1 | import os, shutil |
---|
2 | import numpy |
---|
3 | import numpy.fft as FFT |
---|
4 | import math |
---|
5 | |
---|
6 | from asap.scantable import scantable |
---|
7 | from asap.parameters import rcParams |
---|
8 | from asap.logging import asaplog, asaplog_post_dec |
---|
9 | from asap.selector import selector |
---|
10 | from asap.asapgrid import asapgrid2 |
---|
11 | #from asap._asap import sidebandsep |
---|
12 | |
---|
13 | class 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.intables = None |
---|
41 | self.signalShift = [] |
---|
42 | self.imageShift = [] |
---|
43 | self.dsbmode = True |
---|
44 | self.getboth = False |
---|
45 | self.rejlimit = 0.2 |
---|
46 | self.baseif = -1 |
---|
47 | self.freqtol = 10. |
---|
48 | self.freqframe = "" |
---|
49 | self.solveother = False |
---|
50 | self.dirtol = [1.e-5, 1.e-5] # direction tolerance in rad (2 arcsec) |
---|
51 | |
---|
52 | self.tables = [] |
---|
53 | self.nshift = -1 |
---|
54 | self.nchan = -1 |
---|
55 | |
---|
56 | self.set_data(infiles) |
---|
57 | |
---|
58 | #self.separator = sidebandsep() |
---|
59 | |
---|
60 | @asaplog_post_dec |
---|
61 | def set_data(self, infiles): |
---|
62 | """ |
---|
63 | Set data to be processed. |
---|
64 | |
---|
65 | infiles : a list of filenames or scantables |
---|
66 | """ |
---|
67 | if not (type(infiles) in (list, tuple, numpy.ndarray)): |
---|
68 | infiles = [infiles] |
---|
69 | if isinstance(infiles[0], scantable): |
---|
70 | # a list of scantable |
---|
71 | for stab in infiles: |
---|
72 | if not isinstance(stab, scantable): |
---|
73 | asaplog.post() |
---|
74 | raise TypeError, "Input data is not a list of scantables." |
---|
75 | |
---|
76 | #self.separator._setdata(infiles) |
---|
77 | self._reset_data() |
---|
78 | self.intables = infiles |
---|
79 | else: |
---|
80 | # a list of filenames |
---|
81 | for name in infiles: |
---|
82 | if not os.path.exists(name): |
---|
83 | asaplog.post() |
---|
84 | raise ValueError, "Could not find input file '%s'" % name |
---|
85 | |
---|
86 | #self.separator._setdataname(infiles) |
---|
87 | self._reset_data() |
---|
88 | self.intables = infiles |
---|
89 | |
---|
90 | asaplog.push("%d files are set to process" % len(self.intables)) |
---|
91 | |
---|
92 | |
---|
93 | def _reset_data(self): |
---|
94 | del self.intables |
---|
95 | self.intables = None |
---|
96 | self.signalShift = [] |
---|
97 | #self.imageShift = [] |
---|
98 | self.tables = [] |
---|
99 | self.nshift = -1 |
---|
100 | self.nchan = -1 |
---|
101 | |
---|
102 | @asaplog_post_dec |
---|
103 | def set_frequency(self, baseif, freqtol, frame=""): |
---|
104 | """ |
---|
105 | Set IFNO and frequency tolerance to select data to process. |
---|
106 | |
---|
107 | Parameters: |
---|
108 | - reference IFNO to process in the first table in the list |
---|
109 | - frequency tolerance from reference IF to select data |
---|
110 | frame : frequency frame to select IF |
---|
111 | """ |
---|
112 | self._reset_if() |
---|
113 | self.baseif = baseif |
---|
114 | if isinstance(freqtol,dict) and freqtol["unit"] == "Hz": |
---|
115 | if freqtol['value'] > 0.: |
---|
116 | self.freqtol = freqtol |
---|
117 | else: |
---|
118 | asaplog.post() |
---|
119 | asaplog.push("Frequency tolerance should be positive value.") |
---|
120 | asaplog.post("ERROR") |
---|
121 | return |
---|
122 | else: |
---|
123 | # torelance in channel unit |
---|
124 | if freqtol > 0: |
---|
125 | self.freqtol = float(freqtol) |
---|
126 | else: |
---|
127 | asaplog.post() |
---|
128 | asaplog.push("Frequency tolerance should be positive value.") |
---|
129 | asaplog.post("ERROR") |
---|
130 | return |
---|
131 | self.freqframe = frame |
---|
132 | |
---|
133 | def _reset_if(self): |
---|
134 | self.baseif = -1 |
---|
135 | self.freqtol = 0 |
---|
136 | self.freqframe = "" |
---|
137 | self.signalShift = [] |
---|
138 | #self.imageShift = [] |
---|
139 | self.tables = [] |
---|
140 | self.nshift = 0 |
---|
141 | self.nchan = -1 |
---|
142 | |
---|
143 | @asaplog_post_dec |
---|
144 | def set_dirtol(self, dirtol=[1.e-5,1.e-5]): |
---|
145 | """ |
---|
146 | Set tolerance of direction to select data |
---|
147 | """ |
---|
148 | # direction tolerance in rad |
---|
149 | if not (type(dirtol) in [list, tuple, numpy.ndarray]): |
---|
150 | dirtol = [dirtol, dirtol] |
---|
151 | if len(dirtol) == 1: |
---|
152 | dirtol = [dirtol[0], dirtol[0]] |
---|
153 | if len(dirtol) > 1: |
---|
154 | self.dirtol = dirtol[0:2] |
---|
155 | else: |
---|
156 | asaplog.post() |
---|
157 | asaplog.push("Invalid direction tolerance. Should be a list of float in unit radian") |
---|
158 | asaplog.post("ERROR") |
---|
159 | return |
---|
160 | asaplog.post("Set direction tolerance [%f, %f] (rad)" % \ |
---|
161 | (self.dirtol[0], self.dirtol[1])) |
---|
162 | |
---|
163 | @asaplog_post_dec |
---|
164 | def set_shift(self, mode="DSB", imageshift=None): |
---|
165 | """ |
---|
166 | Set shift mode and channel shift of image band. |
---|
167 | |
---|
168 | mode : shift mode ['DSB'|'SSB'] |
---|
169 | When mode='DSB', imageshift is assumed to be equal |
---|
170 | to the shift of signal sideband but in opposite direction. |
---|
171 | imageshift : a list of number of channel shift in image band of |
---|
172 | each scantable. valid only mode='SSB' |
---|
173 | """ |
---|
174 | if mode.upper().startswith("S"): |
---|
175 | if not imageshift: |
---|
176 | raise ValueError, "Need to set shift value of image sideband" |
---|
177 | self.dsbmode = False |
---|
178 | self.imageShift = imageshift |
---|
179 | asaplog.push("Image sideband shift is set manually: %s" % str(self.imageShift)) |
---|
180 | else: |
---|
181 | # DSB mode |
---|
182 | self.dsbmode = True |
---|
183 | self.imageShift = [] |
---|
184 | |
---|
185 | @asaplog_post_dec |
---|
186 | def set_both(self, flag=False): |
---|
187 | """ |
---|
188 | Resolve both image and signal sideband when True. |
---|
189 | """ |
---|
190 | self.getboth = flag |
---|
191 | if self.getboth: |
---|
192 | asaplog.push("Both signal and image sidebands are solved and output as separate tables.") |
---|
193 | else: |
---|
194 | asaplog.push("Only signal sideband is solved and output as an table.") |
---|
195 | |
---|
196 | @asaplog_post_dec |
---|
197 | def set_limit(self, threshold=0.2): |
---|
198 | """ |
---|
199 | Set rejection limit of solution. |
---|
200 | """ |
---|
201 | #self.separator._setlimit(abs(threshold)) |
---|
202 | self.rejlimit = threshold |
---|
203 | asaplog.push("The threshold of rejection is set to %f" % self.rejlimit) |
---|
204 | |
---|
205 | |
---|
206 | @asaplog_post_dec |
---|
207 | def set_solve_other(self, flag=False): |
---|
208 | """ |
---|
209 | Calculate spectra by subtracting the solution of the other sideband |
---|
210 | when True. |
---|
211 | """ |
---|
212 | self.solveother = flag |
---|
213 | if flag: |
---|
214 | asaplog.push("Expert mode: solution are obtained by subtraction of the other sideband.") |
---|
215 | |
---|
216 | |
---|
217 | @asaplog_post_dec |
---|
218 | def separate(self, outname="", overwrite=False): |
---|
219 | """ |
---|
220 | Invoke sideband separation. |
---|
221 | |
---|
222 | outname : a name of output scantable |
---|
223 | overwrite : overwrite existing table |
---|
224 | """ |
---|
225 | # List up valid scantables and IFNOs to convolve. |
---|
226 | #self.separator._separate() |
---|
227 | self._setup_shift() |
---|
228 | #self._preprocess_tables() |
---|
229 | |
---|
230 | nshift = len(self.tables) |
---|
231 | signaltab = self._grid_outtable(self.tables[0].copy()) |
---|
232 | if self.getboth: |
---|
233 | imagetab = signaltab.copy() |
---|
234 | |
---|
235 | rejrow = [] |
---|
236 | for irow in xrange(signaltab.nrow()): |
---|
237 | currpol = signaltab.getpol(irow) |
---|
238 | currbeam = signaltab.getbeam(irow) |
---|
239 | currdir = signaltab.get_directionval(irow) |
---|
240 | spec_array, tabidx = self._get_specarray(polid=currpol,\ |
---|
241 | beamid=currbeam,\ |
---|
242 | dir=currdir) |
---|
243 | #if not spec_array: |
---|
244 | if len(tabidx) == 0: |
---|
245 | asaplog.post() |
---|
246 | asaplog.push("skipping row %d" % irow) |
---|
247 | rejrow.append(irow) |
---|
248 | continue |
---|
249 | signal = self._solve_signal(spec_array, tabidx) |
---|
250 | signaltab.set_spectrum(signal, irow) |
---|
251 | if self.getboth: |
---|
252 | image = self._solve_image(spec_array, tabidx) |
---|
253 | imagetab.set_spectrum(image, irow) |
---|
254 | |
---|
255 | # TODO: Need to remove rejrow form scantables here |
---|
256 | signaltab.flag_row(rejrow) |
---|
257 | if self.getboth: |
---|
258 | imagetab.flag_row(rejrow) |
---|
259 | |
---|
260 | if outname == "": |
---|
261 | outname = "sbsepareted.asap" |
---|
262 | signalname = outname + ".signalband" |
---|
263 | if os.path.exists(signalname): |
---|
264 | if not overwrite: |
---|
265 | raise Exception, "Output file '%s' exists." % signalname |
---|
266 | else: |
---|
267 | shutil.rmtree(signalname) |
---|
268 | signaltab.save(signalname) |
---|
269 | if self.getboth: |
---|
270 | # Warnings |
---|
271 | asaplog.post() |
---|
272 | asaplog.push("Saving IMAGE sideband.") |
---|
273 | asaplog.push("Note, frequency information of IMAGE sideband cannot be properly filled so far. (future development)") |
---|
274 | asaplog.push("Storing frequency setting of SIGNAL sideband in FREQUENCIES table for now.") |
---|
275 | asaplog.post("WARN") |
---|
276 | |
---|
277 | imagename = outname + ".imageband" |
---|
278 | if os.path.exists(imagename): |
---|
279 | if not overwrite: |
---|
280 | raise Exception, "Output file '%s' exists." % imagename |
---|
281 | else: |
---|
282 | shutil.rmtree(imagename) |
---|
283 | imagetab.save(imagename) |
---|
284 | |
---|
285 | |
---|
286 | def _solve_signal(self, data, tabidx=None): |
---|
287 | if not tabidx: |
---|
288 | tabidx = range(len(data)) |
---|
289 | |
---|
290 | tempshift = [] |
---|
291 | dshift = [] |
---|
292 | if self.solveother: |
---|
293 | for idx in tabidx: |
---|
294 | tempshift.append(-self.imageShift[idx]) |
---|
295 | dshift.append(self.signalShift[idx] - self.imageShift[idx]) |
---|
296 | else: |
---|
297 | for idx in tabidx: |
---|
298 | tempshift.append(-self.signalShift[idx]) |
---|
299 | dshift.append(self.imageShift[idx] - self.signalShift[idx]) |
---|
300 | |
---|
301 | shiftdata = numpy.zeros(data.shape, numpy.float) |
---|
302 | for i in range(len(data)): |
---|
303 | shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i]) |
---|
304 | ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit) |
---|
305 | result_image = self._combineResult(ifftdata) |
---|
306 | if not self.solveother: |
---|
307 | return result_image |
---|
308 | result_signal = self._subtractOtherSide(shiftdata, dshift, result_image) |
---|
309 | return result_signal |
---|
310 | |
---|
311 | |
---|
312 | def _solve_image(self, data, tabidx=None): |
---|
313 | if not tabidx: |
---|
314 | tabidx = range(len(data)) |
---|
315 | |
---|
316 | tempshift = [] |
---|
317 | dshift = [] |
---|
318 | if self.solveother: |
---|
319 | for idx in tabidx: |
---|
320 | tempshift.append(-self.signalShift[idx]) |
---|
321 | dshift.append(self.imageShift[idx] - self.signalShift[idx]) |
---|
322 | else: |
---|
323 | for idx in tabidx: |
---|
324 | tempshift.append(-self.imageShift[idx]) |
---|
325 | dshift.append(self.signalShift[idx] - self.imageShift[idx]) |
---|
326 | |
---|
327 | shiftdata = numpy.zeros(data.shape, numpy.float) |
---|
328 | for i in range(len(data)): |
---|
329 | shiftdata[i] = self._shiftSpectrum(data[i], tempshift[i]) |
---|
330 | ifftdata = self._Deconvolution(shiftdata, dshift, self.rejlimit) |
---|
331 | result_image = self._combineResult(ifftdata) |
---|
332 | if not self.solveother: |
---|
333 | return result_image |
---|
334 | result_signal = self._subtractOtherSide(shiftdata, dshift, result_image) |
---|
335 | return result_signal |
---|
336 | |
---|
337 | @asaplog_post_dec |
---|
338 | def _grid_outtable(self, table): |
---|
339 | # Generate gridded table for output (Just to get rows) |
---|
340 | gridder = asapgrid2(table) |
---|
341 | gridder.setIF(self.baseif) |
---|
342 | |
---|
343 | cellx = str(self.dirtol[0])+"rad" |
---|
344 | celly = str(self.dirtol[1])+"rad" |
---|
345 | dirarr = numpy.array(table.get_directionval()).transpose() |
---|
346 | mapx = dirarr[0].max() - dirarr[0].min() |
---|
347 | mapy = dirarr[1].max() - dirarr[1].min() |
---|
348 | nx = max(1, numpy.ceil(mapx/self.dirtol[0])) |
---|
349 | ny = max(1, numpy.ceil(mapy/self.dirtol[0])) |
---|
350 | |
---|
351 | asaplog.push("Regrid output scantable with cell = [%s, %s]" % \ |
---|
352 | (cellx, celly)) |
---|
353 | gridder.defineImage(nx=nx, ny=ny, cellx=cellx, celly=celly) |
---|
354 | gridder.setFunc(func='box', width=1) |
---|
355 | gridder.setWeight(weightType='uniform') |
---|
356 | gridder.grid() |
---|
357 | return gridder.getResult() |
---|
358 | |
---|
359 | |
---|
360 | @asaplog_post_dec |
---|
361 | def _get_specarray(self, polid=None, beamid=None, dir=None): |
---|
362 | ntable = len(self.tables) |
---|
363 | spec_array = numpy.zeros((ntable, self.nchan), numpy.float) |
---|
364 | nspec = 0 |
---|
365 | asaplog.push("Start data selection by POL=%d, BEAM=%d, direction=[%f, %f]" % (polid, beamid, dir[0], dir[1])) |
---|
366 | tabidx = [] |
---|
367 | for itab in range(ntable): |
---|
368 | tab = self.tables[itab] |
---|
369 | # Select rows by POLNO and BEAMNO |
---|
370 | try: |
---|
371 | tab.set_selection(pols=[polid], beams=[beamid]) |
---|
372 | if tab.nrow() > 0: tabidx.append(itab) |
---|
373 | except: # no selection |
---|
374 | asaplog.post() |
---|
375 | asaplog.push("table %d - No spectrum ....skipping the table" % (itab)) |
---|
376 | asaplog.post("WARN") |
---|
377 | continue |
---|
378 | |
---|
379 | # Select rows by direction |
---|
380 | spec = numpy.zeros(self.nchan, numpy.float) |
---|
381 | selrow = [] |
---|
382 | for irow in range(tab.nrow()): |
---|
383 | currdir = tab.get_directionval(irow) |
---|
384 | if (abs(currdir[0] - dir[0]) > self.dirtol[0]) or \ |
---|
385 | (abs(currdir[1] - dir[1]) > self.dirtol[1]): |
---|
386 | continue |
---|
387 | selrow.append(irow) |
---|
388 | if len(selrow) == 0: |
---|
389 | asaplog.post() |
---|
390 | asaplog.push("table %d - No spectrum ....skipping the table" % (itab)) |
---|
391 | asaplog.post("WARN") |
---|
392 | continue |
---|
393 | else: |
---|
394 | seltab = tab.copy() |
---|
395 | seltab.set_selection(selector(rows=selrow)) |
---|
396 | |
---|
397 | if tab.nrow() > 1: |
---|
398 | asaplog.push("table %d - More than a spectrum selected. averaging rows..." % (itab)) |
---|
399 | tab = seltab.average_time(scanav=False, weight="tintsys") |
---|
400 | else: |
---|
401 | tab = seltab |
---|
402 | |
---|
403 | spec_array[nspec] = tab._getspectrum() |
---|
404 | nspec += 1 |
---|
405 | |
---|
406 | if nspec != ntable: |
---|
407 | asaplog.post() |
---|
408 | #asaplog.push("Some tables has no spectrum with POL=%d BEAM=%d. averaging rows..." % (polid, beamid)) |
---|
409 | asaplog.push("Could not find corresponding rows in some tables.") |
---|
410 | asaplog.push("Number of spectra selected = %d (table: %d)" % (nspec, ntable)) |
---|
411 | if nspec < 2: |
---|
412 | asaplog.push("At least 2 spectra are necessary for convolution") |
---|
413 | asaplog.post("ERROR") |
---|
414 | return False, tabidx |
---|
415 | |
---|
416 | return spec_array[0:nspec], tabidx |
---|
417 | |
---|
418 | |
---|
419 | @asaplog_post_dec |
---|
420 | def _setup_shift(self): |
---|
421 | ### define self.tables, self.signalShift, and self.imageShift |
---|
422 | if not self.intables: |
---|
423 | asaplog.post() |
---|
424 | raise RuntimeError, "Input data is not defined." |
---|
425 | #if self.baseif < 0: |
---|
426 | # asaplog.post() |
---|
427 | # raise RuntimeError, "Reference IFNO is not defined." |
---|
428 | |
---|
429 | byname = False |
---|
430 | #if not self.intables: |
---|
431 | if isinstance(self.intables[0], str): |
---|
432 | # A list of file name is given |
---|
433 | if not os.path.exists(self.intables[0]): |
---|
434 | asaplog.post() |
---|
435 | raise RuntimeError, "Could not find '%s'" % self.intables[0] |
---|
436 | |
---|
437 | stab = scantable(self.intables[0],average=False) |
---|
438 | ntab = len(self.intables) |
---|
439 | byname = True |
---|
440 | else: |
---|
441 | stab = self.intables[0] |
---|
442 | ntab = len(self.intables) |
---|
443 | |
---|
444 | if len(stab.getbeamnos()) > 1: |
---|
445 | asaplog.post() |
---|
446 | asaplog.push("Mult-beam data is not supported by this module.") |
---|
447 | asaplog.post("ERROR") |
---|
448 | return |
---|
449 | |
---|
450 | valid_ifs = stab.getifnos() |
---|
451 | if self.baseif < 0: |
---|
452 | self.baseif = valid_ifs[0] |
---|
453 | asaplog.post() |
---|
454 | asaplog.push("IFNO is not selected. Using the first IF in the first scantable. Reference IFNO = %d" % (self.baseif)) |
---|
455 | |
---|
456 | if not (self.baseif in valid_ifs): |
---|
457 | asaplog.post() |
---|
458 | errmsg = "IF%d does not exist in the first scantable" % \ |
---|
459 | self.baseif |
---|
460 | raise RuntimeError, errmsg |
---|
461 | |
---|
462 | asaplog.push("Start selecting tables and IFNOs to solve.") |
---|
463 | asaplog.push("Cheching frequency of the reference IF") |
---|
464 | unit_org = stab.get_unit() |
---|
465 | coord = stab._getcoordinfo() |
---|
466 | frame_org = coord[1] |
---|
467 | stab.set_unit("Hz") |
---|
468 | if len(self.freqframe) > 0: |
---|
469 | stab.set_freqframe(self.freqframe) |
---|
470 | stab.set_selection(ifs=[self.baseif]) |
---|
471 | spx = stab._getabcissa() |
---|
472 | stab.set_selection() |
---|
473 | basech0 = spx[0] |
---|
474 | baseinc = spx[1]-spx[0] |
---|
475 | self.nchan = len(spx) |
---|
476 | if isinstance(self.freqtol, float): |
---|
477 | vftol = abs(baseinc * self.freqtol) |
---|
478 | self.freqtol = dict(value=vftol, unit="Hz") |
---|
479 | else: |
---|
480 | vftol = abs(self.freqtol['value']) |
---|
481 | inctol = abs(baseinc/float(self.nchan)) |
---|
482 | asaplog.push("Reference frequency setup (Table = 0, IFNO = %d): nchan = %d, chan0 = %f Hz, incr = %f Hz" % (self.baseif, self.nchan, basech0, baseinc)) |
---|
483 | asaplog.push("Allowed frequency tolerance = %f Hz ( %f channels)" % (vftol, vftol/baseinc)) |
---|
484 | poltype0 = stab.poltype() |
---|
485 | |
---|
486 | self.tables = [] |
---|
487 | self.signalShift = [] |
---|
488 | if self.dsbmode: |
---|
489 | self.imageShift = [] |
---|
490 | |
---|
491 | for itab in range(ntab): |
---|
492 | asaplog.push("Table %d:" % itab) |
---|
493 | tab_selected = False |
---|
494 | if itab > 0: |
---|
495 | if byname: |
---|
496 | stab = scantable(self.intables[itab],average=False) |
---|
497 | self.intables.append(stab) |
---|
498 | else: |
---|
499 | stab = self.intables[itab] |
---|
500 | unit_org = stab.get_unit() |
---|
501 | coord = stab._getcoordinfo() |
---|
502 | frame_org = coord[1] |
---|
503 | stab.set_unit("Hz") |
---|
504 | if len(self.freqframe) > 0: |
---|
505 | stab.set_freqframe(self.freqframe) |
---|
506 | |
---|
507 | # Check POLTYPE should be equal to the first table. |
---|
508 | if stab.poltype() != poltype0: |
---|
509 | asaplog.post() |
---|
510 | raise Exception, "POLTYPE should be equal to the first table." |
---|
511 | # Multiple beam data may not handled properly |
---|
512 | if len(stab.getbeamnos()) > 1: |
---|
513 | asaplog.post() |
---|
514 | asaplog.push("table contains multiple beams. It may not be handled properly.") |
---|
515 | asaplog.push("WARN") |
---|
516 | |
---|
517 | for ifno in stab.getifnos(): |
---|
518 | stab.set_selection(ifs=[ifno]) |
---|
519 | spx = stab._getabcissa() |
---|
520 | if (len(spx) != self.nchan) or \ |
---|
521 | (abs(spx[0]-basech0) > vftol) or \ |
---|
522 | (abs(spx[1]-spx[0]-baseinc) > inctol): |
---|
523 | continue |
---|
524 | tab_selected = True |
---|
525 | seltab = stab.copy() |
---|
526 | seltab.set_unit(unit_org) |
---|
527 | seltab.set_freqframe(frame_org) |
---|
528 | self.tables.append(seltab) |
---|
529 | self.signalShift.append((spx[0]-basech0)/baseinc) |
---|
530 | if self.dsbmode: |
---|
531 | self.imageShift.append(-self.signalShift[-1]) |
---|
532 | asaplog.push("- IF%d selected: sideband shift = %16.12e channels" % (ifno, self.signalShift[-1])) |
---|
533 | stab.set_selection() |
---|
534 | stab.set_unit(unit_org) |
---|
535 | stab.set_freqframe(frame_org) |
---|
536 | if not tab_selected: |
---|
537 | asaplog.post() |
---|
538 | asaplog.push("No data selected in Table %d" % itab) |
---|
539 | asaplog.post("WARN") |
---|
540 | |
---|
541 | asaplog.push("Total number of IFs selected = %d" % len(self.tables)) |
---|
542 | if len(self.tables) < 2: |
---|
543 | asaplog.post() |
---|
544 | raise RuntimeError, "At least 2 IFs are necessary for convolution!" |
---|
545 | |
---|
546 | if not self.dsbmode and len(self.imageShift) != len(self.signalShift): |
---|
547 | asaplog.post() |
---|
548 | errmsg = "User defined channel shift of image sideband has %d elements, while selected IFNOs are %d" % (len(self.imageShift), len(self.signalShift)) |
---|
549 | raise RuntimeError, errmsg |
---|
550 | |
---|
551 | self.signalShift = numpy.array(self.signalShift) |
---|
552 | self.imageShift = numpy.array(self.imageShift) |
---|
553 | self.nshift = len(self.tables) |
---|
554 | |
---|
555 | @asaplog_post_dec |
---|
556 | def _preprocess_tables(self): |
---|
557 | ### temporary method to preprocess data |
---|
558 | ### Do time averaging for now. |
---|
559 | for itab in range(len(self.tables)): |
---|
560 | self.tables[itab] = self.tables[itab].average_time(scanav=False, weight="tintsys") |
---|
561 | |
---|
562 | |
---|
563 | # def save(self, outfile, outform="ASAP", overwrite=False): |
---|
564 | # if not overwrite and os.path.exists(outfile): |
---|
565 | # raise RuntimeError, "Output file '%s' already exists" % outfile |
---|
566 | # |
---|
567 | # #self.separator._save(outfile, outform) |
---|
568 | |
---|
569 | # def done(self): |
---|
570 | # self.close() |
---|
571 | |
---|
572 | # def close(self): |
---|
573 | # pass |
---|
574 | # #del self.separator |
---|
575 | |
---|
576 | |
---|
577 | |
---|
578 | ######################################################################## |
---|
579 | def _Deconvolution(self, data_array, shift, threshold=0.00000001): |
---|
580 | FObs = [] |
---|
581 | Reject = 0 |
---|
582 | nshift, nchan = data_array.shape |
---|
583 | nspec = nshift*(nshift-1)/2 |
---|
584 | ifftObs = numpy.zeros((nspec, nchan), numpy.float) |
---|
585 | for i in range(nshift): |
---|
586 | F = FFT.fft(data_array[i]) |
---|
587 | FObs.append(F) |
---|
588 | z = 0 |
---|
589 | for i in range(nshift): |
---|
590 | for j in range(i+1, nshift): |
---|
591 | Fobs = (FObs[i]+FObs[j])/2.0 |
---|
592 | dX = (shift[j]-shift[i])*2.0*math.pi/float(self.nchan) |
---|
593 | #print 'dX,i,j=',dX,i,j |
---|
594 | for k in range(1,self.nchan): |
---|
595 | if math.fabs(math.sin(dX*k)) > threshold: |
---|
596 | Fobs[k] += ((FObs[i][k]-FObs[j][k])/2.0/(1.0-math.cos(dX*k))*math.sin(dX*k))*1.0j |
---|
597 | else: Reject += 1 |
---|
598 | ifftObs[z] = FFT.ifft(Fobs) |
---|
599 | z += 1 |
---|
600 | print 'Threshold=%s Reject=%d' % (threshold, Reject) |
---|
601 | return ifftObs |
---|
602 | |
---|
603 | def _combineResult(self, ifftObs): |
---|
604 | nspec = len(ifftObs) |
---|
605 | sum = ifftObs[0] |
---|
606 | for i in range(1,nspec): |
---|
607 | sum += ifftObs[i] |
---|
608 | return(sum/float(nspec)) |
---|
609 | |
---|
610 | def _subtractOtherSide(self, data_array, shift, Data): |
---|
611 | sum = numpy.zeros(len(Data), numpy.float) |
---|
612 | numSP = len(data_array) |
---|
613 | for i in range(numSP): |
---|
614 | SPsub = data_array[i] - Data |
---|
615 | sum += self._shiftSpectrum(SPsub, -shift[i]) |
---|
616 | return(sum/float(numSP)) |
---|
617 | |
---|
618 | def _shiftSpectrum(self, data, Shift): |
---|
619 | Out = numpy.zeros(self.nchan, numpy.float) |
---|
620 | w2 = Shift % 1 |
---|
621 | w1 = 1.0 - w2 |
---|
622 | for i in range(self.nchan): |
---|
623 | c1 = int((Shift + i) % self.nchan) |
---|
624 | c2 = (c1 + 1) % self.nchan |
---|
625 | Out[c1] += data[i] * w1 |
---|
626 | Out[c2] += data[i] * w2 |
---|
627 | return Out.copy() |
---|