source: trunk/src/SDMath.cc@ 241

Last change on this file since 241 was 234, checked in by kil064, 20 years ago

add binary table operation
add opacity
rework gain-elevation to handle polynomials

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 40.1 KB
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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 (nRowOn>0&&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//
405 if (nRowOff>1) {
406 delete pMOff;
407 pMOff = new MaskedArray<Float>(off->rowAsMaskedArray(i));
408 shpOff = pMOff->shape();
409 if (!shpOn.isEqual(shpOff)) {
410 throw(AipsError("on/off data are not conformant"));
411 }
412//
413 tSysOff.get(i, tSysOffArr);
414 tSysOn.get(i, tSysOnArr);
415 if (!tSysOnArr.shape().isEqual(tSysOffArr.shape())) {
416 throw(AipsError("on/off Tsys data are not conformant"));
417 }
418//
419 if (!shpOn.isEqual(tSysOnArr.shape())) {
420 throw(AipsError("Correlation and Tsys data are not conformant"));
421 }
422 }
423
424// Compute quotient
425
426 MaskedArray<Float> tmp = (mOn-*pMOff);
427 Array<Float> out(tmp.getArray());
428 out /= *pMOff;
429 out *= tSysOffArr;
430
431// MaskedArray<Float> tmp2 = (tSysOnArr * mOn / *pMOff) - tSysOffArr;
432
433
434// Fill container for this row
435
436 SDContainer sc = on->getSDContainer(i);
437//
438 putDataInSDC(sc, out, tmp.getMask());
439 sc.putTsys(tSysOffArr);
440 sc.scanid = i;
441
442// Put new row in output Table
443
444 pTabOut->putSDContainer(sc);
445 }
446 if (pMOff) delete pMOff;
447//
448 return CountedPtr<SDMemTable>(pTabOut);
449}
450
451
452CountedPtr<SDMemTable> SDMath::simpleBinaryOperate (const CountedPtr<SDMemTable>& left,
453 const CountedPtr<SDMemTable>& right,
454 const String& op) const
455//
456// Simple binary Table operators. add, subtract, multiply, divide (what=0,1,2,3)
457//
458{
459
460// CHeck operator
461
462 String op2(op);
463 op2.upcase();
464 uInt what = 0;
465 if (op2=="ADD") {
466 what = 0;
467 } else if (op2=="SUB") {
468 what = 1;
469 } else if (op2=="MUL") {
470 what = 2;
471 } else if (op2=="DIV") {
472 what = 3;
473 } else {
474 throw AipsError("Unrecognized operation");
475 }
476
477// Check rows
478
479 const uInt nRows = left->nRow();
480 if (right->nRow() != nRows) {
481 throw (AipsError("Input Scan Tables must have the same number of rows"));
482 }
483
484// Input Tables and columns
485
486 const Table& tLeft = left->table();
487 const Table& tRight = right->table();
488//
489 ROArrayColumn<Float> tSysLeft(tLeft, "TSYS");
490 ROArrayColumn<Float> tSysRight(tRight, "TSYS");
491
492// Output Table cloned from input
493
494 SDMemTable* pTabOut = new SDMemTable(*left, True);
495
496// Loop over rows
497
498 for (uInt i=0; i<nRows; i++) {
499
500// Get data
501 MaskedArray<Float> mLeft(left->rowAsMaskedArray(i));
502 MaskedArray<Float> mRight(right->rowAsMaskedArray(i));
503//
504 IPosition shpLeft = mLeft.shape();
505 IPosition shpRight = mRight.shape();
506 if (!shpLeft.isEqual(shpRight)) {
507 throw(AipsError("left/right Scan Tables are not conformant"));
508 }
509
510// Get TSys
511
512 Array<Float> tSysLeftArr, tSysRightArr;
513 tSysLeft.get(i, tSysLeftArr);
514 tSysRight.get(i, tSysRightArr);
515
516// Make container
517
518 SDContainer sc = left->getSDContainer(i);
519
520// Operate on data and TSys
521
522 if (what==0) {
523 MaskedArray<Float> tmp = mLeft + mRight;
524 putDataInSDC(sc, tmp.getArray(), tmp.getMask());
525 sc.putTsys(tSysLeftArr+tSysRightArr);
526 } else if (what==1) {
527 MaskedArray<Float> tmp = mLeft - mRight;
528 putDataInSDC(sc, tmp.getArray(), tmp.getMask());
529 sc.putTsys(tSysLeftArr-tSysRightArr);
530 } else if (what==2) {
531 MaskedArray<Float> tmp = mLeft * mRight;
532 putDataInSDC(sc, tmp.getArray(), tmp.getMask());
533 sc.putTsys(tSysLeftArr*tSysRightArr);
534 } else if (what==3) {
535 MaskedArray<Float> tmp = mLeft / mRight;
536 putDataInSDC(sc, tmp.getArray(), tmp.getMask());
537 sc.putTsys(tSysLeftArr/tSysRightArr);
538 }
539
540// Put new row in output Table
541
542 pTabOut->putSDContainer(sc);
543 }
544//
545 return CountedPtr<SDMemTable>(pTabOut);
546}
547
548
549
550std::vector<float> SDMath::statistic(const CountedPtr<SDMemTable>& in,
551 const Vector<Bool>& mask,
552 const String& which, Int row) const
553//
554// Perhaps iteration over pol/beam/if should be in here
555// and inside the nrow iteration ?
556//
557{
558 const uInt nRow = in->nRow();
559
560// Specify cursor location
561
562 IPosition start, end;
563 getCursorLocation(start, end, *in);
564
565// Loop over rows
566
567 const uInt nEl = mask.nelements();
568 uInt iStart = 0;
569 uInt iEnd = in->nRow()-1;
570//
571 if (row>=0) {
572 iStart = row;
573 iEnd = row;
574 }
575//
576 std::vector<float> result(iEnd-iStart+1);
577 for (uInt ii=iStart; ii <= iEnd; ++ii) {
578
579// Get row and deconstruct
580
581 MaskedArray<Float> marr(in->rowAsMaskedArray(ii));
582 Array<Float> arr = marr.getArray();
583 Array<Bool> barr = marr.getMask();
584
585// Access desired piece of data
586
587 Array<Float> v((arr(start,end)).nonDegenerate());
588 Array<Bool> m((barr(start,end)).nonDegenerate());
589
590// Apply OTF mask
591
592 MaskedArray<Float> tmp;
593 if (m.nelements()==nEl) {
594 tmp.setData(v,m&&mask);
595 } else {
596 tmp.setData(v,m);
597 }
598
599// Get statistic
600
601 result[ii-iStart] = mathutil::statistics(which, tmp);
602 }
603//
604 return result;
605}
606
607
608SDMemTable* SDMath::bin(const SDMemTable& in, Int width) const
609{
610 SDHeader sh = in.getSDHeader();
611 SDMemTable* pTabOut = new SDMemTable(in, True);
612
613// Bin up SpectralCoordinates
614
615 IPosition factors(1);
616 factors(0) = width;
617 for (uInt j=0; j<in.nCoordinates(); ++j) {
618 CoordinateSystem cSys;
619 cSys.addCoordinate(in.getCoordinate(j));
620 CoordinateSystem cSysBin =
621 CoordinateUtil::makeBinnedCoordinateSystem(factors, cSys, False);
622//
623 SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0);
624 pTabOut->setCoordinate(sCBin, j);
625 }
626
627// Use RebinLattice to find shape
628
629 IPosition shapeIn(1,sh.nchan);
630 IPosition shapeOut = RebinLattice<Float>::rebinShape(shapeIn, factors);
631 sh.nchan = shapeOut(0);
632 pTabOut->putSDHeader(sh);
633
634
635// Loop over rows and bin along channel axis
636
637 for (uInt i=0; i < in.nRow(); ++i) {
638 SDContainer sc = in.getSDContainer(i);
639//
640 Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape
641
642// Bin up spectrum
643
644 MaskedArray<Float> marr(in.rowAsMaskedArray(i));
645 MaskedArray<Float> marrout;
646 LatticeUtilities::bin(marrout, marr, asap::ChanAxis, width);
647
648// Put back the binned data and flags
649
650 IPosition ip2 = marrout.shape();
651 sc.resize(ip2);
652//
653 putDataInSDC(sc, marrout.getArray(), marrout.getMask());
654
655// Bin up Tsys.
656
657 Array<Bool> allGood(tSys.shape(),True);
658 MaskedArray<Float> tSysIn(tSys, allGood, True);
659//
660 MaskedArray<Float> tSysOut;
661 LatticeUtilities::bin(tSysOut, tSysIn, asap::ChanAxis, width);
662 sc.putTsys(tSysOut.getArray());
663//
664 pTabOut->putSDContainer(sc);
665 }
666 return pTabOut;
667}
668
669SDMemTable* SDMath::simpleOperate(const SDMemTable& in, Float val, Bool doAll,
670 uInt what) const
671//
672// what = 0 Multiply
673// 1 Add
674{
675 SDMemTable* pOut = new SDMemTable(in,False);
676 const Table& tOut = pOut->table();
677 ArrayColumn<Float> spec(tOut,"SPECTRA");
678//
679 if (doAll) {
680 for (uInt i=0; i < tOut.nrow(); i++) {
681
682// Get
683
684 MaskedArray<Float> marr(pOut->rowAsMaskedArray(i));
685
686// Operate
687
688 if (what==0) {
689 marr *= val;
690 } else if (what==1) {
691 marr += val;
692 }
693
694// Put
695
696 spec.put(i, marr.getArray());
697 }
698 } else {
699
700// Get cursor location
701
702 IPosition start, end;
703 getCursorLocation(start, end, in);
704//
705 for (uInt i=0; i < tOut.nrow(); i++) {
706
707// Get
708
709 MaskedArray<Float> dataIn(pOut->rowAsMaskedArray(i));
710
711// Modify. More work than we would like to deal with the mask
712
713 Array<Float>& values = dataIn.getRWArray();
714 Array<Bool> mask(dataIn.getMask());
715//
716 Array<Float> values2 = values(start,end);
717 Array<Bool> mask2 = mask(start,end);
718 MaskedArray<Float> t(values2,mask2);
719 if (what==0) {
720 t *= val;
721 } else if (what==1) {
722 t += val;
723 }
724 values(start, end) = t.getArray(); // Write back into 'dataIn'
725
726// Put
727 spec.put(i, dataIn.getArray());
728 }
729 }
730//
731 return pOut;
732}
733
734
735
736SDMemTable* SDMath::averagePol(const SDMemTable& in, const Vector<Bool>& mask) const
737//
738// Average all polarizations together, weighted by variance
739//
740{
741// WeightType wtType = NONE;
742// convertWeightString(wtType, weight);
743
744 const uInt nRows = in.nRow();
745 const uInt polAxis = asap::PolAxis; // Polarization axis
746 const uInt chanAxis = asap::ChanAxis; // Spectrum axis
747
748// Create output Table and reshape number of polarizations
749
750 Bool clear=True;
751 SDMemTable* pTabOut = new SDMemTable(in, clear);
752 SDHeader header = pTabOut->getSDHeader();
753 header.npol = 1;
754 pTabOut->putSDHeader(header);
755
756// Shape of input and output data
757
758 const IPosition& shapeIn = in.rowAsMaskedArray(0u, False).shape();
759 IPosition shapeOut(shapeIn);
760 shapeOut(polAxis) = 1; // Average all polarizations
761//
762 const uInt nChan = shapeIn(chanAxis);
763 const IPosition vecShapeOut(4,1,1,1,nChan); // A multi-dim form of a Vector shape
764 IPosition start(4), end(4);
765
766// Output arrays
767
768 Array<Float> outData(shapeOut, 0.0);
769 Array<Bool> outMask(shapeOut, True);
770 const IPosition axes(2, 2, 3); // pol-channel plane
771//
772 const Bool useMask = (mask.nelements() == shapeIn(chanAxis));
773
774// Loop over rows
775
776 for (uInt iRow=0; iRow<nRows; iRow++) {
777
778// Get data for this row
779
780 MaskedArray<Float> marr(in.rowAsMaskedArray(iRow));
781 Array<Float>& arr = marr.getRWArray();
782 const Array<Bool>& barr = marr.getMask();
783
784// Make iterators to iterate by pol-channel planes
785
786 ReadOnlyArrayIterator<Float> itDataPlane(arr, axes);
787 ReadOnlyArrayIterator<Bool> itMaskPlane(barr, axes);
788
789// Accumulations
790
791 Float fac = 1.0;
792 Vector<Float> vecSum(nChan,0.0);
793
794// Iterate through data by pol-channel planes
795
796 while (!itDataPlane.pastEnd()) {
797
798// Iterate through plane by polarization and accumulate Vectors
799
800 Vector<Float> t1(nChan); t1 = 0.0;
801 Vector<Bool> t2(nChan); t2 = True;
802 MaskedArray<Float> vecSum(t1,t2);
803 Float varSum = 0.0;
804 {
805 ReadOnlyVectorIterator<Float> itDataVec(itDataPlane.array(), 1);
806 ReadOnlyVectorIterator<Bool> itMaskVec(itMaskPlane.array(), 1);
807 while (!itDataVec.pastEnd()) {
808
809// Create MA of data & mask (optionally including OTF mask) and get variance
810
811 if (useMask) {
812 const MaskedArray<Float> spec(itDataVec.vector(),mask&&itMaskVec.vector());
813 fac = 1.0 / variance(spec);
814 } else {
815 const MaskedArray<Float> spec(itDataVec.vector(),itMaskVec.vector());
816 fac = 1.0 / variance(spec);
817 }
818
819// Normalize spectrum (without OTF mask) and accumulate
820
821 const MaskedArray<Float> spec(fac*itDataVec.vector(), itMaskVec.vector());
822 vecSum += spec;
823 varSum += fac;
824
825// Next
826
827 itDataVec.next();
828 itMaskVec.next();
829 }
830 }
831
832// Normalize summed spectrum
833
834 vecSum /= varSum;
835
836// FInd position in input data array. We are iterating by pol-channel
837// plane so all that will change is beam and IF and that's what we want.
838
839 IPosition pos = itDataPlane.pos();
840
841// Write out data. This is a bit messy. We have to reform the Vector
842// accumulator into an Array of shape (1,1,1,nChan)
843
844 start = pos;
845 end = pos;
846 end(chanAxis) = nChan-1;
847 outData(start,end) = vecSum.getArray().reform(vecShapeOut);
848 outMask(start,end) = vecSum.getMask().reform(vecShapeOut);
849
850// Step to next beam/IF combination
851
852 itDataPlane.next();
853 itMaskPlane.next();
854 }
855
856// Generate output container and write it to output table
857
858 SDContainer sc = in.getSDContainer();
859 sc.resize(shapeOut);
860//
861 putDataInSDC(sc, outData, outMask);
862 pTabOut->putSDContainer(sc);
863 }
864//
865 return pTabOut;
866}
867
868
869SDMemTable* SDMath::smooth(const SDMemTable& in,
870 const casa::String& kernelType,
871 casa::Float width, Bool doAll) const
872{
873
874// Number of channels
875
876 const uInt chanAxis = asap::ChanAxis; // Spectral axis
877 SDHeader sh = in.getSDHeader();
878 const uInt nChan = sh.nchan;
879
880// Generate Kernel
881
882 VectorKernel::KernelTypes type = VectorKernel::toKernelType(kernelType);
883 Vector<Float> kernel = VectorKernel::make(type, width, nChan, True, False);
884
885// Generate Convolver
886
887 IPosition shape(1,nChan);
888 Convolver<Float> conv(kernel, shape);
889
890// New Table
891
892 SDMemTable* pTabOut = new SDMemTable(in,True);
893
894// Get cursor location
895
896 IPosition start, end;
897 getCursorLocation(start, end, in);
898//
899 IPosition shapeOut(4,1);
900
901// Output Vectors
902
903 Vector<Float> valuesOut(nChan);
904 Vector<Bool> maskOut(nChan);
905
906// Loop over rows in Table
907
908 for (uInt ri=0; ri < in.nRow(); ++ri) {
909
910// Get copy of data
911
912 const MaskedArray<Float>& dataIn(in.rowAsMaskedArray(ri));
913 AlwaysAssert(dataIn.shape()(chanAxis)==nChan, AipsError);
914//
915 Array<Float> valuesIn = dataIn.getArray();
916 Array<Bool> maskIn = dataIn.getMask();
917
918// Branch depending on whether we smooth all locations or just
919// those pointed at by the current selection cursor
920
921 if (doAll) {
922 uInt axis = asap::ChanAxis;
923 VectorIterator<Float> itValues(valuesIn, axis);
924 VectorIterator<Bool> itMask(maskIn, axis);
925 while (!itValues.pastEnd()) {
926
927// Smooth
928 if (kernelType==VectorKernel::HANNING) {
929 mathutil::hanning(valuesOut, maskOut, itValues.vector(), itMask.vector());
930 itMask.vector() = maskOut;
931 } else {
932 mathutil::replaceMaskByZero(itValues.vector(), itMask.vector());
933 conv.linearConv(valuesOut, itValues.vector());
934 }
935//
936 itValues.vector() = valuesOut;
937//
938 itValues.next();
939 itMask.next();
940 }
941 } else {
942
943// Set multi-dim Vector shape
944
945 shapeOut(chanAxis) = valuesIn.shape()(chanAxis);
946
947// Stuff about with shapes so that we don't have conformance run-time errors
948
949 Vector<Float> valuesIn2 = valuesIn(start,end).nonDegenerate();
950 Vector<Bool> maskIn2 = maskIn(start,end).nonDegenerate();
951
952// Smooth
953
954 if (kernelType==VectorKernel::HANNING) {
955 mathutil::hanning(valuesOut, maskOut, valuesIn2, maskIn2);
956 maskIn(start,end) = maskOut.reform(shapeOut);
957 } else {
958 mathutil::replaceMaskByZero(valuesIn2, maskIn2);
959 conv.linearConv(valuesOut, valuesIn2);
960 }
961//
962 valuesIn(start,end) = valuesOut.reform(shapeOut);
963 }
964
965// Create and put back
966
967 SDContainer sc = in.getSDContainer(ri);
968 putDataInSDC(sc, valuesIn, maskIn);
969//
970 pTabOut->putSDContainer(sc);
971 }
972//
973 return pTabOut;
974}
975
976
977SDMemTable* SDMath::convertFlux (const SDMemTable& in, Float a, Float eta, Bool doAll) const
978//
979// As it is, this function could be implemented with 'simpleOperate'
980// However, I anticipate that eventually we will look the conversion
981// values up in a Table and apply them in a frequency dependent way,
982// so I have implemented it fully here
983//
984{
985 SDHeader sh = in.getSDHeader();
986 SDMemTable* pTabOut = new SDMemTable(in, True);
987
988// FInd out how to convert values into Jy and K (e.g. units might be mJy or mK)
989// Also automatically find out what we are converting to according to the
990// flux unit
991
992 Unit fluxUnit(sh.fluxunit);
993 Unit K(String("K"));
994 Unit JY(String("Jy"));
995//
996 Bool toKelvin = True;
997 Double inFac = 1.0;
998 if (fluxUnit==JY) {
999 cerr << "Converting to K" << endl;
1000//
1001 Quantum<Double> t(1.0,fluxUnit);
1002 Quantum<Double> t2 = t.get(JY);
1003 inFac = (t2 / t).getValue();
1004//
1005 toKelvin = True;
1006 sh.fluxunit = "K";
1007 } else if (fluxUnit==K) {
1008 cerr << "Converting to Jy" << endl;
1009//
1010 Quantum<Double> t(1.0,fluxUnit);
1011 Quantum<Double> t2 = t.get(K);
1012 inFac = (t2 / t).getValue();
1013//
1014 toKelvin = False;
1015 sh.fluxunit = "Jy";
1016 } else {
1017 throw AipsError("Unrecognized brightness units in Table - must be consistent with Jy or K");
1018 }
1019 pTabOut->putSDHeader(sh);
1020
1021// Compute conversion factor. 'a' and 'eta' are really frequency, time and
1022// telescope dependent and should be looked// up in a table
1023
1024 Float factor = 2.0 * inFac * 1.0e-7 * 1.0e26 *
1025 QC::k.getValue(Unit(String("erg/K"))) / a / eta;
1026 if (toKelvin) {
1027 factor = 1.0 / factor;
1028 }
1029 cerr << "Applying conversion factor = " << factor << endl;
1030
1031// For operations only on specified cursor location
1032
1033 IPosition start, end;
1034 getCursorLocation(start, end, in);
1035
1036// Loop over rows and apply factor to spectra
1037
1038 const uInt axis = asap::ChanAxis;
1039 for (uInt i=0; i < in.nRow(); ++i) {
1040
1041// Get data
1042
1043 MaskedArray<Float> dataIn(in.rowAsMaskedArray(i));
1044 Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference
1045 const Array<Bool>& maskIn = dataIn.getMask();
1046
1047// Need to apply correct conversion factor (frequency and time dependent)
1048// which should be sourced from a Table. For now we just apply the given
1049// factor to everything
1050
1051 if (doAll) {
1052 VectorIterator<Float> itValues(valuesIn, asap::ChanAxis);
1053 while (!itValues.pastEnd()) {
1054 itValues.vector() *= factor; // Writes back into dataIn
1055//
1056 itValues.next();
1057 }
1058 } else {
1059 Array<Float> valuesIn2 = valuesIn(start,end);
1060 valuesIn2 *= factor;
1061 valuesIn(start,end) = valuesIn2;
1062 }
1063
1064// Write out
1065
1066 SDContainer sc = in.getSDContainer(i);
1067 putDataInSDC(sc, valuesIn, maskIn);
1068//
1069 pTabOut->putSDContainer(sc);
1070 }
1071 return pTabOut;
1072}
1073
1074
1075
1076SDMemTable* SDMath::gainElevation (const SDMemTable& in, const Vector<Float>& coeffs,
1077 const String& fileName,
1078 const String& methodStr, Bool doAll) const
1079{
1080
1081// Get header and clone output table
1082
1083 SDHeader sh = in.getSDHeader();
1084 SDMemTable* pTabOut = new SDMemTable(in, True);
1085
1086// Get elevation data from SDMemTable and convert to degrees
1087
1088 const Table& tab = in.table();
1089 ROScalarColumn<Float> elev(tab, "ELEVATION");
1090 Vector<Float> x = elev.getColumn();
1091 x *= Float(180 / C::pi);
1092//
1093 const uInt nC = coeffs.nelements();
1094 if (fileName.length()>0 && nC>0) {
1095 throw AipsError("You must choose either polynomial coefficients or an ascii file, not both");
1096 }
1097
1098// Correct
1099
1100 if (nC>0 || fileName.length()==0) {
1101
1102// Find instrument
1103
1104 Bool throwIt = True;
1105 Instrument inst = SDMemTable::convertInstrument (sh.antennaname, throwIt);
1106
1107// Set polynomial
1108
1109 Polynomial<Float>* pPoly = 0;
1110 Vector<Float> coeff;
1111 String msg;
1112 if (nC>0) {
1113 pPoly = new Polynomial<Float>(nC);
1114 coeff = coeffs;
1115 msg = String("user");
1116 } else {
1117 if (inst==PKSMULTIBEAM) {
1118 } else if (inst==PKSSINGLEBEAM) {
1119 } else if (inst==TIDBINBILLA) {
1120 pPoly = new Polynomial<Float>(3);
1121 coeff.resize(3);
1122 coeff(0) = 3.58788e-1;
1123 coeff(1) = 2.87243e-2;
1124 coeff(2) = -3.219093e-4;
1125 } else if (inst==MOPRA) {
1126 }
1127 msg = String("built in");
1128 }
1129//
1130 if (coeff.nelements()>0) {
1131 pPoly->setCoefficients(coeff);
1132 } else {
1133 throw AipsError("There is no known gain-el polynomial known for this instrument");
1134 }
1135//
1136 cerr << "Making polynomial correction with " << msg << " coefficients" << endl;
1137 const uInt nRow = in.nRow();
1138 Vector<Float> factor(nRow);
1139 for (uInt i=0; i<nRow; i++) {
1140 factor[i] = (*pPoly)(x[i]);
1141 }
1142 delete pPoly;
1143//
1144 correctFromVector (pTabOut, in, doAll, factor);
1145 } else {
1146
1147// Indicate which columns to read from ascii file
1148
1149 String col0("ELEVATION");
1150 String col1("FACTOR");
1151
1152// Read and correct
1153
1154 cerr << "Making correction from ascii Table" << endl;
1155 correctFromAsciiTable (pTabOut, in, fileName, col0, col1,
1156 methodStr, doAll, x);
1157 }
1158//
1159 return pTabOut;
1160}
1161
1162
1163
1164SDMemTable* SDMath::opacity (const SDMemTable& in, Float tau, Bool doAll) const
1165{
1166
1167// Get header and clone output table
1168
1169 SDHeader sh = in.getSDHeader();
1170 SDMemTable* pTabOut = new SDMemTable(in, True);
1171
1172// Get elevation data from SDMemTable and convert to degrees
1173
1174 const Table& tab = in.table();
1175 ROScalarColumn<Float> elev(tab, "ELEVATION");
1176 Vector<Float> zDist = elev.getColumn();
1177 zDist = Float(C::pi_2) - zDist;
1178
1179// Generate correction factor
1180
1181 const uInt nRow = in.nRow();
1182 Vector<Float> factor(nRow);
1183 Vector<Float> factor2(nRow);
1184 for (uInt i=0; i<nRow; i++) {
1185 factor[i] = exp(tau)/cos(zDist[i]);
1186 }
1187
1188// Correct
1189
1190 correctFromVector (pTabOut, in, doAll, factor);
1191//
1192 return pTabOut;
1193}
1194
1195
1196
1197
1198// 'private' functions
1199
1200void SDMath::fillSDC(SDContainer& sc,
1201 const Array<Bool>& mask,
1202 const Array<Float>& data,
1203 const Array<Float>& tSys,
1204 Int scanID, Double timeStamp,
1205 Double interval, const String& sourceName,
1206 const Vector<uInt>& freqID) const
1207{
1208// Data and mask
1209
1210 putDataInSDC(sc, data, mask);
1211
1212// TSys
1213
1214 sc.putTsys(tSys);
1215
1216// Time things
1217
1218 sc.timestamp = timeStamp;
1219 sc.interval = interval;
1220 sc.scanid = scanID;
1221//
1222 sc.sourcename = sourceName;
1223 sc.putFreqMap(freqID);
1224}
1225
1226void SDMath::normalize(MaskedArray<Float>& sum,
1227 const Array<Float>& sumSq,
1228 const Array<Float>& nPts,
1229 WeightType wtType, Int axis,
1230 Int nAxesSub) const
1231{
1232 IPosition pos2(nAxesSub,0);
1233//
1234 if (wtType==NONE) {
1235
1236// We just average by the number of points accumulated.
1237// We need to make a MA out of nPts so that no divide by
1238// zeros occur
1239
1240 MaskedArray<Float> t(nPts, (nPts>Float(0.0)));
1241 sum /= t;
1242 } else if (wtType==VAR) {
1243
1244// Normalize each spectrum by sum(1/var) where the variance
1245// is worked out for each spectrum
1246
1247 Array<Float>& data = sum.getRWArray();
1248 VectorIterator<Float> itData(data, axis);
1249 while (!itData.pastEnd()) {
1250 pos2 = itData.pos().getFirst(nAxesSub);
1251 itData.vector() /= sumSq(pos2);
1252 itData.next();
1253 }
1254 } else if (wtType==TSYS) {
1255 }
1256}
1257
1258
1259void SDMath::accumulate(Double& timeSum, Double& intSum, Int& nAccum,
1260 MaskedArray<Float>& sum, Array<Float>& sumSq,
1261 Array<Float>& nPts, Array<Float>& tSysSum,
1262 const Array<Float>& tSys, const Array<Float>& nInc,
1263 const Vector<Bool>& mask, Double time, Double interval,
1264 const Block<CountedPtr<SDMemTable> >& in,
1265 uInt iTab, uInt iRow, uInt axis,
1266 uInt nAxesSub, Bool useMask,
1267 WeightType wtType) const
1268{
1269
1270// Get data
1271
1272 MaskedArray<Float> dataIn(in[iTab]->rowAsMaskedArray(iRow));
1273 Array<Float>& valuesIn = dataIn.getRWArray(); // writable reference
1274 const Array<Bool>& maskIn = dataIn.getMask(); // RO reference
1275//
1276 if (wtType==NONE) {
1277 const MaskedArray<Float> n(nInc,dataIn.getMask());
1278 nPts += n; // Only accumulates where mask==T
1279 } else if (wtType==VAR) {
1280
1281// We are going to average the data, weighted by the noise for each pol, beam and IF.
1282// So therefore we need to iterate through by spectrum (axis 3)
1283
1284 VectorIterator<Float> itData(valuesIn, axis);
1285 ReadOnlyVectorIterator<Bool> itMask(maskIn, axis);
1286 Float fac = 1.0;
1287 IPosition pos(nAxesSub,0);
1288//
1289 while (!itData.pastEnd()) {
1290
1291// Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor
1292
1293 if (useMask) {
1294 MaskedArray<Float> tmp(itData.vector(),mask&&itMask.vector());
1295 fac = 1.0/variance(tmp);
1296 } else {
1297 MaskedArray<Float> tmp(itData.vector(),itMask.vector());
1298 fac = 1.0/variance(tmp);
1299 }
1300
1301// Scale data
1302
1303 itData.vector() *= fac; // Writes back into 'dataIn'
1304//
1305// Accumulate variance per if/pol/beam averaged over spectrum
1306// This method to get pos2 from itData.pos() is only valid
1307// because the spectral axis is the last one (so we can just
1308// copy the first nAXesSub positions out)
1309
1310 pos = itData.pos().getFirst(nAxesSub);
1311 sumSq(pos) += fac;
1312//
1313 itData.next();
1314 itMask.next();
1315 }
1316 } else if (wtType==TSYS) {
1317 }
1318
1319// Accumulate sum of (possibly scaled) data
1320
1321 sum += dataIn;
1322
1323// Accumulate Tsys, time, and interval
1324
1325 tSysSum += tSys;
1326 timeSum += time;
1327 intSum += interval;
1328 nAccum += 1;
1329}
1330
1331
1332
1333
1334void SDMath::getCursorLocation(IPosition& start, IPosition& end,
1335 const SDMemTable& in) const
1336{
1337 const uInt nDim = 4;
1338 const uInt i = in.getBeam();
1339 const uInt j = in.getIF();
1340 const uInt k = in.getPol();
1341 const uInt n = in.nChan();
1342//
1343 start.resize(nDim);
1344 start(0) = i;
1345 start(1) = j;
1346 start(2) = k;
1347 start(3) = 0;
1348//
1349 end.resize(nDim);
1350 end(0) = i;
1351 end(1) = j;
1352 end(2) = k;
1353 end(3) = n-1;
1354}
1355
1356
1357void SDMath::convertWeightString(WeightType& wtType, const String& weightStr) const
1358{
1359 String tStr(weightStr);
1360 tStr.upcase();
1361 if (tStr.contains(String("NONE"))) {
1362 wtType = NONE;
1363 } else if (tStr.contains(String("VAR"))) {
1364 wtType = VAR;
1365 } else if (tStr.contains(String("TSYS"))) {
1366 wtType = TSYS;
1367 throw(AipsError("T_sys weighting not yet implemented"));
1368 } else {
1369 throw(AipsError("Unrecognized weighting type"));
1370 }
1371}
1372
1373void SDMath::convertInterpString(Int& type, const String& interp) const
1374{
1375 String tStr(interp);
1376 tStr.upcase();
1377 if (tStr.contains(String("NEAR"))) {
1378 type = InterpolateArray1D<Float,Float>::nearestNeighbour;
1379 } else if (tStr.contains(String("LIN"))) {
1380 type = InterpolateArray1D<Float,Float>::linear;
1381 } else if (tStr.contains(String("CUB"))) {
1382 type = InterpolateArray1D<Float,Float>::cubic;
1383 } else if (tStr.contains(String("SPL"))) {
1384 type = InterpolateArray1D<Float,Float>::spline;
1385 } else {
1386 throw(AipsError("Unrecognized interpolation type"));
1387 }
1388}
1389
1390void SDMath::putDataInSDC(SDContainer& sc, const Array<Float>& data,
1391 const Array<Bool>& mask) const
1392{
1393 sc.putSpectrum(data);
1394//
1395 Array<uChar> outflags(data.shape());
1396 convertArray(outflags,!mask);
1397 sc.putFlags(outflags);
1398}
1399
1400Table SDMath::readAsciiFile (const String& fileName) const
1401{
1402 String formatString;
1403 Table tbl = readAsciiTable (formatString, Table::Memory, fileName, "", "", False);
1404 return tbl;
1405}
1406
1407
1408
1409void SDMath::correctFromAsciiTable(SDMemTable* pTabOut,
1410 const SDMemTable& in, const String& fileName,
1411 const String& col0, const String& col1,
1412 const String& methodStr, Bool doAll,
1413 const Vector<Float>& xOut) const
1414{
1415
1416// Read gain-elevation ascii file data into a Table.
1417
1418 Table geTable = readAsciiFile (fileName);
1419//
1420 correctFromTable (pTabOut, in, geTable, col0, col1, methodStr, doAll, xOut);
1421}
1422
1423void SDMath::correctFromTable(SDMemTable* pTabOut, const SDMemTable& in,
1424 const Table& tTable, const String& col0,
1425 const String& col1,
1426 const String& methodStr, Bool doAll,
1427 const Vector<Float>& xOut) const
1428{
1429
1430// Get data from Table
1431
1432 ROScalarColumn<Float> geElCol(tTable, col0);
1433 ROScalarColumn<Float> geFacCol(tTable, col1);
1434 Vector<Float> xIn = geElCol.getColumn();
1435 Vector<Float> yIn = geFacCol.getColumn();
1436 Vector<Bool> maskIn(xIn.nelements(),True);
1437
1438// Interpolate (and extrapolate) with desired method
1439
1440 Int method = 0;
1441 convertInterpString(method, methodStr);
1442//
1443 Vector<Float> yOut;
1444 Vector<Bool> maskOut;
1445 InterpolateArray1D<Float,Float>::interpolate(yOut, maskOut, xOut,
1446 xIn, yIn, maskIn, method,
1447 True, True);
1448// Apply
1449
1450 correctFromVector (pTabOut, in, doAll, yOut);
1451}
1452
1453
1454void SDMath::correctFromVector (SDMemTable* pTabOut, const SDMemTable& in,
1455 Bool doAll, const Vector<Float>& factor) const
1456{
1457// For operations only on specified cursor location
1458
1459 IPosition start, end;
1460 getCursorLocation(start, end, in);
1461
1462// Loop over rows and interpolate correction factor
1463
1464 const uInt axis = asap::ChanAxis;
1465 for (uInt i=0; i < in.nRow(); ++i) {
1466
1467// Get data
1468
1469 MaskedArray<Float> dataIn(in.rowAsMaskedArray(i));
1470 Array<Float>& valuesIn = dataIn.getRWArray();
1471 const Array<Bool>& maskIn = dataIn.getMask();
1472
1473// Apply factor
1474
1475 if (doAll) {
1476 VectorIterator<Float> itValues(valuesIn, asap::ChanAxis);
1477 while (!itValues.pastEnd()) {
1478 itValues.vector() *= factor(i);
1479 itValues.next();
1480 }
1481 } else {
1482 Array<Float> valuesIn2 = valuesIn(start,end);
1483 valuesIn2 *= factor(i);
1484 valuesIn(start,end) = valuesIn2;
1485 }
1486
1487// Write out
1488
1489 SDContainer sc = in.getSDContainer(i);
1490 putDataInSDC(sc, valuesIn, maskIn);
1491//
1492 pTabOut->putSDContainer(sc);
1493 }
1494}
1495
1496
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