <lattices/Lattices/RebinLattice.h>
62#include <coordinates/Coordinates/SpectralCoordinate.h>
63#include <coordinates/Coordinates/CoordinateSystem.h>
64#include <coordinates/Coordinates/CoordinateUtil.h>
65#include <coordinates/Coordinates/VelocityAligner.h>
66
67#include "MathUtils.h"
68#include "SDDefs.h"
69#include "SDContainer.h"
70#include "SDMemTable.h"
71
72#include "SDMath.h"
73
74using namespace casa;
75using namespace asap;
76
77
78SDMath::SDMath()
79{;}
80
81SDMath::SDMath(const SDMath& other)
82{
83
84// No state
85
86}
87
88SDMath& SDMath::operator=(const SDMath& other)
89{
90  if (this != &other) {
91// No state
92  }
93  return *this;
94}
95
96SDMath::~SDMath()
97{;}
98
99
100CountedPtr<SDMemTable> SDMath::average(const Block<CountedPtr<SDMemTable> >& in,
101                                       const Vector<Bool>& mask, Bool scanAv,
102                                       const String& weightStr) const
103//Bool alignVelocity)
104//
105// Weighted averaging of spectra from one or more Tables.
106//
107{
108   Bool alignVelocity = False;
109
110// Convert weight type
111 
112  WeightType wtType = NONE;
113  convertWeightString(wtType, weightStr);
114
115// Create output Table by cloning from the first table
116
117  SDMemTable* pTabOut = new SDMemTable(*in[0],True);
118
119// Setup
120
121  IPosition shp = in[0]->rowAsMaskedArray(0).shape();      // Must not change
122  Array<Float> arr(shp);
123  Array<Bool> barr(shp);
124  const Bool useMask = (mask.nelements() == shp(asap::ChanAxis));
125
126// Columns from Tables
127
128  ROArrayColumn<Float> tSysCol;
129  ROScalarColumn<Double> mjdCol;
130  ROScalarColumn<String> srcNameCol;
131  ROScalarColumn<Double> intCol;
132  ROArrayColumn<uInt> fqIDCol;
133
134// Create accumulation MaskedArray. We accumulate for each channel,if,pol,beam
135// Note that the mask of the accumulation array will ALWAYS remain ALL True.
136// The MA is only used so that when data which is masked Bad is added to it,
137// that data does not contribute.
138
139  Array<Float> zero(shp);
140  zero=0.0;
141  Array<Bool> good(shp);
142  good = True;
143  MaskedArray<Float> sum(zero,good);
144
145// Counter arrays
146
147  Array<Float> nPts(shp);             // Number of points
148  nPts = 0.0;
149  Array<Float> nInc(shp);             // Increment
150  nInc = 1.0;
151
152// Create accumulation Array for variance. We accumulate for
153// each if,pol,beam, but average over channel.  So we need
154// a shape with one less axis dropping channels.
155
156  const uInt nAxesSub = shp.nelements() - 1;
157  IPosition shp2(nAxesSub);
158  for (uInt i=0,j=0; i<(nAxesSub+1); i++) {
159     if (i!=asap::ChanAxis) {
160       shp2(j) = shp(i);
161       j++;
162     }
163  }
164  Array<Float> sumSq(shp2);
165  sumSq = 0.0;
166  IPosition pos2(nAxesSub,0);                        // For indexing
167
168// Time-related accumulators
169
170  Double time;
171  Double timeSum = 0.0;
172  Double intSum = 0.0;
173  Double interval = 0.0;
174
175// To get the right shape for the Tsys accumulator we need to
176// access a column from the first table.  The shape of this
177// array must not change
178
179  Array<Float> tSysSum;
180  {
181    const Table& tabIn = in[0]->table();
182    tSysCol.attach(tabIn,"TSYS");
183    tSysSum.resize(tSysCol.shape(0));
184  }
185  tSysSum =0.0;
186  Array<Float> tSys;
187
188// Scan and row tracking
189
190  Int oldScanID = 0;
191  Int outScanID = 0;
192  Int scanID = 0;
193  Int rowStart = 0;
194  Int nAccum = 0;
195  Int tableStart = 0;
196
197// Source and FreqID
198
199  String sourceName, oldSourceName, sourceNameStart;
200  Vector<uInt> freqID, freqIDStart, oldFreqID;
201
202// Velocity Aligner. We need an aligner for each Direction and FreqID
203// combination.  I don't think there is anyway to know how many
204// directions there are.
205// For now, assume all Tables have the same Frequency Table
206
207/*
208  {
209     MEpoch::Ref timeRef(MEpoch::UTC);              // Should be in header
210     MDirection::Types dirRef(MDirection::J2000);   // Should be in header
211//
212     SDHeader sh = in[0].getSDHeader();
213     const uInt nChan = sh.nchan;
214//
215     const SDFrequencyTable freqTab = in[0]->getSDFreqTable();
216     const uInt nFreqID = freqTab.length();
217     PtrBlock<const VelocityAligner<Float>* > vA(nFreqID);
218
219// Get first time from first table
220
221     const Table& tabIn0 = in[0]->table();
222     mjdCol.attach(tabIn0, "TIME");
223     Double dTmp;
224     mjdCol.get(0, dTmp);
225     MVEpoch tmp2(Quantum<Double>(dTmp, Unit(String("d"))));
226     MEpoch epoch(tmp2, timeRef);
227//
228     for (uInt freqID=0; freqID<nFreqID; freqID++) {
229        SpectralCoordinate sC = in[0]->getCoordinate(freqID);
230        vA[freqID] = new VelocityAligner<Float>(sC, nChan, epoch, const MDirection& dir,
231                                                const MPosition& pos, const String& velUnit,
232                                                MDoppler::Types velType, MFrequency::Types velFreqSystem)
233     }
234  }
235*/
236
237// Loop over tables
238
239  Float fac = 1.0;
240  const uInt nTables = in.nelements();
241  for (uInt iTab=0; iTab<nTables; iTab++) {
242
243// Should check that the frequency tables don't change if doing VelocityAlignment
244
245// Attach columns to Table
246
247     const Table& tabIn = in[iTab]->table();
248     tSysCol.attach(tabIn, "TSYS");
249     mjdCol.attach(tabIn, "TIME");
250     srcNameCol.attach(tabIn, "SRCNAME");
251     intCol.attach(tabIn, "INTERVAL");
252     fqIDCol.attach(tabIn, "FREQID");
253
254// Loop over rows in Table
255
256     const uInt nRows = in[iTab]->nRow();
257     for (uInt iRow=0; iRow<nRows; iRow++) {
258
259// Check conformance
260
261        IPosition shp2 = in[iTab]->rowAsMaskedArray(iRow).shape();
262        if (!shp.isEqual(shp2)) {
263           throw (AipsError("Shapes for all rows must be the same"));
264        }
265
266// If we are not doing scan averages, make checks for source and
267// frequency setup and warn if averaging across them
268
269// Get copy of Scan Container for this row
270
271        SDContainer sc = in[iTab]->getSDContainer(iRow);
272        scanID = sc.scanid;
273
274// Get quantities from columns
275
276        srcNameCol.getScalar(iRow, sourceName);
277        mjdCol.get(iRow, time);
278        tSysCol.get(iRow, tSys);
279        intCol.get(iRow, interval);
280        fqIDCol.get(iRow, freqID);
281
282// Initialize first source and freqID
283
284        if (iRow==0 && iTab==0) {
285          sourceNameStart = sourceName;
286          freqIDStart = freqID;
287        }
288
289// If we are doing scan averages, see if we are at the end of an
290// accumulation period (scan).  We must check soutce names too,
291// since we might have two tables with one scan each but different
292// source names; we shouldn't average different sources together
293
294        if (scanAv && ( (scanID != oldScanID)  ||
295                        (iRow==0 && iTab>0 && sourceName!=oldSourceName))) {
296
297// Normalize data in 'sum' accumulation array according to weighting scheme
298
299           normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub);
300
301// Fill scan container. The source and freqID come from the
302// first row of the first table that went into this average (
303// should be the same for all rows in the scan average)
304
305           Float nR(nAccum);
306           fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID,
307                    timeSum/nR, intSum, sourceNameStart, freqIDStart);
308
309// Write container out to Table
310
311           pTabOut->putSDContainer(sc);
312
313// Reset accumulators
314
315           sum = 0.0;
316           sumSq = 0.0;
317           nAccum = 0;
318//
319           tSysSum =0.0;
320           timeSum = 0.0;
321           intSum = 0.0;
322           nPts = 0.0;
323
324// Increment
325
326           rowStart = iRow;              // First row for next accumulation
327           tableStart = iTab;            // First table for next accumulation
328           sourceNameStart = sourceName; // First source name for next accumulation
329           freqIDStart = freqID;         // First FreqID for next accumulation
330//
331           oldScanID = scanID;
332           outScanID += 1;               // Scan ID for next accumulation period
333        }
334
335// Accumulate
336
337        accumulate(timeSum, intSum, nAccum, sum, sumSq, nPts, tSysSum,
338                    tSys, nInc, mask, time, interval, in, iTab, iRow, asap::ChanAxis,
339                    nAxesSub, useMask, wtType);
340//
341       oldSourceName = sourceName;
342       oldFreqID = freqID;
343     }
344  }
345
346// OK at this point we have accumulation data which is either
347//   - accumulated from all tables into one row
348// or
349//   - accumulated from the last scan average
350//
351// Normalize data in 'sum' accumulation array according to weighting scheme
352  normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub);
353
354// Create and fill container.  The container we clone will be from
355// the last Table and the first row that went into the current
356// accumulation.  It probably doesn't matter that much really...
357
358  Float nR(nAccum);
359  SDContainer sc = in[tableStart]->getSDContainer(rowStart);
360  fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID,
361           timeSum/nR, intSum, sourceNameStart, freqIDStart);
362  pTabOut->putSDContainer(sc);
363//
364  return CountedPtr<SDMemTable>(pTabOut);
365}
366
367
368
369CountedPtr<SDMemTable> SDMath::quotient(const CountedPtr<SDMemTable>& on,
370                                        const CountedPtr<SDMemTable>& off,
371                                        Bool preserveContinuum)  const
372{
373  const uInt nRowOn = on->nRow();
374  const uInt nRowOff = off->nRow();
375  Bool ok = (nRowOff==1&&nRowOn>0) ||
376            (nRowOff>=1&&nRowOn==nRowOff);
377  if (!ok) {
378     throw (AipsError("The reference Scan Table can have one row or the same number of rows as the source Scan Table"));
379  }
380
381// Input Tables and columns
382
383  Table tabOn = on->table();
384  Table tabOff = off->table();
385  ROArrayColumn<Float> tSysOn(tabOn, "TSYS");
386  ROArrayColumn<Float> tSysOff(tabOff, "TSYS");
387
388// Output Table cloned from input
389
390  SDMemTable* pTabOut = new SDMemTable(*on, True);
391
392// Loop over rows
393
394  MaskedArray<Float>* pMOff = new MaskedArray<Float>(off->rowAsMaskedArray(0));
395  IPosition shpOff = pMOff->shape();
396//
397  Array<Float> tSysOnArr, tSysOffArr;
398  tSysOn.get(0, tSysOnArr);
399  tSysOff.get(0, tSysOffArr);
400//
401  for (uInt i=0; i<nRowOn; i++) {
402     MaskedArray<Float> mOn(on->rowAsMaskedArray(i));
403     IPosition shpOn = mOn.shape();
404     tSysOn.get(i, tSysOnArr);
405//
406     if (nRowOff>1) {
407        delete pMOff;
408        pMOff = new MaskedArray<Float>(off->rowAsMaskedArray(i));
409        shpOff = pMOff->shape();
410        tSysOff.get(i, tSysOffArr);
411     }
412
413// Conformance
414
415     if (!shpOn.isEqual(shpOff)) {
416        throw(AipsError("on/off data are not conformant"));
417     }
418     if (!tSysOnArr.shape().isEqual(tSysOffArr.shape())) {
419        throw(AipsError("on/off Tsys data are not conformant"));
420     }
421     if (!shpOn.isEqual(tSysOnArr.shape())) {
422        throw(AipsError("Correlation and Tsys data are not conformant"));
423     }
424
425// Get container
426
427     SDContainer sc = on->getSDContainer(i);
428
429// Compute and put quotient into container
430
431     if (preserveContinuum) {     
432        MaskedArray<Float> tmp = (tSysOffArr * mOn / *pMOff) - tSysOffArr;
433        putDataInSDC(sc, tmp.getArray(), tmp.getMask());
434     } else {
435        MaskedArray<Float> tmp = (tSysOffArr * mOn / *pMOff) - tSysOnArr;
436        putDataInSDC(sc, tmp.getArray(), tmp.getMask());
437     }
438     sc.putTsys(tSysOffArr);
439     sc.scanid = i;
440
441// Put new row in output Table
442 
443     pTabOut->putSDContainer(sc);
444  }
445  if (pMOff) delete pMOff;
446//
447  return CountedPtr<SDMemTable>(pTabOut);
448}
449
450
451CountedPtr<SDMemTable> SDMath::simpleBinaryOperate (const CountedPtr<SDMemTable>& left,
452                                                    const CountedPtr<SDMemTable>& right,
453                                                    const String& op)  const
454//
455// Simple binary Table operators. add, subtract, multiply, divide (what=0,1,2,3)
456//
457{
458
459// CHeck operator
460
461  String op2(op);
462  op2.upcase();
463  uInt what = 0;
464  if (op2=="ADD") {
465     what = 0;
466  } else if (op2=="SUB") {
467     what = 1;
468  } else if (op2=="MUL") {
469     what = 2;
470  } else if (op2=="DIV") {
471     what = 3;
472  } else {
473    throw AipsError("Unrecognized operation");
474  }
475
476// Check rows
477
478  const uInt nRows = left->nRow();
479  if (right->nRow() != nRows) {
480     throw (AipsError("Input Scan Tables must have the same number of rows"));
481  }
482
483// Input Tables and columns
484
485  const Table& tLeft = left->table();
486  const Table& tRight = right->table();
487//
488  ROArrayColumn<Float> tSysLeft(tLeft, "TSYS");
489  ROArrayColumn<Float> tSysRight(tRight, "TSYS");
490
491// Output Table cloned from input
492
493  SDMemTable* pTabOut = new SDMemTable(*left, True);
494
495// Loop over rows
496
497  for (uInt i=0; i<nRows; i++) {
498
499// Get data
500     MaskedArray<Float> mLeft(left->rowAsMaskedArray(i));
501     MaskedArray<Float> mRight(right->rowAsMaskedArray(i));
502//
503     IPosition shpLeft = mLeft.shape();
504     IPosition shpRight = mRight.shape();
505     if (!shpLeft.isEqual(shpRight)) {
506       throw(AipsError("left/right Scan Tables are not conformant"));
507     }
508
509// Get TSys
510
511     Array<Float> tSysLeftArr, tSysRightArr;
512     tSysLeft.get(i, tSysLeftArr);
513     tSysRight.get(i, tSysRightArr);
514
515// Make container
516
517     SDContainer sc = left->getSDContainer(i);
518
519// Operate on data and TSys
520
521     if (what==0) {                               
522        MaskedArray<Float> tmp = mLeft + mRight;
523        putDataInSDC(sc, tmp.getArray(), tmp.getMask());
524        sc.putTsys(tSysLeftArr+tSysRightArr);
525     } else if (what==1) {
526        MaskedArray<Float> tmp = mLeft - mRight;
527        putDataInSDC(sc, tmp.getArray(), tmp.getMask());
528        sc.putTsys(tSysLeftArr-tSysRightArr);
529     } else if (what==2) {
530        MaskedArray<Float> tmp = mLeft * mRight;
531        putDataInSDC(sc, tmp.getArray(), tmp.getMask());
532        sc.putTsys(tSysLeftArr*tSysRightArr);
533     } else if (what==3) {
534        MaskedArray<Float> tmp = mLeft / mRight;
535        putDataInSDC(sc, tmp.getArray(), tmp.getMask());
536        sc.putTsys(tSysLeftArr/tSysRightArr);
537     }
538
539// Put new row in output Table
540
541     pTabOut->putSDContainer(sc);
542  }
543//
544  return CountedPtr<SDMemTable>(pTabOut);
545}
546
547
548
549std::vector<float> SDMath::statistic(const CountedPtr<SDMemTable>& in,
550                                     const Vector<Bool>& mask,
551                                     const String& which, Int row) const
552//
553// Perhaps iteration over pol/beam/if should be in here
554// and inside the nrow iteration ?
555//
556{
557  const uInt nRow = in->nRow();
558
559// Specify cursor location
560
561  IPosition start, end;
562  getCursorLocation(start, end, *in);
563
564// Loop over rows
565
566  const uInt nEl = mask.nelements();
567  uInt iStart = 0;
568  uInt iEnd = in->nRow()-1;
569// 
570  if (row>=0) {
571     iStart = row;
572     iEnd = row;
573  }
574//
575  std::vector<float> result(iEnd-iStart+1);
576  for (uInt ii=iStart; ii <= iEnd; ++ii) {
577
578// Get row and deconstruct
579
580     MaskedArray<Float> marr(in->rowAsMaskedArray(ii));
581     Array<Float> arr = marr.getArray();
582     Array<Bool> barr = marr.getMask();
583
584// Access desired piece of data
585
586     Array<Float> v((arr(start,end)).nonDegenerate());
587     Array<Bool> m((barr(start,end)).nonDegenerate());
588
589// Apply OTF mask
590
591     MaskedArray<Float> tmp;
592     if (m.nelements()==nEl) {
593       tmp.setData(v,m&&mask);
594     } else {
595       tmp.setData(v,m);
596     }
597
598// Get statistic
599
600     result[ii-iStart] = mathutil::statistics(which, tmp);
601  }
602//
603  return result;
604}
605
606
607SDMemTable* SDMath::bin(const SDMemTable& in, Int width) const
608{
609  SDHeader sh = in.getSDHeader();
610  SDMemTable* pTabOut = new SDMemTable(in, True);
611
612// Bin up SpectralCoordinates
613
614  IPosition factors(1);
615  factors(0) = width;
616  for (uInt j=0; j<in.nCoordinates(); ++j) {
617    CoordinateSystem cSys;
618    cSys.addCoordinate(in.getCoordinate(j));
619    CoordinateSystem cSysBin =
620      CoordinateUtil::makeBinnedCoordinateSystem(factors, cSys, False);
621//
622    SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0);
623    pTabOut->setCoordinate(sCBin, j);
624  }
625
626// Use RebinLattice to find shape
627
628  IPosition shapeIn(1,sh.nchan);
629  IPosition shapeOut = RebinLattice<Float>::rebinShape(shapeIn, factors);
630  sh.nchan = shapeOut(0);
631  pTabOut->putSDHeader(sh);
632
633
634// Loop over rows and bin along channel axis
635 
636  for (uInt i=0; i < in.nRow(); ++i) {
637    SDContainer sc = in.getSDContainer(i);
638//
639    Array<Float> tSys(sc.getTsys());                           // Get it out before sc changes shape
640
641// Bin up spectrum
642
643    MaskedArray<Float> marr(in.rowAsMaskedArray(i));
644    MaskedArray<Float> marrout;
645    LatticeUtilities::bin(marrout, marr, asap::ChanAxis, width);
646
647// Put back the binned data and flags
648
649    IPosition ip2 = marrout.shape();
650    sc.resize(ip2);
651//
652    putDataInSDC(sc, marrout.getArray(), marrout.getMask());
653
654// Bin up Tsys. 
655
656    Array<Bool> allGood(tSys.shape(),True);
657    MaskedArray<Float> tSysIn(tSys, allGood, True);
658//
659    MaskedArray<Float> tSysOut;   
660    LatticeUtilities::bin(tSysOut, tSysIn, asap::ChanAxis, width);
661    sc.putTsys(tSysOut.getArray());
662//
663    pTabOut->putSDContainer(sc);
664  }
665  return pTabOut;
666}
667
668SDMemTable* SDMath::simpleOperate(const SDMemTable& in, Float val, Bool doAll,
669                                  uInt what) const
670//
671// what = 0   Multiply
672//        1   Add
673{
674   SDMemTable* pOut = new SDMemTable(in,False);
675   const Table& tOut = pOut->table();
676   ArrayColumn<Float> spec(tOut,"SPECTRA"); 
677//
678   if (doAll) {
679      for (uInt i=0; i < tOut.nrow(); i++) {
680
681// Get
682
683         MaskedArray<Float> marr(pOut->rowAsMaskedArray(i));
684
685// Operate
686
687         if (what==0) {
688            marr *= val;
689         } else if (what==1) {
690            marr += val;
691         }
692
693// Put
694
695         spec.put(i, marr.getArray());
696      }
697   } else {
698
699// Get cursor location
700
701      IPosition start, end;
702      getCursorLocation(start, end, in);
703//
704      for (uInt i=0; i < tOut.nrow(); i++) {
705
706// Get
707
708         MaskedArray<Float> dataIn(pOut->rowAsMaskedArray(i));
709
710// Modify. More work than we would like to deal with the mask
711
712         Array<Float>& values = dataIn.getRWArray();
713         Array<Bool> mask(dataIn.getMask());
714//
715         Array<Float> values2 = values(start,end);
716         Array<Bool> mask2 = mask(start,end);
717         MaskedArray<Float> t(values2,mask2);
718         if (what==0) {
719            t *= val;
720         } else if (what==1) {
721            t += val;
722         }
723         values(start, end) = t.getArray();     // Write back into 'dataIn'
724
725// Put
726         spec.put(i, dataIn.getArray());
727      }
728   }
729//
730   return pOut;
731}
732
733
734
735SDMemTable* SDMath::averagePol(const SDMemTable& in, const Vector<Bool>& mask) const
736//
737// Average all polarizations together, weighted by variance
738//
739{
740//   WeightType wtType = NONE;
741//   convertWeightString(wtType, weight);
742
743   const uInt nRows = in.nRow();
744   const uInt polAxis = asap::PolAxis;                     // Polarization axis
745   const uInt chanAxis = asap::ChanAxis;                    // Spectrum axis
746
747// Create output Table and reshape number of polarizations
748
749  Bool clear=True;
750  SDMemTable* pTabOut = new SDMemTable(in, clear);
751  SDHeader header = pTabOut->getSDHeader();
752  header.npol = 1;
753  pTabOut->putSDHeader(header);
754
755// Shape of input and output data
756
757  const IPosition& shapeIn = in.rowAsMaskedArray(0u, False).shape();
758  IPosition shapeOut(shapeIn);
759  shapeOut(polAxis) = 1;                          // Average all polarizations
760//
761  const uInt nChan = shapeIn(chanAxis);
762  const IPosition vecShapeOut(4,1,1,1,nChan);     // A multi-dim form of a Vector shape
763  IPosition start(4), end(4);
764
765// Output arrays
766
767  Array<Float> outData(shapeOut, 0.0);
768  Array<Bool> outMask(shapeOut, True);
769  const IPosition axes(2, 2, 3);              // pol-channel plane
770//
771  const Bool useMask = (mask.nelements() == shapeIn(chanAxis));
772
773// Loop over rows
774
775   for (uInt iRow=0; iRow<nRows; iRow++) {
776
777// Get data for this row
778
779      MaskedArray<Float> marr(in.rowAsMaskedArray(iRow));
780      Array<Float>& arr = marr.getRWArray();
781      const Array<Bool>& barr = marr.getMask();
782
783// Make iterators to iterate by pol-channel planes
784
785      ReadOnlyArrayIterator<Float> itDataPlane(arr, axes);
786      ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes);
787
788// Accumulations
789
790      Float fac = 1.0;
791      Vector<Float> vecSum(nChan,0.0);
792
793// Iterate through data by pol-channel planes
794
795      while (!itDataPlane.pastEnd()) {
796
797// Iterate through plane by polarization  and accumulate Vectors
798
799        Vector<Float> t1(nChan); t1 = 0.0;
800        Vector<Bool> t2(nChan); t2 = True;
801        MaskedArray<Float> vecSum(t1,t2);
802        Float varSum = 0.0;
803        {
804           ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1);
805           ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1);
806           while (!itDataVec.pastEnd()) {     
807
808// Create MA of data & mask (optionally including OTF mask) and  get variance
809
810              if (useMask) {
811                 const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector());
812                 fac = 1.0 / variance(spec);
813              } else {
814                 const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector());
815                 fac = 1.0 / variance(spec);
816              }
817
818// Normalize spectrum (without OTF mask) and accumulate
819
820              const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector());
821              vecSum += spec;
822              varSum += fac;
823
824// Next
825
826              itDataVec.next();
827              itMaskVec.next();
828           }
829        }
830
831// Normalize summed spectrum
832
833        vecSum /= varSum;
834
835// FInd position in input data array.  We are iterating by pol-channel
836// plane so all that will change is beam and IF and that's what we want.
837
838        IPosition pos = itDataPlane.pos();
839
840// Write out data. This is a bit messy. We have to reform the Vector
841// accumulator into an Array of shape (1,1,1,nChan)
842
843        start = pos;
844        end = pos;
845        end(chanAxis) = nChan-1;
846        outData(start,end) = vecSum.getArray().reform(vecShapeOut);
847        outMask(start,end) = vecSum.getMask().reform(vecShapeOut);
848
849// Step to next beam/IF combination
850
851        itDataPlane.next();
852        itMaskPlane.next();
853      }
854
855// Generate output container and write it to output table
856
857      SDContainer sc = in.getSDContainer();
858      sc.resize(shapeOut);
859//
860      putDataInSDC(sc, outData, outMask);
861      pTabOut->putSDContainer(sc);
862   }
863//
864  return pTabOut;
865}
866
867
868SDMemTable* SDMath::smooth(const SDMemTable& in,
869                           const casa::String& kernelType,
870                           casa::Float width, Bool doAll) const
871{
872
873// Number of channels
874
875   const uInt chanAxis = asap::ChanAxis;  // Spectral axis
876   SDHeader sh = in.getSDHeader();
877   const uInt nChan = sh.nchan;
878
879// Generate Kernel
880
881   VectorKernel::KernelTypes type = VectorKernel::toKernelType(kernelType);
882   Vector<Float> kernel = VectorKernel::make(type, width, nChan, True, False);
883
884// Generate Convolver
885
886   IPosition shape(1,nChan);
887   Convolver<Float> conv(kernel, shape);
888
889// New Table
890
891   SDMemTable* pTabOut = new SDMemTable(in,True);
892
893// Get cursor location
894         
895  IPosition start, end;
896  getCursorLocation(start, end, in);
897//
898  IPosition shapeOut(4,1);
899
900// Output Vectors
901
902  Vector<Float> valuesOut(nChan);
903  Vector<Bool> maskOut(nChan);
904
905// Loop over rows in Table
906
907  for (uInt ri=0; ri < in.nRow(); ++ri) {
908
909// Get copy of data
910   
911    const MaskedArray<Float>& dataIn(in.rowAsMaskedArray(ri));
912    AlwaysAssert(dataIn.shape()(chanAxis)==nChan, AipsError);
913//
914    Array<Float> valuesIn = dataIn.getArray();
915    Array<Bool> maskIn = dataIn.getMask();
916
917// Branch depending on whether we smooth all locations or just
918// those pointed at by the current selection cursor
919
920    if (doAll) {
921       uInt axis = asap::ChanAxis;
922       VectorIterator<Float> itValues(valuesIn, axis);
923       VectorIterator<Bool> itMask(maskIn, axis);
924       while (!itValues.pastEnd()) {
925
926// Smooth
927          if (kernelType==VectorKernel::HANNING) {
928             mathutil::hanning(valuesOut, maskOut, itValues.vector(), itMask.vector());
929             itMask.vector() = maskOut;
930          } else {
931             mathutil::replaceMaskByZero(itValues.vector(), itMask.vector());
932             conv.linearConv(valuesOut, itValues.vector());
933          }
934//
935          itValues.vector() = valuesOut;
936//
937          itValues.next();
938          itMask.next();
939       }
940    } else {
941
942// Set multi-dim Vector shape
943
944       shapeOut(chanAxis) = valuesIn.shape()(chanAxis);
945
946// Stuff about with shapes so that we don't have conformance run-time errors
947
948       Vector<Float> valuesIn2 = valuesIn(start,end).nonDegenerate();
949       Vector<Bool> maskIn2 = maskIn(start,end).nonDegenerate();
950
951// Smooth
952
953       if (kernelType==VectorKernel::HANNING) {
954          mathutil::hanning(valuesOut, maskOut, valuesIn2, maskIn2);
955          maskIn(start,end) = maskOut.reform(shapeOut);
956       } else {
957          mathutil::replaceMaskByZero(valuesIn2, maskIn2);
958          conv.linearConv(valuesOut, valuesIn2);
959       }
960//
961       valuesIn(start,end) = valuesOut.reform(shapeOut);
962    }
963
964// Create and put back
965
966    SDContainer sc = in.getSDContainer(ri);
967    putDataInSDC(sc, valuesIn, maskIn);
968//
969    pTabOut->putSDContainer(sc);
970  }
971//
972  return pTabOut;
973}
974
975
976SDMemTable* SDMath::convertFlux (const SDMemTable& in, Float a, Float eta, Bool doAll) const
977//
978// As it is, this function could be implemented with 'simpleOperate'
979// However, I anticipate that eventually we will look the conversion
980// values up in a Table and apply them in a frequency dependent way,
981// so I have implemented it fully here
982//
983{
984  SDHeader sh = in.getSDHeader();
985  SDMemTable* pTabOut = new SDMemTable(in, True);
986
987// FInd out how to convert values into Jy and K (e.g. units might be mJy or mK)
988// Also automatically find out what we are converting to according to the
989// flux unit
990
991  Unit fluxUnit(sh.fluxunit);
992  Unit K(String("K"));
993  Unit JY(String("Jy"));
994//
995  Bool toKelvin = True;
996  Double inFac = 1.0;
997  if (fluxUnit==JY) {
998     cerr << "Converting to K" << endl;
999//
1000     Quantum<Double> t(1.0,fluxUnit);
1001     Quantum<Double> t2 = t.get(JY);
1002     inFac = (t2 / t).getValue();
1003//
1004     toKelvin = True;
1005     sh.fluxunit = "K";
1006  } else if (fluxUnit==K) {
1007     cerr << "Converting to Jy" << endl;
1008//
1009     Quantum<Double> t(1.0,fluxUnit);
1010     Quantum<Double> t2 = t.get(K);
1011     inFac = (t2 / t).getValue();
1012//
1013     toKelvin = False;
1014     sh.fluxunit = "Jy";
1015  } else {
1016     throw AipsError("Unrecognized brightness units in Table - must be consistent with Jy or K");
1017  }
1018  pTabOut->putSDHeader(sh);
1019
1020// Compute conversion factor. 'a' and 'eta' are really frequency, time and 
1021// telescope dependent and should be looked// up in a table
1022
1023  Float factor = 2.0 * inFac * 1.0e-7 * 1.0e26 *
1024                 QC::k.getValue(Unit(String("erg/K"))) / a / eta;
1025  if (toKelvin) {
1026    factor = 1.0 / factor;
1027  }
1028  cerr << "Applying conversion factor = " << factor << endl;
1029
1030// For operations only on specified cursor location
1031
1032  IPosition start, end;
1033  getCursorLocation(start, end, in);
1034
1035// Loop over rows and apply factor to spectra
1036 
1037  const uInt axis = asap::ChanAxis;
1038  for (uInt i=0; i < in.nRow(); ++i) {
1039
1040// Get data
1041
1042    MaskedArray<Float> dataIn(in.rowAsMaskedArray(i));
1043    Array<Float>& valuesIn = dataIn.getRWArray();              // writable reference
1044    const Array<Bool>& maskIn = dataIn.getMask(); 
1045
1046// Need to apply correct conversion factor (frequency and time dependent)
1047// which should be sourced from a Table. For now we just apply the given
1048// factor to everything
1049
1050    if (doAll) {
1051       VectorIterator<Float> itValues(valuesIn, asap::ChanAxis);
1052       while (!itValues.pastEnd()) {
1053          itValues.vector() *= factor;                            // Writes back into dataIn
1054//
1055          itValues.next();
1056       }
1057    } else {
1058       Array<Float> valuesIn2 = valuesIn(start,end);
1059       valuesIn2 *= factor;
1060       valuesIn(start,end) = valuesIn2;
1061    }
1062
1063// Write out
1064
1065    SDContainer sc = in.getSDContainer(i);
1066    putDataInSDC(sc, valuesIn, maskIn);
1067//
1068    pTabOut->putSDContainer(sc);
1069  }
1070  return pTabOut;
1071}
1072
1073
1074
1075SDMemTable* SDMath::gainElevation (const SDMemTable& in, const Vector<Float>& coeffs,
1076                                   const String& fileName,
1077                                   const String& methodStr, Bool doAll) const
1078{
1079
1080// Get header and clone output table
1081
1082  SDHeader sh = in.getSDHeader();
1083  SDMemTable* pTabOut = new SDMemTable(in, True);
1084
1085// Get elevation data from SDMemTable and convert to degrees
1086
1087  const Table& tab = in.table();
1088  ROScalarColumn<Float> elev(tab, "ELEVATION");
1089  Vector<Float> x = elev.getColumn();
1090  x *= Float(180 / C::pi);
1091//
1092  const uInt nC = coeffs.nelements();
1093  if (fileName.length()>0 && nC>0) {
1094     throw AipsError("You must choose either polynomial coefficients or an ascii file, not both");
1095  }
1096
1097// Correct
1098
1099  if (nC>0 || fileName.length()==0) {
1100
1101// Find instrument
1102
1103     Bool throwIt = True;
1104     Instrument inst = SDMemTable::convertInstrument (sh.antennaname, throwIt);
1105     
1106// Set polynomial
1107
1108     Polynomial<Float>* pPoly = 0;
1109     Vector<Float> coeff;
1110     String msg;
1111     if (nC>0) {
1112        pPoly = new Polynomial<Float>(nC);
1113        coeff = coeffs;
1114        msg = String("user");
1115     } else {
1116        if (inst==PKSMULTIBEAM) {
1117        } else if (inst==PKSSINGLEBEAM) {
1118        } else if (inst==TIDBINBILLA) {
1119           pPoly = new Polynomial<Float>(3);
1120           coeff.resize(3);
1121           coeff(0) = 3.58788e-1;
1122           coeff(1) = 2.87243e-2;
1123           coeff(2) = -3.219093e-4;
1124        } else if (inst==MOPRA) {
1125        }
1126        msg = String("built in");
1127     }
1128//
1129     if (coeff.nelements()>0) {
1130        pPoly->setCoefficients(coeff);
1131     } else {
1132        throw AipsError("There is no known gain-el polynomial known for this instrument");
1133     }
1134//
1135     cerr << "Making polynomial correction with " << msg << " coefficients" << endl;
1136     const uInt nRow = in.nRow();
1137     Vector<Float> factor(nRow);
1138     for (uInt i=0; i<nRow; i++) {
1139        factor[i] = (*pPoly)(x[i]);
1140     }
1141     delete pPoly;
1142//
1143     correctFromVector (pTabOut, in, doAll, factor);
1144  } else {
1145
1146// Indicate which columns to read from ascii file
1147
1148     String col0("ELEVATION");
1149     String col1("FACTOR");
1150
1151// Read and correct
1152
1153     cerr << "Making correction from ascii Table" << endl;
1154     correctFromAsciiTable (pTabOut, in, fileName, col0, col1,
1155                            methodStr, doAll, x);
1156   }
1157//
1158   return pTabOut;
1159}
1160
1161 
1162
1163SDMemTable* SDMath::opacity (const SDMemTable& in, Float tau, Bool doAll) const
1164{
1165
1166// Get header and clone output table
1167
1168  SDHeader sh = in.getSDHeader();
1169  SDMemTable* pTabOut = new SDMemTable(in, True);
1170
1171// Get elevation data from SDMemTable and convert to degrees
1172
1173  const Table& tab = in.table();
1174  ROScalarColumn<Float> elev(tab, "ELEVATION");
1175  Vector<Float> zDist = elev.getColumn();
1176  zDist = Float(C::pi_2) - zDist;
1177
1178// Generate correction factor
1179
1180  const uInt nRow = in.nRow();
1181  Vector<Float> factor(nRow);
1182  Vector<Float> factor2(nRow);
1183  for (uInt i=0; i<nRow; i++) {
1184     factor[i] = exp(tau)/cos(zDist[i]);
1185  }
1186
1187// Correct
1188
1189  correctFromVector (pTabOut, in, doAll, factor);
1190//
1191  return pTabOut;
1192}
1193
1194
1195
1196
1197// 'private' functions
1198
1199void SDMath::fillSDC(SDContainer& sc,
1200                     const Array<Bool>& mask,
1201                     const Array<Float>& data,
1202                     const Array<Float>& tSys,
1203                     Int scanID, Double timeStamp,
1204                     Double interval, const String& sourceName,
1205                     const Vector<uInt>& freqID) const
1206{
1207// Data and mask
1208
1209  putDataInSDC(sc, data, mask);
1210
1211// TSys
1212
1213  sc.putTsys(tSys);
1214
1215// Time things
1216
1217  sc.timestamp = timeStamp;
1218  sc.interval = interval;
1219  sc.scanid = scanID;
1220//
1221  sc.sourcename = sourceName;
1222  sc.putFreqMap(freqID);
1223}
1224
1225void SDMath::normalize(MaskedArray<Float>& sum,
1226                        const Array<Float>& sumSq,
1227                        const Array<Float>& nPts,
1228                        WeightType wtType, Int axis,
1229                        Int nAxesSub) const
1230{
1231   IPosition pos2(nAxesSub,0);
1232//
1233   if (wtType==NONE) {
1234
1235// We just average by the number of points accumulated.
1236// We need to make a MA out of nPts so that no divide by
1237// zeros occur
1238
1239      MaskedArray<Float> t(nPts, (nPts>Float(0.0)));
1240      sum /= t;
1241   } else if (wtType==VAR) {
1242
1243// Normalize each spectrum by sum(1/var) where the variance
1244// is worked out for each spectrum
1245
1246      Array<Float>& data = sum.getRWArray();
1247      VectorIterator<Float> itData(data, axis);
1248      while (!itData.pastEnd()) {
1249         pos2 = itData.pos().getFirst(nAxesSub);
1250         itData.vector() /= sumSq(pos2);
1251         itData.next();
1252      }
1253   } else if (wtType==TSYS) {
1254   }
1255}
1256
1257
1258void SDMath::accumulate(Double& timeSum, Double& intSum, Int& nAccum,
1259                        MaskedArray<Float>& sum, Array<Float>& sumSq,
1260                        Array<Float>& nPts, Array<Float>& tSysSum,
1261                        const Array<Float>& tSys, const Array<Float>& nInc,
1262                        const Vector<Bool>& mask, Double time, Double interval,
1263                        const Block<CountedPtr<SDMemTable> >& in,
1264                        uInt iTab, uInt iRow, uInt axis,
1265                        uInt nAxesSub, Bool useMask,
1266                        WeightType wtType) const
1267{
1268
1269// Get data
1270
1271   MaskedArray<Float> dataIn(in[iTab]->rowAsMaskedArray(iRow));
1272   Array<Float>& valuesIn = dataIn.getRWArray();           // writable reference
1273   const Array<Bool>& maskIn = dataIn.getMask();          // RO reference
1274//
1275   if (wtType==NONE) {
1276      const MaskedArray<Float> n(nInc,dataIn.getMask());
1277      nPts += n;                               // Only accumulates where mask==T
1278   } else if (wtType==VAR) {
1279
1280// We are going to average the data, weighted by the noise for each pol, beam and IF.
1281// So therefore we need to iterate through by spectrum (axis 3)
1282
1283      VectorIterator<Float> itData(valuesIn, axis);
1284      ReadOnlyVectorIterator<Bool> itMask(maskIn, axis);
1285      Float fac = 1.0;
1286      IPosition pos(nAxesSub,0); 
1287//
1288      while (!itData.pastEnd()) {
1289
1290// Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor
1291
1292        if (useMask) {
1293           MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector());
1294           fac = 1.0/variance(tmp);
1295        } else {
1296           MaskedArray<Float> tmp(itData.vector(),itMask.vector());
1297           fac = 1.0/variance(tmp);
1298        }
1299
1300// Scale data
1301
1302        itData.vector() *= fac;     // Writes back into 'dataIn'
1303//
1304// Accumulate variance per if/pol/beam averaged over spectrum
1305// This method to get pos2 from itData.pos() is only valid
1306// because the spectral axis is the last one (so we can just
1307// copy the first nAXesSub positions out)
1308
1309        pos = itData.pos().getFirst(nAxesSub);
1310        sumSq(pos) += fac;
1311//
1312        itData.next();
1313        itMask.next();
1314      }
1315   } else if (wtType==TSYS) {
1316   }
1317
1318// Accumulate sum of (possibly scaled) data
1319
1320   sum += dataIn;
1321
1322// Accumulate Tsys, time, and interval
1323
1324   tSysSum += tSys;
1325   timeSum += time;
1326   intSum += interval;
1327   nAccum += 1;
1328}
1329
1330
1331
1332
1333void SDMath::getCursorLocation(IPosition& start, IPosition& end,
1334                               const SDMemTable& in) const
1335{
1336  const uInt nDim = 4;
1337  const uInt i = in.getBeam();
1338  const uInt j = in.getIF();
1339  const uInt k = in.getPol();
1340  const uInt n = in.nChan();
1341//
1342  start.resize(nDim);
1343  start(0) = i;
1344  start(1) = j;
1345  start(2) = k;
1346  start(3) = 0;
1347//
1348  end.resize(nDim);
1349  end(0) = i;
1350  end(1) = j;
1351  end(2) = k;
1352  end(3) = n-1;
1353}
1354
1355
1356void SDMath::convertWeightString(WeightType& wtType, const String& weightStr) const
1357{
1358  String tStr(weightStr);
1359  tStr.upcase();
1360  if (tStr.contains(String("NONE"))) {
1361     wtType = NONE;
1362  } else if (tStr.contains(String("VAR"))) {
1363     wtType = VAR;
1364  } else if (tStr.contains(String("TSYS"))) {
1365     wtType = TSYS;
1366     throw(AipsError("T_sys weighting not yet implemented"));
1367  } else {
1368    throw(AipsError("Unrecognized weighting type"));
1369  }
1370}
1371
1372void SDMath::convertInterpString(Int& type, const String& interp) const
1373{
1374  String tStr(interp);
1375  tStr.upcase();
1376  if (tStr.contains(String("NEAR"))) {
1377     type = InterpolateArray1D<Float,Float>::nearestNeighbour;
1378  } else if (tStr.contains(String("LIN"))) {
1379     type = InterpolateArray1D<Float,Float>::linear;
1380  } else if (tStr.contains(String("CUB"))) {
1381     type = InterpolateArray1D<Float,Float>::cubic;
1382  } else if (tStr.contains(String("SPL"))) {
1383     type = InterpolateArray1D<Float,Float>::spline;
1384  } else {
1385    throw(AipsError("Unrecognized interpolation type"));
1386  }
1387}
1388
1389void SDMath::putDataInSDC(SDContainer& sc, const Array<Float>& data,
1390                          const Array<Bool>& mask) const
1391{
1392    sc.putSpectrum(data);
1393//
1394    Array<uChar> outflags(data.shape());
1395    convertArray(outflags,!mask);
1396    sc.putFlags(outflags);
1397}
1398
1399Table SDMath::readAsciiFile (const String& fileName) const
1400{
1401   String formatString;
1402   Table tbl = readAsciiTable (formatString, Table::Memory, fileName, "", "", False);
1403   return tbl;
1404}
1405
1406
1407
1408void SDMath::correctFromAsciiTable(SDMemTable* pTabOut,
1409                                   const SDMemTable& in, const String& fileName,
1410                                   const String& col0, const String& col1,
1411                                   const String& methodStr, Bool doAll,
1412                                   const Vector<Float>& xOut) const
1413{
1414
1415// Read gain-elevation ascii file data into a Table.
1416
1417  Table geTable = readAsciiFile (fileName);
1418//
1419  correctFromTable (pTabOut, in, geTable, col0, col1, methodStr, doAll, xOut);
1420}
1421
1422void SDMath::correctFromTable(SDMemTable* pTabOut, const SDMemTable& in,
1423                              const Table& tTable, const String& col0,
1424                              const String& col1,
1425                              const String& methodStr, Bool doAll,
1426                              const Vector<Float>& xOut) const
1427{
1428
1429// Get data from Table
1430
1431  ROScalarColumn<Float> geElCol(tTable, col0);
1432  ROScalarColumn<Float> geFacCol(tTable, col1);
1433  Vector<Float> xIn = geElCol.getColumn();
1434  Vector<Float> yIn = geFacCol.getColumn();
1435  Vector<Bool> maskIn(xIn.nelements(),True);
1436
1437// Interpolate (and extrapolate) with desired method
1438
1439   Int method = 0;
1440   convertInterpString(method, methodStr);
1441//
1442   Vector<Float> yOut;
1443   Vector<Bool> maskOut;
1444   InterpolateArray1D<Float,Float>::interpolate(yOut, maskOut, xOut,
1445                                                xIn, yIn, maskIn, method,
1446                                                True, True);
1447// Apply
1448
1449   correctFromVector (pTabOut, in, doAll, yOut);
1450}
1451
1452
1453void SDMath::correctFromVector (SDMemTable* pTabOut, const SDMemTable& in,
1454                                Bool doAll, const Vector<Float>& factor) const
1455{
1456// For operations only on specified cursor location
1457
1458  IPosition start, end;
1459  getCursorLocation(start, end, in);
1460
1461// Loop over rows and interpolate correction factor
1462 
1463  const uInt axis = asap::ChanAxis;
1464  for (uInt i=0; i < in.nRow(); ++i) {
1465
1466// Get data
1467
1468    MaskedArray<Float> dataIn(in.rowAsMaskedArray(i));
1469    Array<Float>& valuesIn = dataIn.getRWArray(); 
1470    const Array<Bool>& maskIn = dataIn.getMask(); 
1471
1472// Apply factor
1473
1474    if (doAll) {
1475       VectorIterator<Float> itValues(valuesIn, asap::ChanAxis);
1476       while (!itValues.pastEnd()) {
1477          itValues.vector() *= factor(i);
1478          itValues.next();
1479       }
1480    } else {
1481       Array<Float> valuesIn2 = valuesIn(start,end);
1482       valuesIn2 *= factor(i);
1483       valuesIn(start,end) = valuesIn2;
1484    }
1485
1486// Write out
1487
1488    SDContainer sc = in.getSDContainer(i);
1489    putDataInSDC(sc, valuesIn, maskIn);
1490//
1491    pTabOut->putSDContainer(sc);
1492  }
1493}
1494
1495
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