1 | from asap.scantable import scantable |
---|
2 | from asap.parameters import rcParams |
---|
3 | from asap.logging import asaplog, asaplog_post_dec |
---|
4 | from asap.selector import selector |
---|
5 | #from asap import asaplotgui |
---|
6 | from asap.asapplotter import new_asaplot |
---|
7 | |
---|
8 | @asaplog_post_dec |
---|
9 | def average_time(*args, **kwargs): |
---|
10 | """ |
---|
11 | Return the (time) average of a scan or list of scans. [in channels only] |
---|
12 | The cursor of the output scan is set to 0 |
---|
13 | Parameters: |
---|
14 | one scan or comma separated scans or a list of scans |
---|
15 | mask: an optional mask (only used for 'var' and 'tsys' weighting) |
---|
16 | scanav: True averages each scan separately. |
---|
17 | False (default) averages all scans together, |
---|
18 | weight: Weighting scheme. |
---|
19 | 'none' (mean no weight) |
---|
20 | 'var' (1/var(spec) weighted) |
---|
21 | 'tsys' (1/Tsys**2 weighted) |
---|
22 | 'tint' (integration time weighted) |
---|
23 | 'tintsys' (Tint/Tsys**2) |
---|
24 | 'median' ( median averaging) |
---|
25 | align: align the spectra in velocity before averaging. It takes |
---|
26 | the time of the first spectrum in the first scantable |
---|
27 | as reference time. |
---|
28 | Example: |
---|
29 | # return a time averaged scan from scana and scanb |
---|
30 | # without using a mask |
---|
31 | scanav = average_time(scana,scanb) |
---|
32 | # or equivalent |
---|
33 | # scanav = average_time([scana, scanb]) |
---|
34 | # return the (time) averaged scan, i.e. the average of |
---|
35 | # all correlator cycles |
---|
36 | scanav = average_time(scan, scanav=True) |
---|
37 | """ |
---|
38 | scanav = False |
---|
39 | if kwargs.has_key('scanav'): |
---|
40 | scanav = kwargs.get('scanav') |
---|
41 | weight = 'tint' |
---|
42 | if kwargs.has_key('weight'): |
---|
43 | weight = kwargs.get('weight') |
---|
44 | mask = () |
---|
45 | if kwargs.has_key('mask'): |
---|
46 | mask = kwargs.get('mask') |
---|
47 | align = False |
---|
48 | if kwargs.has_key('align'): |
---|
49 | align = kwargs.get('align') |
---|
50 | compel = False |
---|
51 | if kwargs.has_key('compel'): |
---|
52 | compel = kwargs.get('compel') |
---|
53 | varlist = vars() |
---|
54 | if isinstance(args[0],list): |
---|
55 | lst = args[0] |
---|
56 | elif isinstance(args[0],tuple): |
---|
57 | lst = list(args[0]) |
---|
58 | else: |
---|
59 | lst = list(args) |
---|
60 | |
---|
61 | del varlist["kwargs"] |
---|
62 | varlist["args"] = "%d scantables" % len(lst) |
---|
63 | # need special formatting here for history... |
---|
64 | |
---|
65 | from asap._asap import stmath |
---|
66 | stm = stmath() |
---|
67 | for s in lst: |
---|
68 | if not isinstance(s,scantable): |
---|
69 | msg = "Please give a list of scantables" |
---|
70 | raise TypeError(msg) |
---|
71 | if scanav: scanav = "SCAN" |
---|
72 | else: scanav = "NONE" |
---|
73 | alignedlst = [] |
---|
74 | if align: |
---|
75 | refepoch = lst[0].get_time(0) |
---|
76 | for scan in lst: |
---|
77 | alignedlst.append(scan.freq_align(refepoch,insitu=False)) |
---|
78 | else: |
---|
79 | alignedlst = lst |
---|
80 | if weight.upper() == 'MEDIAN': |
---|
81 | # median doesn't support list of scantables - merge first |
---|
82 | merged = None |
---|
83 | if len(alignedlst) > 1: |
---|
84 | merged = merge(alignedlst) |
---|
85 | else: |
---|
86 | merged = alignedlst[0] |
---|
87 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav)) |
---|
88 | del merged |
---|
89 | else: |
---|
90 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav)) |
---|
91 | s = scantable(stm._new_average(alignedlst, compel, mask, weight.upper(), scanav)) |
---|
92 | s._add_history("average_time",varlist) |
---|
93 | |
---|
94 | return s |
---|
95 | |
---|
96 | @asaplog_post_dec |
---|
97 | def quotient(source, reference, preserve=True): |
---|
98 | """ |
---|
99 | Return the quotient of a 'source' (signal) scan and a 'reference' scan. |
---|
100 | The reference can have just one scan, even if the signal has many. Otherwise |
---|
101 | they must have the same number of scans. |
---|
102 | The cursor of the output scan is set to 0 |
---|
103 | Parameters: |
---|
104 | source: the 'on' scan |
---|
105 | reference: the 'off' scan |
---|
106 | preserve: you can preserve (default) the continuum or |
---|
107 | remove it. The equations used are |
---|
108 | preserve: Output = Toff * (on/off) - Toff |
---|
109 | remove: Output = Toff * (on/off) - Ton |
---|
110 | """ |
---|
111 | varlist = vars() |
---|
112 | from asap._asap import stmath |
---|
113 | stm = stmath() |
---|
114 | stm._setinsitu(False) |
---|
115 | s = scantable(stm._quotient(source, reference, preserve)) |
---|
116 | s._add_history("quotient",varlist) |
---|
117 | return s |
---|
118 | |
---|
119 | @asaplog_post_dec |
---|
120 | def dototalpower(calon, caloff, tcalval=0.0): |
---|
121 | """ |
---|
122 | Do calibration for CAL on,off signals. |
---|
123 | Adopted from GBTIDL dototalpower |
---|
124 | Parameters: |
---|
125 | calon: the 'cal on' subintegration |
---|
126 | caloff: the 'cal off' subintegration |
---|
127 | tcalval: user supplied Tcal value |
---|
128 | """ |
---|
129 | varlist = vars() |
---|
130 | from asap._asap import stmath |
---|
131 | stm = stmath() |
---|
132 | stm._setinsitu(False) |
---|
133 | s = scantable(stm._dototalpower(calon, caloff, tcalval)) |
---|
134 | s._add_history("dototalpower",varlist) |
---|
135 | return s |
---|
136 | |
---|
137 | @asaplog_post_dec |
---|
138 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0): |
---|
139 | """ |
---|
140 | Calculate a quotient (sig-ref/ref * Tsys) |
---|
141 | Adopted from GBTIDL dosigref |
---|
142 | Parameters: |
---|
143 | sig: on source data |
---|
144 | ref: reference data |
---|
145 | smooth: width of box car smoothing for reference |
---|
146 | tsysval: user specified Tsys (scalar only) |
---|
147 | tauval: user specified Tau (required if tsysval is set) |
---|
148 | """ |
---|
149 | varlist = vars() |
---|
150 | from asap._asap import stmath |
---|
151 | stm = stmath() |
---|
152 | stm._setinsitu(False) |
---|
153 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval)) |
---|
154 | s._add_history("dosigref",varlist) |
---|
155 | return s |
---|
156 | |
---|
157 | @asaplog_post_dec |
---|
158 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
---|
159 | """ |
---|
160 | Calibrate GBT position switched data |
---|
161 | Adopted from GBTIDL getps |
---|
162 | Currently calps identify the scans as position switched data if source |
---|
163 | type enum is pson or psoff. The data must contains 'CAL' signal |
---|
164 | on/off in each integration. To identify 'CAL' on state, the source type |
---|
165 | enum of poncal and poffcal need to be present in the source name field. |
---|
166 | (GBT MS data reading process to scantable automatically append these |
---|
167 | id names to the source names) |
---|
168 | |
---|
169 | Parameters: |
---|
170 | scantab: scantable |
---|
171 | scannos: list of scan numbers |
---|
172 | smooth: optional box smoothing order for the reference |
---|
173 | (default is 1 = no smoothing) |
---|
174 | tsysval: optional user specified Tsys (default is 0.0, |
---|
175 | use Tsys in the data) |
---|
176 | tauval: optional user specified Tau |
---|
177 | tcalval: optional user specified Tcal (default is 0.0, |
---|
178 | use Tcal value in the data) |
---|
179 | verify: Verify calibration if true |
---|
180 | """ |
---|
181 | varlist = vars() |
---|
182 | # check for the appropriate data |
---|
183 | ## s = scantab.get_scan('*_ps*') |
---|
184 | ## if s is None: |
---|
185 | ## msg = "The input data appear to contain no position-switch mode data." |
---|
186 | ## raise TypeError(msg) |
---|
187 | s = scantab.copy() |
---|
188 | from asap._asap import srctype |
---|
189 | sel = selector() |
---|
190 | sel.set_types( srctype.pson ) |
---|
191 | try: |
---|
192 | scantab.set_selection( sel ) |
---|
193 | except Exception, e: |
---|
194 | msg = "The input data appear to contain no position-switch mode data." |
---|
195 | raise TypeError(msg) |
---|
196 | s.set_selection() |
---|
197 | sel.reset() |
---|
198 | ssub = s.get_scan(scannos) |
---|
199 | if ssub is None: |
---|
200 | msg = "No data was found with given scan numbers!" |
---|
201 | raise TypeError(msg) |
---|
202 | #ssubon = ssub.get_scan('*calon') |
---|
203 | #ssuboff = ssub.get_scan('*[^calon]') |
---|
204 | sel.set_types( [srctype.poncal,srctype.poffcal] ) |
---|
205 | ssub.set_selection( sel ) |
---|
206 | ssubon = ssub.copy() |
---|
207 | ssub.set_selection() |
---|
208 | sel.reset() |
---|
209 | sel.set_types( [srctype.pson,srctype.psoff] ) |
---|
210 | ssub.set_selection( sel ) |
---|
211 | ssuboff = ssub.copy() |
---|
212 | ssub.set_selection() |
---|
213 | sel.reset() |
---|
214 | if ssubon.nrow() != ssuboff.nrow(): |
---|
215 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers." |
---|
216 | raise TypeError(msg) |
---|
217 | cals = dototalpower(ssubon, ssuboff, tcalval) |
---|
218 | #sig = cals.get_scan('*ps') |
---|
219 | #ref = cals.get_scan('*psr') |
---|
220 | sel.set_types( srctype.pson ) |
---|
221 | cals.set_selection( sel ) |
---|
222 | sig = cals.copy() |
---|
223 | cals.set_selection() |
---|
224 | sel.reset() |
---|
225 | sel.set_types( srctype.psoff ) |
---|
226 | cals.set_selection( sel ) |
---|
227 | ref = cals.copy() |
---|
228 | cals.set_selection() |
---|
229 | sel.reset() |
---|
230 | if sig.nscan() != ref.nscan(): |
---|
231 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers." |
---|
232 | raise TypeError(msg) |
---|
233 | |
---|
234 | #for user supplied Tsys |
---|
235 | if tsysval>0.0: |
---|
236 | if tauval<=0.0: |
---|
237 | msg = "Need to supply a valid tau to use the supplied Tsys" |
---|
238 | raise TypeError(msg) |
---|
239 | else: |
---|
240 | sig.recalc_azel() |
---|
241 | ref.recalc_azel() |
---|
242 | #msg = "Use of user specified Tsys is not fully implemented yet." |
---|
243 | #raise TypeError(msg) |
---|
244 | # use get_elevation to get elevation and |
---|
245 | # calculate a scaling factor using the formula |
---|
246 | # -> tsys use to dosigref |
---|
247 | |
---|
248 | #ress = dosigref(sig, ref, smooth, tsysval) |
---|
249 | ress = dosigref(sig, ref, smooth, tsysval, tauval) |
---|
250 | ### |
---|
251 | if verify: |
---|
252 | # get data |
---|
253 | import numpy |
---|
254 | precal={} |
---|
255 | postcal=[] |
---|
256 | keys=['ps','ps_calon','psr','psr_calon'] |
---|
257 | types=[srctype.pson,srctype.poncal,srctype.psoff,srctype.poffcal] |
---|
258 | ifnos=list(ssub.getifnos()) |
---|
259 | polnos=list(ssub.getpolnos()) |
---|
260 | sel=selector() |
---|
261 | for i in range(2): |
---|
262 | #ss=ssuboff.get_scan('*'+keys[2*i]) |
---|
263 | ll=[] |
---|
264 | for j in range(len(ifnos)): |
---|
265 | for k in range(len(polnos)): |
---|
266 | sel.set_ifs(ifnos[j]) |
---|
267 | sel.set_polarizations(polnos[k]) |
---|
268 | sel.set_types(types[2*i]) |
---|
269 | try: |
---|
270 | #ss.set_selection(sel) |
---|
271 | ssuboff.set_selection(sel) |
---|
272 | except: |
---|
273 | continue |
---|
274 | #ll.append(numpy.array(ss._getspectrum(0))) |
---|
275 | ll.append(numpy.array(ssuboff._getspectrum(0))) |
---|
276 | sel.reset() |
---|
277 | ssuboff.set_selection() |
---|
278 | precal[keys[2*i]]=ll |
---|
279 | #del ss |
---|
280 | #ss=ssubon.get_scan('*'+keys[2*i+1]) |
---|
281 | ll=[] |
---|
282 | for j in range(len(ifnos)): |
---|
283 | for k in range(len(polnos)): |
---|
284 | sel.set_ifs(ifnos[j]) |
---|
285 | sel.set_polarizations(polnos[k]) |
---|
286 | sel.set_types(types[2*i+1]) |
---|
287 | try: |
---|
288 | #ss.set_selection(sel) |
---|
289 | ssubon.set_selection(sel) |
---|
290 | except: |
---|
291 | continue |
---|
292 | #ll.append(numpy.array(ss._getspectrum(0))) |
---|
293 | ll.append(numpy.array(ssubon._getspectrum(0))) |
---|
294 | sel.reset() |
---|
295 | ssubon.set_selection() |
---|
296 | precal[keys[2*i+1]]=ll |
---|
297 | #del ss |
---|
298 | for j in range(len(ifnos)): |
---|
299 | for k in range(len(polnos)): |
---|
300 | sel.set_ifs(ifnos[j]) |
---|
301 | sel.set_polarizations(polnos[k]) |
---|
302 | try: |
---|
303 | ress.set_selection(sel) |
---|
304 | except: |
---|
305 | continue |
---|
306 | postcal.append(numpy.array(ress._getspectrum(0))) |
---|
307 | sel.reset() |
---|
308 | ress.set_selection() |
---|
309 | del sel |
---|
310 | # plot |
---|
311 | asaplog.post() |
---|
312 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
313 | asaplog.post('WARN') |
---|
314 | #p=asaplotgui.asaplotgui() |
---|
315 | p=new_asaplot() |
---|
316 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
317 | nr=len(ifnos)*len(polnos) |
---|
318 | titles=[] |
---|
319 | btics=[] |
---|
320 | if nr<4: |
---|
321 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False) |
---|
322 | for i in range(2*nr): |
---|
323 | b=False |
---|
324 | if i >= 2*nr-2: |
---|
325 | b=True |
---|
326 | btics.append(b) |
---|
327 | elif nr==4: |
---|
328 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False) |
---|
329 | for i in range(2*nr): |
---|
330 | b=False |
---|
331 | if i >= 2*nr-4: |
---|
332 | b=True |
---|
333 | btics.append(b) |
---|
334 | elif nr<7: |
---|
335 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
336 | for i in range(2*nr): |
---|
337 | if i >= 2*nr-4: |
---|
338 | b=True |
---|
339 | btics.append(b) |
---|
340 | else: |
---|
341 | asaplog.post() |
---|
342 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
---|
343 | asaplog.post('WARN') |
---|
344 | nr=6 |
---|
345 | for i in range(2*nr): |
---|
346 | b=False |
---|
347 | if i >= 2*nr-4: |
---|
348 | b=True |
---|
349 | btics.append(b) |
---|
350 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
351 | for i in range(nr): |
---|
352 | p.subplot(2*i) |
---|
353 | p.color=0 |
---|
354 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
355 | titles.append(title) |
---|
356 | #p.set_axes('title',title,fontsize=40) |
---|
357 | ymin=1.0e100 |
---|
358 | ymax=-1.0e100 |
---|
359 | nchan=s.nchan() |
---|
360 | edge=int(nchan*0.01) |
---|
361 | for j in range(4): |
---|
362 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
363 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
364 | ymin=min(ymin,spmin) |
---|
365 | ymax=max(ymax,spmax) |
---|
366 | for j in range(4): |
---|
367 | if i==0: |
---|
368 | p.set_line(label=keys[j]) |
---|
369 | else: |
---|
370 | p.legend() |
---|
371 | p.plot(precal[keys[j]][i]) |
---|
372 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
373 | if not btics[2*i]: |
---|
374 | p.axes.set_xticks([]) |
---|
375 | p.subplot(2*i+1) |
---|
376 | p.color=0 |
---|
377 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
378 | titles.append(title) |
---|
379 | #p.set_axes('title',title) |
---|
380 | p.legend() |
---|
381 | ymin=postcal[i][edge:nchan-edge].min() |
---|
382 | ymax=postcal[i][edge:nchan-edge].max() |
---|
383 | p.plot(postcal[i]) |
---|
384 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
385 | if not btics[2*i+1]: |
---|
386 | p.axes.set_xticks([]) |
---|
387 | for i in range(2*nr): |
---|
388 | p.subplot(i) |
---|
389 | p.set_axes('title',titles[i],fontsize='medium') |
---|
390 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
391 | if x.upper() == 'N': |
---|
392 | p.quit() |
---|
393 | del p |
---|
394 | return scabtab |
---|
395 | p.quit() |
---|
396 | del p |
---|
397 | ### |
---|
398 | ress._add_history("calps", varlist) |
---|
399 | return ress |
---|
400 | |
---|
401 | @asaplog_post_dec |
---|
402 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
---|
403 | """ |
---|
404 | Do full (but a pair of scans at time) processing of GBT Nod data |
---|
405 | calibration. |
---|
406 | Adopted from GBTIDL's getnod |
---|
407 | Parameters: |
---|
408 | scantab: scantable |
---|
409 | scannos: a pair of scan numbers, or the first scan number of the pair |
---|
410 | smooth: box car smoothing order |
---|
411 | tsysval: optional user specified Tsys value |
---|
412 | tauval: optional user specified tau value (not implemented yet) |
---|
413 | tcalval: optional user specified Tcal value |
---|
414 | verify: Verify calibration if true |
---|
415 | """ |
---|
416 | varlist = vars() |
---|
417 | from asap._asap import stmath |
---|
418 | from asap._asap import srctype |
---|
419 | stm = stmath() |
---|
420 | stm._setinsitu(False) |
---|
421 | |
---|
422 | # check for the appropriate data |
---|
423 | ## s = scantab.get_scan('*_nod*') |
---|
424 | ## if s is None: |
---|
425 | ## msg = "The input data appear to contain no Nod observing mode data." |
---|
426 | ## raise TypeError(msg) |
---|
427 | s = scantab.copy() |
---|
428 | sel = selector() |
---|
429 | sel.set_types( srctype.nod ) |
---|
430 | try: |
---|
431 | s.set_selection( sel ) |
---|
432 | except Exception, e: |
---|
433 | msg = "The input data appear to contain no Nod observing mode data." |
---|
434 | raise TypeError(msg) |
---|
435 | sel.reset() |
---|
436 | del sel |
---|
437 | del s |
---|
438 | |
---|
439 | # need check correspondance of each beam with sig-ref ... |
---|
440 | # check for timestamps, scan numbers, subscan id (not available in |
---|
441 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig |
---|
442 | # and beam 1 - ref...) |
---|
443 | # First scan number of paired scans or list of pairs of |
---|
444 | # scan numbers (has to have even number of pairs.) |
---|
445 | |
---|
446 | #data splitting |
---|
447 | scan1no = scan2no = 0 |
---|
448 | |
---|
449 | if len(scannos)==1: |
---|
450 | scan1no = scannos[0] |
---|
451 | scan2no = scannos[0]+1 |
---|
452 | pairScans = [scan1no, scan2no] |
---|
453 | else: |
---|
454 | #if len(scannos)>2: |
---|
455 | # msg = "calnod can only process a pair of nod scans at time." |
---|
456 | # raise TypeError(msg) |
---|
457 | # |
---|
458 | #if len(scannos)==2: |
---|
459 | # scan1no = scannos[0] |
---|
460 | # scan2no = scannos[1] |
---|
461 | pairScans = list(scannos) |
---|
462 | |
---|
463 | if tsysval>0.0: |
---|
464 | if tauval<=0.0: |
---|
465 | msg = "Need to supply a valid tau to use the supplied Tsys" |
---|
466 | raise TypeError(msg) |
---|
467 | else: |
---|
468 | scantab.recalc_azel() |
---|
469 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval)) |
---|
470 | ### |
---|
471 | if verify: |
---|
472 | # get data |
---|
473 | import numpy |
---|
474 | precal={} |
---|
475 | postcal=[] |
---|
476 | keys=['','_calon'] |
---|
477 | types=[srctype.nod,srctype.nodcal] |
---|
478 | ifnos=list(scantab.getifnos()) |
---|
479 | polnos=list(scantab.getpolnos()) |
---|
480 | sel=selector() |
---|
481 | ss = scantab.copy() |
---|
482 | for i in range(2): |
---|
483 | #ss=scantab.get_scan('*'+keys[i]) |
---|
484 | ll=[] |
---|
485 | ll2=[] |
---|
486 | for j in range(len(ifnos)): |
---|
487 | for k in range(len(polnos)): |
---|
488 | sel.set_ifs(ifnos[j]) |
---|
489 | sel.set_polarizations(polnos[k]) |
---|
490 | sel.set_scans(pairScans[0]) |
---|
491 | sel.set_types(types[i]) |
---|
492 | try: |
---|
493 | ss.set_selection(sel) |
---|
494 | except: |
---|
495 | continue |
---|
496 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
497 | sel.reset() |
---|
498 | ss.set_selection() |
---|
499 | sel.set_ifs(ifnos[j]) |
---|
500 | sel.set_polarizations(polnos[k]) |
---|
501 | sel.set_scans(pairScans[1]) |
---|
502 | sel.set_types(types[i]) |
---|
503 | try: |
---|
504 | ss.set_selection(sel) |
---|
505 | except: |
---|
506 | ll.pop() |
---|
507 | continue |
---|
508 | ll2.append(numpy.array(ss._getspectrum(0))) |
---|
509 | sel.reset() |
---|
510 | ss.set_selection() |
---|
511 | key='%s%s' %(pairScans[0],keys[i]) |
---|
512 | precal[key]=ll |
---|
513 | key='%s%s' %(pairScans[1],keys[i]) |
---|
514 | precal[key]=ll2 |
---|
515 | #del ss |
---|
516 | keys=precal.keys() |
---|
517 | for j in range(len(ifnos)): |
---|
518 | for k in range(len(polnos)): |
---|
519 | sel.set_ifs(ifnos[j]) |
---|
520 | sel.set_polarizations(polnos[k]) |
---|
521 | sel.set_scans(pairScans[0]) |
---|
522 | try: |
---|
523 | resspec.set_selection(sel) |
---|
524 | except: |
---|
525 | continue |
---|
526 | postcal.append(numpy.array(resspec._getspectrum(0))) |
---|
527 | sel.reset() |
---|
528 | resspec.set_selection() |
---|
529 | del sel |
---|
530 | # plot |
---|
531 | asaplog.post() |
---|
532 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
533 | asaplog.post('WARN') |
---|
534 | #p=asaplotgui.asaplotgui() |
---|
535 | p=new_asaplot() |
---|
536 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
537 | nr=len(ifnos)*len(polnos) |
---|
538 | titles=[] |
---|
539 | btics=[] |
---|
540 | if nr<4: |
---|
541 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False) |
---|
542 | for i in range(2*nr): |
---|
543 | b=False |
---|
544 | if i >= 2*nr-2: |
---|
545 | b=True |
---|
546 | btics.append(b) |
---|
547 | elif nr==4: |
---|
548 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False) |
---|
549 | for i in range(2*nr): |
---|
550 | b=False |
---|
551 | if i >= 2*nr-4: |
---|
552 | b=True |
---|
553 | btics.append(b) |
---|
554 | elif nr<7: |
---|
555 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
556 | for i in range(2*nr): |
---|
557 | if i >= 2*nr-4: |
---|
558 | b=True |
---|
559 | btics.append(b) |
---|
560 | else: |
---|
561 | asaplog.post() |
---|
562 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
---|
563 | asaplog.post('WARN') |
---|
564 | nr=6 |
---|
565 | for i in range(2*nr): |
---|
566 | b=False |
---|
567 | if i >= 2*nr-4: |
---|
568 | b=True |
---|
569 | btics.append(b) |
---|
570 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
571 | for i in range(nr): |
---|
572 | p.subplot(2*i) |
---|
573 | p.color=0 |
---|
574 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
575 | titles.append(title) |
---|
576 | #p.set_axes('title',title,fontsize=40) |
---|
577 | ymin=1.0e100 |
---|
578 | ymax=-1.0e100 |
---|
579 | nchan=scantab.nchan() |
---|
580 | edge=int(nchan*0.01) |
---|
581 | for j in range(4): |
---|
582 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
583 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
584 | ymin=min(ymin,spmin) |
---|
585 | ymax=max(ymax,spmax) |
---|
586 | for j in range(4): |
---|
587 | if i==0: |
---|
588 | p.set_line(label=keys[j]) |
---|
589 | else: |
---|
590 | p.legend() |
---|
591 | p.plot(precal[keys[j]][i]) |
---|
592 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
593 | if not btics[2*i]: |
---|
594 | p.axes.set_xticks([]) |
---|
595 | p.subplot(2*i+1) |
---|
596 | p.color=0 |
---|
597 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
598 | titles.append(title) |
---|
599 | #p.set_axes('title',title) |
---|
600 | p.legend() |
---|
601 | ymin=postcal[i][edge:nchan-edge].min() |
---|
602 | ymax=postcal[i][edge:nchan-edge].max() |
---|
603 | p.plot(postcal[i]) |
---|
604 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
605 | if not btics[2*i+1]: |
---|
606 | p.axes.set_xticks([]) |
---|
607 | for i in range(2*nr): |
---|
608 | p.subplot(i) |
---|
609 | p.set_axes('title',titles[i],fontsize='medium') |
---|
610 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
611 | if x.upper() == 'N': |
---|
612 | p.quit() |
---|
613 | del p |
---|
614 | return scabtab |
---|
615 | p.quit() |
---|
616 | del p |
---|
617 | ### |
---|
618 | resspec._add_history("calnod",varlist) |
---|
619 | return resspec |
---|
620 | |
---|
621 | @asaplog_post_dec |
---|
622 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
---|
623 | """ |
---|
624 | Calibrate GBT frequency switched data. |
---|
625 | Adopted from GBTIDL getfs. |
---|
626 | Currently calfs identify the scans as frequency switched data if source |
---|
627 | type enum is fson and fsoff. The data must contains 'CAL' signal |
---|
628 | on/off in each integration. To identify 'CAL' on state, the source type |
---|
629 | enum of foncal and foffcal need to be present in the source name field. |
---|
630 | (GBT MS data reading via scantable automatically append these |
---|
631 | id names to the source names) |
---|
632 | |
---|
633 | Parameters: |
---|
634 | scantab: scantable |
---|
635 | scannos: list of scan numbers |
---|
636 | smooth: optional box smoothing order for the reference |
---|
637 | (default is 1 = no smoothing) |
---|
638 | tsysval: optional user specified Tsys (default is 0.0, |
---|
639 | use Tsys in the data) |
---|
640 | tauval: optional user specified Tau |
---|
641 | verify: Verify calibration if true |
---|
642 | """ |
---|
643 | varlist = vars() |
---|
644 | from asap._asap import stmath |
---|
645 | from asap._asap import srctype |
---|
646 | stm = stmath() |
---|
647 | stm._setinsitu(False) |
---|
648 | |
---|
649 | # check = scantab.get_scan('*_fs*') |
---|
650 | # if check is None: |
---|
651 | # msg = "The input data appear to contain no Nod observing mode data." |
---|
652 | # raise TypeError(msg) |
---|
653 | s = scantab.get_scan(scannos) |
---|
654 | del scantab |
---|
655 | |
---|
656 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval)) |
---|
657 | ### |
---|
658 | if verify: |
---|
659 | # get data |
---|
660 | ssub = s.get_scan(scannos) |
---|
661 | #ssubon = ssub.get_scan('*calon') |
---|
662 | #ssuboff = ssub.get_scan('*[^calon]') |
---|
663 | sel = selector() |
---|
664 | sel.set_types( [srctype.foncal,srctype.foffcal] ) |
---|
665 | ssub.set_selection( sel ) |
---|
666 | ssubon = ssub.copy() |
---|
667 | ssub.set_selection() |
---|
668 | sel.reset() |
---|
669 | sel.set_types( [srctype.fson,srctype.fsoff] ) |
---|
670 | ssub.set_selection( sel ) |
---|
671 | ssuboff = ssub.copy() |
---|
672 | ssub.set_selection() |
---|
673 | sel.reset() |
---|
674 | import numpy |
---|
675 | precal={} |
---|
676 | postcal=[] |
---|
677 | keys=['fs','fs_calon','fsr','fsr_calon'] |
---|
678 | types=[srctype.fson,srctype.foncal,srctype.fsoff,srctype.foffcal] |
---|
679 | ifnos=list(ssub.getifnos()) |
---|
680 | polnos=list(ssub.getpolnos()) |
---|
681 | for i in range(2): |
---|
682 | #ss=ssuboff.get_scan('*'+keys[2*i]) |
---|
683 | ll=[] |
---|
684 | for j in range(len(ifnos)): |
---|
685 | for k in range(len(polnos)): |
---|
686 | sel.set_ifs(ifnos[j]) |
---|
687 | sel.set_polarizations(polnos[k]) |
---|
688 | sel.set_types(types[2*i]) |
---|
689 | try: |
---|
690 | #ss.set_selection(sel) |
---|
691 | ssuboff.set_selection(sel) |
---|
692 | except: |
---|
693 | continue |
---|
694 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
695 | sel.reset() |
---|
696 | #ss.set_selection() |
---|
697 | ssuboff.set_selection() |
---|
698 | precal[keys[2*i]]=ll |
---|
699 | #del ss |
---|
700 | #ss=ssubon.get_scan('*'+keys[2*i+1]) |
---|
701 | ll=[] |
---|
702 | for j in range(len(ifnos)): |
---|
703 | for k in range(len(polnos)): |
---|
704 | sel.set_ifs(ifnos[j]) |
---|
705 | sel.set_polarizations(polnos[k]) |
---|
706 | sel.set_types(types[2*i+1]) |
---|
707 | try: |
---|
708 | #ss.set_selection(sel) |
---|
709 | ssubon.set_selection(sel) |
---|
710 | except: |
---|
711 | continue |
---|
712 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
713 | sel.reset() |
---|
714 | #ss.set_selection() |
---|
715 | ssubon.set_selection() |
---|
716 | precal[keys[2*i+1]]=ll |
---|
717 | #del ss |
---|
718 | #sig=resspec.get_scan('*_fs') |
---|
719 | #ref=resspec.get_scan('*_fsr') |
---|
720 | sel.set_types( srctype.fson ) |
---|
721 | resspec.set_selection( sel ) |
---|
722 | sig=resspec.copy() |
---|
723 | resspec.set_selection() |
---|
724 | sel.reset() |
---|
725 | sel.set_type( srctype.fsoff ) |
---|
726 | resspec.set_selection( sel ) |
---|
727 | ref=resspec.copy() |
---|
728 | resspec.set_selection() |
---|
729 | sel.reset() |
---|
730 | for k in range(len(polnos)): |
---|
731 | for j in range(len(ifnos)): |
---|
732 | sel.set_ifs(ifnos[j]) |
---|
733 | sel.set_polarizations(polnos[k]) |
---|
734 | try: |
---|
735 | sig.set_selection(sel) |
---|
736 | postcal.append(numpy.array(sig._getspectrum(0))) |
---|
737 | except: |
---|
738 | ref.set_selection(sel) |
---|
739 | postcal.append(numpy.array(ref._getspectrum(0))) |
---|
740 | sel.reset() |
---|
741 | resspec.set_selection() |
---|
742 | del sel |
---|
743 | # plot |
---|
744 | asaplog.post() |
---|
745 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
746 | asaplog.post('WARN') |
---|
747 | #p=asaplotgui.asaplotgui() |
---|
748 | p=new_asaplot() |
---|
749 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
750 | nr=len(ifnos)/2*len(polnos) |
---|
751 | titles=[] |
---|
752 | btics=[] |
---|
753 | if nr>3: |
---|
754 | asaplog.post() |
---|
755 | asaplog.push('Only first 3 [if,pol] pairs are plotted.') |
---|
756 | asaplog.post('WARN') |
---|
757 | nr=3 |
---|
758 | p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False) |
---|
759 | for i in range(3*nr): |
---|
760 | b=False |
---|
761 | if i >= 3*nr-3: |
---|
762 | b=True |
---|
763 | btics.append(b) |
---|
764 | for i in range(nr): |
---|
765 | p.subplot(3*i) |
---|
766 | p.color=0 |
---|
767 | title='raw data IF%s,%s POL%s' % (ifnos[2*int(i/len(polnos))],ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)]) |
---|
768 | titles.append(title) |
---|
769 | #p.set_axes('title',title,fontsize=40) |
---|
770 | ymin=1.0e100 |
---|
771 | ymax=-1.0e100 |
---|
772 | nchan=s.nchan() |
---|
773 | edge=int(nchan*0.01) |
---|
774 | for j in range(4): |
---|
775 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
776 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
777 | ymin=min(ymin,spmin) |
---|
778 | ymax=max(ymax,spmax) |
---|
779 | for j in range(4): |
---|
780 | if i==0: |
---|
781 | p.set_line(label=keys[j]) |
---|
782 | else: |
---|
783 | p.legend() |
---|
784 | p.plot(precal[keys[j]][i]) |
---|
785 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
786 | if not btics[3*i]: |
---|
787 | p.axes.set_xticks([]) |
---|
788 | p.subplot(3*i+1) |
---|
789 | p.color=0 |
---|
790 | title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
791 | titles.append(title) |
---|
792 | #p.set_axes('title',title) |
---|
793 | p.legend() |
---|
794 | ymin=postcal[2*i][edge:nchan-edge].min() |
---|
795 | ymax=postcal[2*i][edge:nchan-edge].max() |
---|
796 | p.plot(postcal[2*i]) |
---|
797 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
798 | if not btics[3*i+1]: |
---|
799 | p.axes.set_xticks([]) |
---|
800 | p.subplot(3*i+2) |
---|
801 | p.color=0 |
---|
802 | title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)]) |
---|
803 | titles.append(title) |
---|
804 | #p.set_axes('title',title) |
---|
805 | p.legend() |
---|
806 | ymin=postcal[2*i+1][edge:nchan-edge].min() |
---|
807 | ymax=postcal[2*i+1][edge:nchan-edge].max() |
---|
808 | p.plot(postcal[2*i+1]) |
---|
809 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
810 | if not btics[3*i+2]: |
---|
811 | p.axes.set_xticks([]) |
---|
812 | for i in range(3*nr): |
---|
813 | p.subplot(i) |
---|
814 | p.set_axes('title',titles[i],fontsize='medium') |
---|
815 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
816 | if x.upper() == 'N': |
---|
817 | p.quit() |
---|
818 | del p |
---|
819 | return scabtab |
---|
820 | p.quit() |
---|
821 | del p |
---|
822 | ### |
---|
823 | resspec._add_history("calfs",varlist) |
---|
824 | return resspec |
---|
825 | |
---|
826 | @asaplog_post_dec |
---|
827 | def merge(*args): |
---|
828 | """ |
---|
829 | Merge a list of scanatables, or comma-sperated scantables into one |
---|
830 | scnatble. |
---|
831 | Parameters: |
---|
832 | A list [scan1, scan2] or scan1, scan2. |
---|
833 | Example: |
---|
834 | myscans = [scan1, scan2] |
---|
835 | allscans = merge(myscans) |
---|
836 | # or equivalent |
---|
837 | sameallscans = merge(scan1, scan2) |
---|
838 | """ |
---|
839 | varlist = vars() |
---|
840 | if isinstance(args[0],list): |
---|
841 | lst = tuple(args[0]) |
---|
842 | elif isinstance(args[0],tuple): |
---|
843 | lst = args[0] |
---|
844 | else: |
---|
845 | lst = tuple(args) |
---|
846 | varlist["args"] = "%d scantables" % len(lst) |
---|
847 | # need special formatting her for history... |
---|
848 | from asap._asap import stmath |
---|
849 | stm = stmath() |
---|
850 | for s in lst: |
---|
851 | if not isinstance(s,scantable): |
---|
852 | msg = "Please give a list of scantables" |
---|
853 | raise TypeError(msg) |
---|
854 | s = scantable(stm._merge(lst)) |
---|
855 | s._add_history("merge", varlist) |
---|
856 | return s |
---|
857 | |
---|
858 | @asaplog_post_dec |
---|
859 | def calibrate( scantab, scannos=[], calmode='none', verify=None ): |
---|
860 | """ |
---|
861 | Calibrate data. |
---|
862 | |
---|
863 | Parameters: |
---|
864 | scantab: scantable |
---|
865 | scannos: list of scan number |
---|
866 | calmode: calibration mode |
---|
867 | verify: verify calibration |
---|
868 | """ |
---|
869 | import re |
---|
870 | antname = scantab.get_antennaname() |
---|
871 | if ( calmode == 'nod' ): |
---|
872 | asaplog.push( 'Calibrating nod data.' ) |
---|
873 | scal = calnod( scantab, scannos=scannos, verify=verify ) |
---|
874 | elif ( calmode == 'quotient' ): |
---|
875 | asaplog.push( 'Calibrating using quotient.' ) |
---|
876 | scal = scantab.auto_quotient( verify=verify ) |
---|
877 | elif ( calmode == 'ps' ): |
---|
878 | asaplog.push( 'Calibrating %s position-switched data.' % antname ) |
---|
879 | if ( antname.find( 'APEX' ) != -1 ): |
---|
880 | scal = apexcal( scantab, scannos, calmode, verify ) |
---|
881 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 |
---|
882 | or re.match('DV[0-9][0-9]$',antname) is not None |
---|
883 | or re.match('PM[0-9][0-9]$',antname) is not None |
---|
884 | or re.match('CM[0-9][0-9]$',antname) is not None |
---|
885 | or re.match('DA[0-9][0-9]$',antname) is not None ): |
---|
886 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
887 | else: |
---|
888 | scal = calps( scantab, scannos=scannos, verify=verify ) |
---|
889 | elif ( calmode == 'fs' or calmode == 'fsotf' ): |
---|
890 | asaplog.push( 'Calibrating %s frequency-switched data.' % antname ) |
---|
891 | if ( antname.find( 'APEX' ) != -1 ): |
---|
892 | scal = apexcal( scantab, scannos, calmode, verify ) |
---|
893 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ): |
---|
894 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
895 | else: |
---|
896 | scal = calfs( scantab, scannos=scannos, verify=verify ) |
---|
897 | elif ( calmode == 'otf' ): |
---|
898 | asaplog.push( 'Calibrating %s On-The-Fly data.' % antname ) |
---|
899 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
900 | else: |
---|
901 | asaplog.push( 'No calibration.' ) |
---|
902 | scal = scantab.copy() |
---|
903 | |
---|
904 | return scal |
---|
905 | |
---|
906 | def apexcal( scantab, scannos=[], calmode='none', verify=False ): |
---|
907 | """ |
---|
908 | Calibrate APEX data |
---|
909 | |
---|
910 | Parameters: |
---|
911 | scantab: scantable |
---|
912 | scannos: list of scan number |
---|
913 | calmode: calibration mode |
---|
914 | |
---|
915 | verify: verify calibration |
---|
916 | """ |
---|
917 | from asap._asap import stmath |
---|
918 | stm = stmath() |
---|
919 | antname = scantab.get_antennaname() |
---|
920 | ssub = scantab.get_scan( scannos ) |
---|
921 | scal = scantable( stm.cwcal( ssub, calmode, antname ) ) |
---|
922 | return scal |
---|
923 | |
---|
924 | def almacal( scantab, scannos=[], calmode='none', verify=False ): |
---|
925 | """ |
---|
926 | Calibrate ALMA data |
---|
927 | |
---|
928 | Parameters: |
---|
929 | scantab: scantable |
---|
930 | scannos: list of scan number |
---|
931 | calmode: calibration mode |
---|
932 | |
---|
933 | verify: verify calibration |
---|
934 | """ |
---|
935 | from asap._asap import stmath |
---|
936 | stm = stmath() |
---|
937 | ssub = scantab.get_scan( scannos ) |
---|
938 | scal = scantable( stm.almacal( ssub, calmode ) ) |
---|
939 | return scal |
---|
940 | |
---|
941 | @asaplog_post_dec |
---|
942 | def splitant(filename, outprefix='',overwrite=False): |
---|
943 | """ |
---|
944 | Split Measurement set by antenna name, save data as a scantables, |
---|
945 | and return a list of filename. |
---|
946 | Notice this method can only be available from CASA. |
---|
947 | Prameter |
---|
948 | filename: the name of Measurement set to be read. |
---|
949 | outprefix: the prefix of output scantable name. |
---|
950 | the names of output scantable will be |
---|
951 | outprefix.antenna1, outprefix.antenna2, .... |
---|
952 | If not specified, outprefix = filename is assumed. |
---|
953 | overwrite If the file should be overwritten if it exists. |
---|
954 | The default False is to return with warning |
---|
955 | without writing the output. USE WITH CARE. |
---|
956 | |
---|
957 | """ |
---|
958 | # Import the table toolkit from CASA |
---|
959 | import casac |
---|
960 | from asap.scantable import is_ms |
---|
961 | tbtool = casac.homefinder.find_home_by_name('tableHome') |
---|
962 | tb = tbtool.create() |
---|
963 | # Check the input filename |
---|
964 | if isinstance(filename, str): |
---|
965 | import os.path |
---|
966 | filename = os.path.expandvars(filename) |
---|
967 | filename = os.path.expanduser(filename) |
---|
968 | if not os.path.exists(filename): |
---|
969 | s = "File '%s' not found." % (filename) |
---|
970 | raise IOError(s) |
---|
971 | # check if input file is MS |
---|
972 | #if not os.path.isdir(filename) \ |
---|
973 | # or not os.path.exists(filename+'/ANTENNA') \ |
---|
974 | # or not os.path.exists(filename+'/table.f1'): |
---|
975 | if not is_ms(filename): |
---|
976 | s = "File '%s' is not a Measurement set." % (filename) |
---|
977 | raise IOError(s) |
---|
978 | else: |
---|
979 | s = "The filename should be string. " |
---|
980 | raise TypeError(s) |
---|
981 | # Check out put file name |
---|
982 | outname='' |
---|
983 | if len(outprefix) > 0: prefix=outprefix+'.' |
---|
984 | else: |
---|
985 | prefix=filename.rstrip('/') |
---|
986 | # Now do the actual splitting. |
---|
987 | outfiles=[] |
---|
988 | tb.open(tablename=filename,nomodify=True) |
---|
989 | ant1=tb.getcol('ANTENNA1',0,-1,1) |
---|
990 | anttab=tb.getkeyword('ANTENNA').split()[-1] |
---|
991 | tb.close() |
---|
992 | #tb.open(tablename=filename+'/ANTENNA',nomodify=True) |
---|
993 | tb.open(tablename=anttab,nomodify=True) |
---|
994 | nant=tb.nrows() |
---|
995 | antnames=tb.getcol('NAME',0,nant,1) |
---|
996 | tb.close() |
---|
997 | tmpname='asapmath.splitant.tmp' |
---|
998 | for antid in set(ant1): |
---|
999 | tb.open(tablename=filename,nomodify=True) |
---|
1000 | tbsel=tb.query('ANTENNA1 == %s && ANTENNA2 == %s'%(antid,antid),tmpname) |
---|
1001 | scan=scantable(tmpname,average=False,getpt=True,antenna=int(antid)) |
---|
1002 | outname=prefix+antnames[antid]+'.asap' |
---|
1003 | scan.save(outname,format='ASAP',overwrite=overwrite) |
---|
1004 | tbsel.close() |
---|
1005 | tb.close() |
---|
1006 | del tbsel |
---|
1007 | del scan |
---|
1008 | outfiles.append(outname) |
---|
1009 | os.system('rm -rf '+tmpname) |
---|
1010 | del tb |
---|
1011 | return outfiles |
---|
1012 | |
---|
1013 | @asaplog_post_dec |
---|
1014 | def _array2dOp( scan, value, mode="ADD", tsys=False ): |
---|
1015 | """ |
---|
1016 | This function is workaround on the basic operation of scantable |
---|
1017 | with 2 dimensional float list. |
---|
1018 | |
---|
1019 | scan: scantable operand |
---|
1020 | value: float list operand |
---|
1021 | mode: operation mode (ADD, SUB, MUL, DIV) |
---|
1022 | tsys: if True, operate tsys as well |
---|
1023 | """ |
---|
1024 | nrow = scan.nrow() |
---|
1025 | s = None |
---|
1026 | if len( value ) == 1: |
---|
1027 | from asap._asap import stmath |
---|
1028 | stm = stmath() |
---|
1029 | s = scantable( stm._arrayop( scan.copy(), value[0], mode, tsys ) ) |
---|
1030 | del stm |
---|
1031 | elif len( value ) != nrow: |
---|
1032 | raise ValueError( 'len(value) must be 1 or conform to scan.nrow()' ) |
---|
1033 | else: |
---|
1034 | from asap._asap import stmath |
---|
1035 | stm = stmath() |
---|
1036 | # insitu must be True |
---|
1037 | stm._setinsitu( True ) |
---|
1038 | s = scan.copy() |
---|
1039 | sel = selector() |
---|
1040 | for irow in range( nrow ): |
---|
1041 | sel.set_rows( irow ) |
---|
1042 | s.set_selection( sel ) |
---|
1043 | if len( value[irow] ) == 1: |
---|
1044 | stm._unaryop( s, value[irow][0], mode, tsys ) |
---|
1045 | else: |
---|
1046 | #stm._arrayop( s, value[irow], mode, tsys, 'channel' ) |
---|
1047 | stm._arrayop( s, value[irow], mode, tsys ) |
---|
1048 | s.set_selection() |
---|
1049 | sel.reset() |
---|
1050 | del sel |
---|
1051 | del stm |
---|
1052 | return s |
---|