source: trunk/src/SDMath.cc @ 233

Last change on this file since 233 was 232, checked in by mar637, 19 years ago

renamed Definitions.h -> SDDefs.h

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