source: trunk/python/sbseparator.py @ 2821

Last change on this file since 2821 was 2807, checked in by Kana Sugimoto, 11 years ago

New Development: No (A bug fix for CASA 4.1)

JIRA Issue: Yes (CAS-4141/TRAC-290)

Ready for Test: Yes

Interface Changes: No

What Interface Changed:

Test Programs:

Put in Release Notes: No

Module(s): itself

Description: fixed a bug in sbseparator.set_lo1.
File size: 22.5 KB
Line 
1import os, shutil
2import numpy
3import numpy.fft as FFT
4import math
5
6from asap.scantable import scantable
7from asap.parameters import rcParams
8from asap.logging import asaplog, asaplog_post_dec
9from asap.selector import selector
10from asap.asapgrid import asapgrid2
11from asap._asap import SBSeparator
12
13class sbseparator:
14    """
15    The sbseparator class is defined to separate SIGNAL and IMAGE
16    sideband spectra observed by frequency-switching technique.
17    It also helps supressing emmission of IMAGE sideband.
18    *** WARNING *** THIS MODULE IS EXPERIMENTAL
19    Known issues:
20    - Frequencies of IMAGE sideband cannot be reconstructed from
21      information in scantable in sideband sparation. Frequency
22      setting of SIGNAL sideband is stored in output table for now.
23    - Flag information (stored in FLAGTRA) is ignored.
24
25    Example:
26        # Create sideband separator instance whith 3 input data
27        sbsep = sbseparator(['test1.asap', 'test2.asap', 'test3.asap'])
28        # Set reference IFNO and tolerance to select data
29        sbsep.set_frequency(5, 30, frame='TOPO')
30        # Set direction tolerance to select data in unit of radian
31        sbsep.set_dirtol(1.e-5)
32        # Set rejection limit of solution
33        sbsep.set_limit(0.2)
34        # Solve image sideband as well
35        sbsep.set_both(True)
36        # Invoke sideband separation
37        sbsep.separate('testout.asap', overwrite = True)
38    """
39    def __init__(self, infiles):
40        self._separator = SBSeparator(infiles)
41
42################## temp functions #################
43#     def rfft(self, invec):
44#         print "Python method cppRfft"
45#         self._separator._cpprfft(invec)
46#         return
47################## temp functions #################
48
49    def set_frequency(self, baseif, freqtol, frame=""):
50        """
51        Set IFNO and frequency tolerance to select data to process.
52
53        Parameters:
54          - reference IFNO to process in the first table in the list
55          - frequency tolerance from reference IF to select data (string)
56          frame  : frequency frame to select IF
57        """
58        if type(freqtol) in (float, int):
59            freqtol = str(freqtol)
60        elif isinstance(freqtol, dict):
61            try:
62                freqtol = str(freqtol['value']) + freqtol['unit']
63            except:
64                raise ValueError, "Invalid frequency tolerance."
65        self._separator.set_freq(baseif, freqtol, frame)
66
67
68    def set_dirtol(self, dirtol=["2arcsec", "2arcsec"]):
69        """
70        Set tolerance of direction to select data
71        """
72        if isinstance(dirtol, str):
73            dirtol = [dirtol]
74
75        self._separator.set_dirtol(dirtol)
76   
77           
78    def set_shift(self, imageshift=[]):
79        """
80        Set shift mode and channel shift of image band.
81
82        imageshift : a list of number of channels shifted in image
83                     side band of each scantable.
84                     If the shifts are not set, they are assumed to be
85                     equal to those of signal side band, but in opposite
86                     direction as usual by LO1 offsetting of DSB receivers.
87        """
88        if not imageshift:
89            imageshift = []
90        self._separator.set_shift(imageshift)
91
92
93    @asaplog_post_dec
94    def set_both(self, flag=False):
95        """
96        Resolve both image and signal sideband when True.
97        """
98        self._separator.solve_both(flag)
99        if flag:
100            asaplog.push("Both signal and image sidebands will be solved and stored in separate tables.")
101        else:
102            asaplog.push("Only signal sideband will be solved and stored in an table.")
103
104    @asaplog_post_dec
105    def set_limit(self, threshold=0.2):
106        """
107        Set rejection limit of solution.
108        """
109        self._separator.set_limit(threshold)
110
111
112    @asaplog_post_dec
113    def set_solve_other(self, flag=False):
114        """
115        Calculate spectra by subtracting the solution of the other sideband
116        when True.
117        """
118        self._separator.subtract_other(flag)
119        if flag:
120            asaplog.push("Expert mode: solution are obtained by subtraction of the other sideband.")
121
122
123    def set_lo1(self, lo1, frame="TOPO", reftime=-1, refdir=""):
124        """
125        Set LO1 frequency to calculate frequency of image sideband.
126
127        lo1     : LO1 frequency
128        frame   : the frequency frame of LO1
129        reftime : the reference time used in frequency frame conversion.
130        refdir  : the reference direction used in frequency frame conversion.
131        """
132        self._separator.set_lo1(lo1, frame, reftime, refdir)
133
134
135    def set_lo1root(self, name):
136        """
137        Set MS name which stores LO1 frequency of signal side band.
138        It is used to calculate frequency of image sideband.
139
140        name : MS name which contains 'ASDM_SPECTRALWINDOW' and
141               'ASDM_RECEIVER' tables.
142        """
143        self._separator.set_lo1root(name)
144
145    @asaplog_post_dec
146    def separate(self, outname="", overwrite=False):
147        """
148        Invoke sideband separation.
149
150        outname   : a name of output scantable
151        overwrite : overwrite existing table
152        """
153        out_default = "sbseparated.asap"
154        if len(outname) == 0:
155            outname = out_default
156            asaplog.post()
157            asaplog.push("The output file name is not specified.")
158            asaplog.push("Using default name '%s'" % outname)
159            asaplog.post("WARN")
160
161        if os.path.exists(outname):
162            if overwrite:
163                asaplog.push("removing the old file '%s'" % outname)
164                shutil.rmtree(outname)
165            else:
166                asaplog.post()
167                asaplog.push("Output file '%s' already exists." % outname)
168                asaplog.post("ERROR")
169                return False
170
171        self._separator.separate(outname)
172
173######################################################################
174#     @asaplog_post_dec
175#     def separate0(self, outname="", overwrite=False):
176#         """
177#         Invoke sideband separation.
178
179#         outname   : a name of output scantable
180#         overwrite : overwrite existing table
181#         """
182#         # List up valid scantables and IFNOs to convolve.
183#         #self._separator.separate()
184#         self._setup_shift()
185#         #self._preprocess_tables()
186
187#         ### TEMPORAL ###
188#         self._separator._get_asistb_from_scantb(self.tables[0])
189#         ################
190
191#         nshift = len(self.tables)
192#         signaltab = self._grid_outtable(self.tables[0])
193#         if self.getboth:
194#             imagetab = signaltab.copy()
195
196#         rejrow = []
197#         for irow in xrange(signaltab.nrow()):
198#             currpol = signaltab.getpol(irow)
199#             currbeam = signaltab.getbeam(irow)
200#             currdir = signaltab.get_directionval(irow)
201#             spec_array, tabidx = self._get_specarray(polid=currpol,\
202#                                                      beamid=currbeam,\
203#                                                      dir=currdir)
204#             #if not spec_array:
205#             if len(tabidx) == 0:
206#                 asaplog.post()
207#                 asaplog.push("skipping row %d" % irow)
208#                 rejrow.append(irow)
209#                 continue
210#             signal = self._solve_signal(spec_array, tabidx)
211#             signaltab.set_spectrum(signal, irow)
212
213#             # Solve image side side band
214#             if self.getboth:
215#                 image = self._solve_image(spec_array, tabidx)
216#                 imagetab.set_spectrum(image, irow)
217
218#         # TODO: Need to remove rejrow form scantables here
219#         signaltab.flag_row(rejrow)
220#         if self.getboth:
221#             imagetab.flag_row(rejrow)
222       
223#         if outname == "":
224#             outname = "sbsepareted.asap"
225#         signalname = outname + ".signalband"
226#         if os.path.exists(signalname):
227#             if not overwrite:
228#                 raise Exception, "Output file '%s' exists." % signalname
229#             else:
230#                 shutil.rmtree(signalname)
231#         signaltab.save(signalname)
232
233#         if self.getboth:
234#             # Warnings
235#             asaplog.post()
236#             asaplog.push("Saving IMAGE sideband.")
237#             #asaplog.push("Note, frequency information of IMAGE sideband cannot be properly filled so far. (future development)")
238#             #asaplog.push("Storing frequency setting of SIGNAL sideband in FREQUENCIES table for now.")
239#             #asaplog.post("WARN")
240
241#             imagename = outname + ".imageband"
242#             if os.path.exists(imagename):
243#                 if not overwrite:
244#                     raise Exception, "Output file '%s' exists." % imagename
245#                 else:
246#                     shutil.rmtree(imagename)
247#             # Update frequency information
248#             self._separator.set_imgtable(imagetab)
249#             self._separator.solve_imgfreq()
250#             imagetab.save(imagename)
251
252
253#     def _solve_signal(self, data, tabidx=None):
254#         if not tabidx:
255#             tabidx = range(len(data))
256
257#         tempshift = []
258#         dshift = []
259#         if self.solveother:
260#             for idx in tabidx:
261#                 tempshift.append(-self.imageShift[idx])
262#                 dshift.append(self.signalShift[idx] - self.imageShift[idx])
263#         else:
264#             for idx in tabidx:
265#                 tempshift.append(-self.signalShift[idx])
266#                 dshift.append(self.imageShift[idx] - self.signalShift[idx])
267
268#         shiftdata = numpy.zeros(data.shape, numpy.float)
269#         for i in range(len(data)):
270#             shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i])
271#         ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit)
272#         result_image = self._combineResult(ifftdata)
273#         if not self.solveother:
274#             return result_image
275#         result_signal = self._subtractOtherSide(shiftdata, dshift, result_image)
276#         return result_signal
277
278
279#     def _solve_image(self, data, tabidx=None):
280#         if not tabidx:
281#             tabidx = range(len(data))
282
283#         tempshift = []
284#         dshift = []
285#         if self.solveother:
286#             for idx in tabidx:
287#                 tempshift.append(-self.signalShift[idx])
288#                 dshift.append(self.imageShift[idx] - self.signalShift[idx])
289#         else:
290#             for idx in tabidx:
291#                 tempshift.append(-self.imageShift[idx])
292#                 dshift.append(self.signalShift[idx] - self.imageShift[idx])
293
294#         shiftdata = numpy.zeros(data.shape, numpy.float)
295#         for i in range(len(data)):
296#             shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i])
297#         ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit)
298#         result_image = self._combineResult(ifftdata)
299#         if not self.solveother:
300#             return result_image
301#         result_signal = self._subtractOtherSide(shiftdata, dshift, result_image)
302#         return result_signal
303
304#     @asaplog_post_dec
305#     def _grid_outtable(self, table):
306#         # Generate gridded table for output (Just to get rows)
307#         gridder = asapgrid2(table)
308#         gridder.setIF(self.baseif)
309
310#         cellx = str(self.dirtol[0])+"rad"
311#         celly = str(self.dirtol[1])+"rad"
312#         dirarr = numpy.array(table.get_directionval()).transpose()
313#         mapx = dirarr[0].max() - dirarr[0].min()
314#         mapy = dirarr[1].max() - dirarr[1].min()
315#         centy = 0.5 * (dirarr[1].max() + dirarr[1].min())
316#         nx = max(1, numpy.ceil(mapx*numpy.cos(centy)/self.dirtol[0]))
317#         ny = max(1, numpy.ceil(mapy/self.dirtol[0]))
318
319#         asaplog.push("Regrid output scantable with cell = [%s, %s]" % \
320#                      (cellx, celly))
321#         gridder.defineImage(nx=nx, ny=ny, cellx=cellx, celly=celly)
322#         gridder.setFunc(func='box', convsupport=1)
323#         gridder.setWeight(weightType='uniform')
324#         gridder.grid()
325#         return gridder.getResult()
326
327#     @asaplog_post_dec
328#     def _get_specarray(self, polid=None, beamid=None, dir=None):
329#         ntable = len(self.tables)
330#         spec_array = numpy.zeros((ntable, self.nchan), numpy.float)
331#         nspec = 0
332#         asaplog.push("Start data selection by POL=%d, BEAM=%d, direction=[%f, %f]" % (polid, beamid, dir[0], dir[1]))
333#         tabidx = []
334#         for itab in range(ntable):
335#             tab = self.tables[itab]
336#             # Select rows by POLNO and BEAMNO
337#             try:
338#                 tab.set_selection(pols=[polid], beams=[beamid])
339#                 if tab.nrow() > 0: tabidx.append(itab)
340#             except: # no selection
341#                 asaplog.post()
342#                 asaplog.push("table %d - No spectrum ....skipping the table" % (itab))
343#                 asaplog.post("WARN")
344#                 continue
345
346#             # Select rows by direction
347#             spec = numpy.zeros(self.nchan, numpy.float)
348#             selrow = []
349#             for irow in range(tab.nrow()):
350#                 currdir = tab.get_directionval(irow)
351#                 if (abs(currdir[0] - dir[0]) > self.dirtol[0]) or \
352#                    (abs(currdir[1] - dir[1]) > self.dirtol[1]):
353#                     continue
354#                 selrow.append(irow)
355#             if len(selrow) == 0:
356#                 asaplog.post()
357#                 asaplog.push("table %d - No spectrum ....skipping the table" % (itab))
358#                 asaplog.post("WARN")
359#                 continue
360#             else:
361#                 seltab = tab.copy()
362#                 seltab.set_selection(selector(rows=selrow))
363
364#             if seltab.nrow() > 1:
365#                 asaplog.push("table %d - More than a spectrum selected. averaging rows..." % (itab))
366#                 tab = seltab.average_time(scanav=False, weight="tintsys")
367#             else:
368#                 tab = seltab
369
370#             spec_array[nspec] = tab._getspectrum()
371#             nspec += 1
372
373#         if nspec != ntable:
374#             asaplog.post()
375#             #asaplog.push("Some tables has no spectrum with POL=%d BEAM=%d. averaging rows..." % (polid, beamid))
376#             asaplog.push("Could not find corresponding rows in some tables.")
377#             asaplog.push("Number of spectra selected = %d (table: %d)" % (nspec, ntable))
378#             if nspec < 2:
379#                 asaplog.push("At least 2 spectra are necessary for convolution")
380#                 asaplog.post("ERROR")
381#                 return False, tabidx
382
383#         return spec_array[0:nspec], tabidx
384
385
386#     @asaplog_post_dec
387#     def _setup_shift(self):
388#         ### define self.tables, self.signalShift, and self.imageShift
389#         if not self.intables:
390#             asaplog.post()
391#             raise RuntimeError, "Input data is not defined."
392#         #if self.baseif < 0:
393#         #    asaplog.post()
394#         #    raise RuntimeError, "Reference IFNO is not defined."
395       
396#         byname = False
397#         #if not self.intables:
398#         if isinstance(self.intables[0], str):
399#             # A list of file name is given
400#             if not os.path.exists(self.intables[0]):
401#                 asaplog.post()
402#                 raise RuntimeError, "Could not find '%s'" % self.intables[0]
403           
404#             stab = scantable(self.intables[0],average=False)
405#             ntab = len(self.intables)
406#             byname = True
407#         else:
408#             stab = self.intables[0]
409#             ntab = len(self.intables)
410
411#         if len(stab.getbeamnos()) > 1:
412#             asaplog.post()
413#             asaplog.push("Mult-beam data is not supported by this module.")
414#             asaplog.post("ERROR")
415#             return
416
417#         valid_ifs = stab.getifnos()
418#         if self.baseif < 0:
419#             self.baseif = valid_ifs[0]
420#             asaplog.post()
421#             asaplog.push("IFNO is not selected. Using the first IF in the first scantable. Reference IFNO = %d" % (self.baseif))
422
423#         if not (self.baseif in valid_ifs):
424#             asaplog.post()
425#             errmsg = "IF%d does not exist in the first scantable" %  \
426#                      self.baseif
427#             raise RuntimeError, errmsg
428
429#         asaplog.push("Start selecting tables and IFNOs to solve.")
430#         asaplog.push("Checking frequency of the reference IF")
431#         unit_org = stab.get_unit()
432#         coord = stab._getcoordinfo()
433#         frame_org = coord[1]
434#         stab.set_unit("Hz")
435#         if len(self.freqframe) > 0:
436#             stab.set_freqframe(self.freqframe)
437#         stab.set_selection(ifs=[self.baseif])
438#         spx = stab._getabcissa()
439#         stab.set_selection()
440#         basech0 = spx[0]
441#         baseinc = spx[1]-spx[0]
442#         self.nchan = len(spx)
443#         # frequency tolerance
444#         if isinstance(self.freqtol, dict) and self.freqtol['unit'] == "Hz":
445#             vftol = abs(self.freqtol['value'])
446#         else:
447#             vftol = abs(baseinc * float(self.freqtol))
448#             self.freqtol = dict(value=vftol, unit="Hz")
449#         # tolerance of frequency increment
450#         inctol = abs(baseinc/float(self.nchan))
451#         asaplog.push("Reference frequency setup (Table = 0, IFNO = %d):  nchan = %d, chan0 = %f Hz, incr = %f Hz" % (self.baseif, self.nchan, basech0, baseinc))
452#         asaplog.push("Allowed frequency tolerance = %f Hz ( %f channels)" % (vftol, vftol/baseinc))
453#         poltype0 = stab.poltype()
454
455#         self.tables = []
456#         self.signalShift = []
457#         if self.dsbmode:
458#             self.imageShift = []
459
460#         for itab in range(ntab):
461#             asaplog.push("Table %d:" % itab)
462#             tab_selected = False
463#             if itab > 0:
464#                 if byname:
465#                     stab = scantable(self.intables[itab],average=False)
466#                 else:
467#                     stab = self.intables[itab]
468#                 unit_org = stab.get_unit()
469#                 coord = stab._getcoordinfo()
470#                 frame_org = coord[1]
471#                 stab.set_unit("Hz")
472#                 if len(self.freqframe) > 0:
473#                     stab.set_freqframe(self.freqframe)
474
475#             # Check POLTYPE should be equal to the first table.
476#             if stab.poltype() != poltype0:
477#                 asaplog.post()
478#                 raise Exception, "POLTYPE should be equal to the first table."
479#             # Multiple beam data may not handled properly
480#             if len(stab.getbeamnos()) > 1:
481#                 asaplog.post()
482#                 asaplog.push("table contains multiple beams. It may not be handled properly.")
483#                 asaplog.push("WARN")
484
485#             for ifno in stab.getifnos():
486#                 stab.set_selection(ifs=[ifno])
487#                 spx = stab._getabcissa()
488#                 if (len(spx) != self.nchan) or \
489#                    (abs(spx[0]-basech0) > vftol) or \
490#                    (abs(spx[1]-spx[0]-baseinc) > inctol):
491#                     continue
492#                 tab_selected = True
493#                 seltab = stab.copy()
494#                 seltab.set_unit(unit_org)
495#                 seltab.set_freqframe(frame_org)
496#                 self.tables.append(seltab)
497#                 self.signalShift.append((spx[0]-basech0)/baseinc)
498#                 if self.dsbmode:
499#                     self.imageShift.append(-self.signalShift[-1])
500#                 asaplog.push("- IF%d selected: sideband shift = %16.12e channels" % (ifno, self.signalShift[-1]))
501#             stab.set_selection()
502#             stab.set_unit(unit_org)
503#             stab.set_freqframe(frame_org)
504#             if not tab_selected:
505#                 asaplog.post()
506#                 asaplog.push("No data selected in Table %d" % itab)
507#                 asaplog.post("WARN")
508
509#         asaplog.push("Total number of IFs selected = %d" % len(self.tables))
510#         if len(self.tables) < 2:
511#             asaplog.post()
512#             raise RuntimeError, "At least 2 IFs are necessary for convolution!"
513
514#         if not self.dsbmode and len(self.imageShift) != len(self.signalShift):
515#             asaplog.post()
516#             errmsg = "User defined channel shift of image sideband has %d elements, while selected IFNOs are %d" % (len(self.imageShift), len(self.signalShift))
517#             errmsg += "\nThe frequency tolerance (freqtol) you set may be too small."
518#             raise RuntimeError, errmsg
519
520#         self.signalShift = numpy.array(self.signalShift)
521#         self.imageShift = numpy.array(self.imageShift)
522#         self.nshift = len(self.tables)
523
524#     @asaplog_post_dec
525#     def _preprocess_tables(self):
526#         ### temporary method to preprocess data
527#         ### Do time averaging for now.
528#         for itab in range(len(self.tables)):
529#             self.tables[itab] = self.tables[itab].average_time(scanav=False, weight="tintsys")
530
531
532# ########################################################################
533#     def _Deconvolution(self, data_array, shift, threshold=0.00000001):
534#         FObs = []
535#         Reject = 0
536#         nshift, nchan = data_array.shape
537#         nspec = nshift*(nshift-1)/2
538#         ifftObs  = numpy.zeros((nspec, nchan), numpy.float)
539#         for i in range(nshift):
540#            F = FFT.fft(data_array[i])
541#            FObs.append(F)
542#         z = 0
543#         for i in range(nshift):
544#             for j in range(i+1, nshift):
545#                 Fobs = (FObs[i]+FObs[j])/2.0
546#                 dX = (shift[j]-shift[i])*2.0*math.pi/float(self.nchan)
547#                 #print 'dX,i,j=',dX,i,j
548#                 for k in range(1,self.nchan):
549#                     if math.fabs(math.sin(dX*k)) > threshold:
550#                         Fobs[k] += ((FObs[i][k]-FObs[j][k])/2.0/(1.0-math.cos(dX*k))*math.sin(dX*k))*1.0j
551#                     else: Reject += 1
552#                 ifftObs[z] = FFT.ifft(Fobs)
553#                 z += 1
554#         print 'Threshold=%s Reject=%d' % (threshold, Reject)
555#         return ifftObs
556
557#     def _combineResult(self, ifftObs):
558#         nspec = len(ifftObs)
559#         sum = ifftObs[0]
560#         for i in range(1,nspec):
561#             sum += ifftObs[i]
562#         return(sum/float(nspec))
563
564#     def _subtractOtherSide(self, data_array, shift, Data):
565#         sum = numpy.zeros(len(Data), numpy.float)
566#         numSP = len(data_array)
567#         for i in range(numSP):
568#             SPsub = data_array[i] - Data
569#             sum += self._shiftSpectrum(SPsub, -shift[i])
570#         return(sum/float(numSP))
571
572#     def _shiftSpectrum(self, data, Shift):
573#         Out = numpy.zeros(self.nchan, numpy.float)
574#         w2 = Shift % 1
575#         w1 = 1.0 - w2
576#         for i in range(self.nchan):
577#             c1 = int((Shift + i) % self.nchan)
578#             c2 = (c1 + 1) % self.nchan
579#             Out[c1] += data[i] * w1
580#             Out[c2] += data[i] * w2
581#         return Out.copy()
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