source: trunk/src/SDMath.cc@ 247

Last change on this file since 247 was 247, checked in by kil064, 20 years ago

fix error in nRow test in function quotient

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[2]1//#---------------------------------------------------------------------------
2//# SDMath.cc: A collection of single dish mathematical operations
3//#---------------------------------------------------------------------------
4//# Copyright (C) 2004
[125]5//# ATNF
[2]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//#---------------------------------------------------------------------------
[38]31#include <vector>
32
[81]33#include <casa/aips.h>
34#include <casa/BasicSL/String.h>
35#include <casa/Arrays/IPosition.h>
36#include <casa/Arrays/Array.h>
[130]37#include <casa/Arrays/ArrayIter.h>
38#include <casa/Arrays/VectorIter.h>
[81]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>
[234]44#include <casa/BasicMath/Math.h>
[221]45#include <casa/Containers/Block.h>
46#include <casa/Quanta/QC.h>
[177]47#include <casa/Utilities/Assert.h>
[130]48#include <casa/Exceptions.h>
[2]49
[177]50#include <scimath/Mathematics/VectorKernel.h>
51#include <scimath/Mathematics/Convolver.h>
[227]52#include <scimath/Mathematics/InterpolateArray1D.h>
[234]53#include <scimath/Functionals/Polynomial.h>
[177]54
[81]55#include <tables/Tables/Table.h>
56#include <tables/Tables/ScalarColumn.h>
57#include <tables/Tables/ArrayColumn.h>
[227]58#include <tables/Tables/ReadAsciiTable.h>
[2]59
[130]60#include <lattices/Lattices/LatticeUtilities.h>
61#include <lattices/Lattices/RebinLattice.h>
[81]62#include <coordinates/Coordinates/SpectralCoordinate.h>
[130]63#include <coordinates/Coordinates/CoordinateSystem.h>
64#include <coordinates/Coordinates/CoordinateUtil.h>
[221]65#include <coordinates/Coordinates/VelocityAligner.h>
[38]66
67#include "MathUtils.h"
[232]68#include "SDDefs.h"
[2]69#include "SDContainer.h"
70#include "SDMemTable.h"
71
72#include "SDMath.h"
73
[125]74using namespace casa;
[83]75using namespace asap;
[2]76
[170]77
78SDMath::SDMath()
79{;}
80
[185]81SDMath::SDMath(const SDMath& other)
[170]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
[183]96SDMath::~SDMath()
97{;}
[170]98
[183]99
[185]100CountedPtr<SDMemTable> SDMath::average(const Block<CountedPtr<SDMemTable> >& in,
101 const Vector<Bool>& mask, Bool scanAv,
[234]102 const String& weightStr) const
[221]103//Bool alignVelocity)
[130]104//
[144]105// Weighted averaging of spectra from one or more Tables.
[130]106//
107{
[221]108 Bool alignVelocity = False;
[2]109
[163]110// Convert weight type
111
112 WeightType wtType = NONE;
[185]113 convertWeightString(wtType, weightStr);
[163]114
[144]115// Create output Table by cloning from the first table
[2]116
[144]117 SDMemTable* pTabOut = new SDMemTable(*in[0],True);
[130]118
[144]119// Setup
[130]120
[144]121 IPosition shp = in[0]->rowAsMaskedArray(0).shape(); // Must not change
122 Array<Float> arr(shp);
123 Array<Bool> barr(shp);
[221]124 const Bool useMask = (mask.nelements() == shp(asap::ChanAxis));
[130]125
[144]126// Columns from Tables
[130]127
[144]128 ROArrayColumn<Float> tSysCol;
129 ROScalarColumn<Double> mjdCol;
130 ROScalarColumn<String> srcNameCol;
131 ROScalarColumn<Double> intCol;
132 ROArrayColumn<uInt> fqIDCol;
[130]133
[144]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++) {
[221]159 if (i!=asap::ChanAxis) {
[144]160 shp2(j) = shp(i);
161 j++;
162 }
[2]163 }
[144]164 Array<Float> sumSq(shp2);
165 sumSq = 0.0;
166 IPosition pos2(nAxesSub,0); // For indexing
[130]167
[144]168// Time-related accumulators
[130]169
[144]170 Double time;
171 Double timeSum = 0.0;
172 Double intSum = 0.0;
173 Double interval = 0.0;
[130]174
[144]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
[130]178
[144]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
[221]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
[144]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
[221]243// Should check that the frequency tables don't change if doing VelocityAlignment
244
[144]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
[221]299 normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub);
[144]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);
[185]306 fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID,
[144]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;
[221]322 nPts = 0.0;
[144]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
[227]333 }
[144]334
[146]335// Accumulate
[144]336
[185]337 accumulate(timeSum, intSum, nAccum, sum, sumSq, nPts, tSysSum,
[221]338 tSys, nInc, mask, time, interval, in, iTab, iRow, asap::ChanAxis,
[146]339 nAxesSub, useMask, wtType);
[144]340//
341 oldSourceName = sourceName;
342 oldFreqID = freqID;
[184]343 }
[144]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
[221]352 normalize(sum, sumSq, nPts, wtType, asap::ChanAxis, nAxesSub);
[144]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);
[185]360 fillSDC(sc, sum.getMask(), sum.getArray(), tSysSum/nR, outScanID,
[144]361 timeSum/nR, intSum, sourceNameStart, freqIDStart);
[221]362 pTabOut->putSDContainer(sc);
[144]363//
364 return CountedPtr<SDMemTable>(pTabOut);
[2]365}
[9]366
[144]367
368
[234]369CountedPtr<SDMemTable> SDMath::quotient(const CountedPtr<SDMemTable>& on,
370 const CountedPtr<SDMemTable>& off,
371 Bool preserveContinuum) const
[185]372{
[234]373 const uInt nRowOn = on->nRow();
374 const uInt nRowOff = off->nRow();
375 Bool ok = (nRowOff==1&&nRowOn>0) ||
[247]376 (nRowOff>=1&&nRowOn==nRowOff);
[234]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"));
[130]379 }
[85]380
[130]381// Input Tables and columns
382
[234]383 Table tabOn = on->table();
384 Table tabOff = off->table();
385 ROArrayColumn<Float> tSysOn(tabOn, "TSYS");
386 ROArrayColumn<Float> tSysOff(tabOff, "TSYS");
[38]387
[130]388// Output Table cloned from input
[85]389
[171]390 SDMemTable* pTabOut = new SDMemTable(*on, True);
[130]391
392// Loop over rows
393
[234]394 MaskedArray<Float>* pMOff = new MaskedArray<Float>(off->rowAsMaskedArray(0));
395 IPosition shpOff = pMOff->shape();
[130]396//
[234]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();
[247]404 tSysOn.get(i, tSysOnArr);
[234]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);
[130]411 }
412
[247]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
[244]425// Get container
[130]426
[244]427 SDContainer sc = on->getSDContainer(i);
[130]428
[244]429// Compute and put quotient into container
[234]430
[244]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 }
[234]438 sc.putTsys(tSysOffArr);
[184]439 sc.scanid = i;
[130]440
441// Put new row in output Table
[234]442
443 pTabOut->putSDContainer(sc);
444 }
445 if (pMOff) delete pMOff;
446//
447 return CountedPtr<SDMemTable>(pTabOut);
448}
[130]449
[234]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
[171]541 pTabOut->putSDContainer(sc);
[130]542 }
543//
[171]544 return CountedPtr<SDMemTable>(pTabOut);
[9]545}
[48]546
[146]547
548
[185]549std::vector<float> SDMath::statistic(const CountedPtr<SDMemTable>& in,
[234]550 const Vector<Bool>& mask,
551 const String& which, Int row) const
[130]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
[152]561 IPosition start, end;
[185]562 getCursorLocation(start, end, *in);
[130]563
564// Loop over rows
565
[234]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) {
[130]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) {
[234]593 tmp.setData(v,m&&mask);
[130]594 } else {
595 tmp.setData(v,m);
596 }
597
598// Get statistic
599
[234]600 result[ii-iStart] = mathutil::statistics(which, tmp);
[130]601 }
602//
603 return result;
604}
605
[146]606
[234]607SDMemTable* SDMath::bin(const SDMemTable& in, Int width) const
[144]608{
[169]609 SDHeader sh = in.getSDHeader();
610 SDMemTable* pTabOut = new SDMemTable(in, True);
[163]611
[169]612// Bin up SpectralCoordinates
[163]613
[169]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 =
[185]620 CoordinateUtil::makeBinnedCoordinateSystem(factors, cSys, False);
[169]621//
622 SpectralCoordinate sCBin = cSysBin.spectralCoordinate(0);
623 pTabOut->setCoordinate(sCBin, j);
624 }
[163]625
[169]626// Use RebinLattice to find shape
[130]627
[169]628 IPosition shapeIn(1,sh.nchan);
[185]629 IPosition shapeOut = RebinLattice<Float>::rebinShape(shapeIn, factors);
[169]630 sh.nchan = shapeOut(0);
631 pTabOut->putSDHeader(sh);
[144]632
633
[169]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);
[144]638//
[169]639 Array<Float> tSys(sc.getTsys()); // Get it out before sc changes shape
[144]640
[169]641// Bin up spectrum
[144]642
[169]643 MaskedArray<Float> marr(in.rowAsMaskedArray(i));
644 MaskedArray<Float> marrout;
[221]645 LatticeUtilities::bin(marrout, marr, asap::ChanAxis, width);
[144]646
[169]647// Put back the binned data and flags
[144]648
[169]649 IPosition ip2 = marrout.shape();
650 sc.resize(ip2);
[146]651//
[185]652 putDataInSDC(sc, marrout.getArray(), marrout.getMask());
[146]653
[169]654// Bin up Tsys.
[146]655
[169]656 Array<Bool> allGood(tSys.shape(),True);
657 MaskedArray<Float> tSysIn(tSys, allGood, True);
[146]658//
[169]659 MaskedArray<Float> tSysOut;
[221]660 LatticeUtilities::bin(tSysOut, tSysIn, asap::ChanAxis, width);
[169]661 sc.putTsys(tSysOut.getArray());
[146]662//
[169]663 pTabOut->putSDContainer(sc);
664 }
665 return pTabOut;
[146]666}
667
[185]668SDMemTable* SDMath::simpleOperate(const SDMemTable& in, Float val, Bool doAll,
[234]669 uInt what) const
[152]670//
671// what = 0 Multiply
672// 1 Add
[146]673{
[152]674 SDMemTable* pOut = new SDMemTable(in,False);
675 const Table& tOut = pOut->table();
676 ArrayColumn<Float> spec(tOut,"SPECTRA");
[146]677//
[152]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;
[185]702 getCursorLocation(start, end, in);
[152]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//
[146]730 return pOut;
731}
732
733
[152]734
[234]735SDMemTable* SDMath::averagePol(const SDMemTable& in, const Vector<Bool>& mask) const
[152]736//
[165]737// Average all polarizations together, weighted by variance
738//
739{
740// WeightType wtType = NONE;
[185]741// convertWeightString(wtType, weight);
[165]742
743 const uInt nRows = in.nRow();
[209]744 const uInt polAxis = asap::PolAxis; // Polarization axis
745 const uInt chanAxis = asap::ChanAxis; // Spectrum axis
[165]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//
[185]860 putDataInSDC(sc, outData, outMask);
[165]861 pTabOut->putSDContainer(sc);
862 }
863//
864 return pTabOut;
865}
[167]866
[169]867
[185]868SDMemTable* SDMath::smooth(const SDMemTable& in,
869 const casa::String& kernelType,
[234]870 casa::Float width, Bool doAll) const
[177]871{
[169]872
[177]873// Number of channels
[169]874
[209]875 const uInt chanAxis = asap::ChanAxis; // Spectral axis
[177]876 SDHeader sh = in.getSDHeader();
877 const uInt nChan = sh.nchan;
878
879// Generate Kernel
880
[185]881 VectorKernel::KernelTypes type = VectorKernel::toKernelType(kernelType);
[177]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;
[185]896 getCursorLocation(start, end, in);
[177]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) {
[221]921 uInt axis = asap::ChanAxis;
[177]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);
[185]967 putDataInSDC(sc, valuesIn, maskIn);
[177]968//
969 pTabOut->putSDContainer(sc);
970 }
971//
972 return pTabOut;
973}
974
975
[234]976SDMemTable* SDMath::convertFlux (const SDMemTable& in, Float a, Float eta, Bool doAll) const
[221]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);
[177]986
[221]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
[177]990
[221]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);
[177]1019
[221]1020// Compute conversion factor. 'a' and 'eta' are really frequency, time and
1021// telescope dependent and should be looked// up in a table
1022
[234]1023 Float factor = 2.0 * inFac * 1.0e-7 * 1.0e26 *
1024 QC::k.getValue(Unit(String("erg/K"))) / a / eta;
[221]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
[234]1075SDMemTable* SDMath::gainElevation (const SDMemTable& in, const Vector<Float>& coeffs,
1076 const String& fileName,
1077 const String& methodStr, Bool doAll) const
[227]1078{
[234]1079
1080// Get header and clone output table
1081
[227]1082 SDHeader sh = in.getSDHeader();
1083 SDMemTable* pTabOut = new SDMemTable(in, True);
1084
[234]1085// Get elevation data from SDMemTable and convert to degrees
[227]1086
1087 const Table& tab = in.table();
1088 ROScalarColumn<Float> elev(tab, "ELEVATION");
[234]1089 Vector<Float> x = elev.getColumn();
1090 x *= Float(180 / C::pi);
[227]1091//
[234]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 }
[227]1128//
[234]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;
[230]1159}
[227]1160
[230]1161
[227]1162
[234]1163SDMemTable* SDMath::opacity (const SDMemTable& in, Float tau, Bool doAll) const
1164{
[227]1165
[234]1166// Get header and clone output table
[227]1167
[234]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
[169]1197// 'private' functions
1198
[185]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,
[227]1205 const Vector<uInt>& freqID) const
[167]1206{
[169]1207// Data and mask
[167]1208
[185]1209 putDataInSDC(sc, data, mask);
[167]1210
[169]1211// TSys
1212
1213 sc.putTsys(tSys);
1214
1215// Time things
1216
1217 sc.timestamp = timeStamp;
1218 sc.interval = interval;
1219 sc.scanid = scanID;
[167]1220//
[169]1221 sc.sourcename = sourceName;
1222 sc.putFreqMap(freqID);
1223}
[167]1224
[185]1225void SDMath::normalize(MaskedArray<Float>& sum,
[169]1226 const Array<Float>& sumSq,
1227 const Array<Float>& nPts,
1228 WeightType wtType, Int axis,
[227]1229 Int nAxesSub) const
[169]1230{
1231 IPosition pos2(nAxesSub,0);
1232//
1233 if (wtType==NONE) {
[167]1234
[169]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
[167]1238
[169]1239 MaskedArray<Float> t(nPts, (nPts>Float(0.0)));
1240 sum /= t;
1241 } else if (wtType==VAR) {
[167]1242
[169]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
[185]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,
[227]1266 WeightType wtType) const
[169]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
[167]1274//
[169]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) {
[167]1279
[169]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)
[167]1282
[169]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()) {
[167]1289
[169]1290// Make MaskedArray of Vector, optionally apply OTF mask, and find scaling factor
[167]1291
[169]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'
[167]1303//
[169]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)
[167]1308
[169]1309 pos = itData.pos().getFirst(nAxesSub);
1310 sumSq(pos) += fac;
1311//
1312 itData.next();
1313 itMask.next();
1314 }
1315 } else if (wtType==TSYS) {
1316 }
[167]1317
[169]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
[185]1333void SDMath::getCursorLocation(IPosition& start, IPosition& end,
[227]1334 const SDMemTable& in) const
[169]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();
[167]1341//
[169]1342 start.resize(nDim);
1343 start(0) = i;
1344 start(1) = j;
1345 start(2) = k;
1346 start(3) = 0;
[167]1347//
[169]1348 end.resize(nDim);
1349 end(0) = i;
1350 end(1) = j;
1351 end(2) = k;
1352 end(3) = n-1;
1353}
1354
1355
[227]1356void SDMath::convertWeightString(WeightType& wtType, const String& weightStr) const
[169]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;
[185]1366 throw(AipsError("T_sys weighting not yet implemented"));
[169]1367 } else {
[185]1368 throw(AipsError("Unrecognized weighting type"));
[167]1369 }
1370}
1371
[227]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
[185]1389void SDMath::putDataInSDC(SDContainer& sc, const Array<Float>& data,
[227]1390 const Array<Bool>& mask) const
[169]1391{
1392 sc.putSpectrum(data);
1393//
1394 Array<uChar> outflags(data.shape());
1395 convertArray(outflags,!mask);
1396 sc.putFlags(outflags);
1397}
[227]1398
1399Table SDMath::readAsciiFile (const String& fileName) const
1400{
[230]1401 String formatString;
1402 Table tbl = readAsciiTable (formatString, Table::Memory, fileName, "", "", False);
[227]1403 return tbl;
1404}
[230]1405
1406
[234]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
[230]1413{
1414
1415// Read gain-elevation ascii file data into a Table.
1416
[234]1417 Table geTable = readAsciiFile (fileName);
[230]1418//
[234]1419 correctFromTable (pTabOut, in, geTable, col0, col1, methodStr, doAll, xOut);
[230]1420}
1421
[234]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
[230]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);
[234]1447// Apply
[230]1448
[234]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{
[230]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));
[234]1469 Array<Float>& valuesIn = dataIn.getRWArray();
[230]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()) {
[234]1477 itValues.vector() *= factor(i);
[230]1478 itValues.next();
1479 }
1480 } else {
1481 Array<Float> valuesIn2 = valuesIn(start,end);
[234]1482 valuesIn2 *= factor(i);
[230]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
[234]1495
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