Coverage for /wheeldirectory/casa-6.7.0-12-py3.10.el8/lib/py/lib/python3.10/site-packages/casatasks/flagdata.py: 56%

1##################### generated by xml-casa (v2) from flagdata.xml ################## 

2##################### 4f26e57fc00d2ca604825e5f4b7fac4a ############################## 

3from __future__ import absolute_import 

4import numpy 

5from casatools.typecheck import CasaValidator as _val_ctor 

6_pc = _val_ctor( ) 

7from casatools.coercetype import coerce as _coerce 

8from casatools.errors import create_error_string 

9from .private.task_flagdata import flagdata as _flagdata_t 

10from casatasks.private.task_logging import start_log as _start_log 

11from casatasks.private.task_logging import end_log as _end_log 

12from casatasks.private.task_logging import except_log as _except_log 

13 

14class _flagdata: 

15 """ 

16 flagdata ---- All-purpose flagging task based on data-selections and flagging modes/algorithms. 

17 

18  

19 This task can flag a Measurement Set or a calibration table. It has 

20 two main types of operation. One type will read the parameters from 

21 the interface and flag using any of the various available modes. The 

22 other type will read the commands from a text file, a list of files or 

23 a Python list of strings, containing a list of flag commands. 

24  

25 It is also possible to only save the parameters set in the interface 

26 without flagging. The parameters can be saved in the FLAG_CMD 

27 sub-table or in a text file. Note that when saving to an external 

28 file, the parameters will be appended to the given file. 

29  

30 The current flags can be automatically backed up before applying new 

31 flags if the parameter flagbackup is set. Previous flag versions can 

32 be recovered using the flagmanager task. 

33  

34 Flagdata can also flag many types of calibration tables. For detailed 

35 information, see the task pages of flagdata in CASA Docs 

36 (https://casa.nrao.edu/casadocs/) 

37 

38 --------- parameter descriptions --------------------------------------------- 

39 

40 vis Name of input visibility file 

41 Default: none 

42  

43 Example: vis='ngc5921.ms' 

44 mode Flagging mode 

45 Default: 'manual' 

46 Options: 'list', 'manual', 'clip', 'quack', 

47 'shadow', 'elevation', 'tfcrop', 'rflag', 

48 'antint', 'extend', 'unflag', 'summary' 

49  

50  

51 \* 'list': Flag according to the data selection 

52 and flag commands specified in the input 

53 list. The input list may come from a text file, 

54 a list of text files or from a Python list of 

55 strings. Each input line may contain data 

56 selection parameters and any parameter 

57 specific to the mode given in the line. Default 

58 values will be used for the parameters that are 

59 not present in the line. Each line will be 

60 taken as a command to the task. If data is 

61 pre-selected using any of the selection 

62 parameters, then flagging will apply only to 

63 that subset of the MS. 

64  

65 For optimization and whenever possible, the 

66 task will create a union of the data selection 

67 parameters present in the list and select only 

68 that portion of the MS. 

69  

70 NOTE1: the flag commands will be applied only 

71 when action='apply'. If action='calculate' the 

72 flags will be calculated, but not applied. This 

73 is useful if display is set to something other 

74 than 'none'. If action='' or 'none', the flag 

75 commands will not be applied either. An empty 

76 action is useful only to save the parameters of 

77 the list to a file or to the FLAG_CMD 

78 sub-table. 

79  

80 NOTE2: In list mode the parameter 

81 quackincrement=True is not supported as part of 

82 any quack flag command, unless it is the first 

83 command of the list. See more about this in the 

84 quack mode section of this help. 

85  

86  

87 \* 'manual': Flag according to the data selection 

88 specified. This is the default mode  

89  

90  

91 \* 'clip': Clip data according to values of the 

92 following subparameters. The polarization 

93 expression is given by the correlation 

94 parameter. For calibration tables, the 

95 solutions are also given by the correlation 

96 parameter. 

97  

98  

99 \* 'quack': Option to remove specified part of 

100 scan beginning/end. 

101  

102  

103 \* 'shadow': Option to flag data of shadowed 

104 antennas. This mode is not available for cal 

105 tables. 

106  

107 All antennas in the antenna-subtable of the MS 

108 (and the corresponding diameters) will be 

109 considered for shadow-flag calculations. For a 

110 given timestep, an antenna is flagged if any of 

111 its baselines (projected onto the uv-plane) is 

112 shorter than radius_1 + radius_2 - 

113 tolerance. The value of 'w' is used to 

114 determine which antenna is behind the 

115 other. The phase-reference center is used for 

116 antenna-pointing direction.  

117  

118  

119 \* 'elevation': Option to flag based on antenna 

120 elevation. This mode is not available for cal 

121 tables. 

122  

123  

124 \* 'tfcrop': Flag using the TFCrop autoflag 

125 algorithm. 

126  

127 For each field, spw, timerange (specified by 

128 ntime), and baseline,  

129 (1) Average visibility amplitudes along time 

130 dimension to form an average spectrum 

131 (2) Calculate a robust piece-wise polynomial 

132 fit for the band-shape at the base of RFI 

133 spikes. Calculate 'stddev' of (data - fit). 

134 (3) Flag points deviating from the fit by more 

135 than N-stddev 

136 (4) Repeat (1-3) along the other dimension. 

137  

138 This algorithm is designed to operate on 

139 un-calibrated data (step (2)), as well as 

140 calibrated data. It is recommended to extend 

141 the flags after running this algorithm. See the 

142 sub-parameter extendflags below. 

143  

144  

145 \* 'rflag': Detect outliers based on the RFlag 

146 algorithm (ref. E.Greisen, AIPS, 2011). The 

147 polarization expression is given by the 

148 correlation parameter. 

149  

150 Iterate through the data in chunks of time. 

151 For each chunk, calculate local statistics, and 

152 apply flags based on user supplied (or 

153 auto-calculated) thresholds. 

154  

155 Step 1 : Time analysis (for each channel) 

156 -- calculate local rms of real and imag 

157 visibilities, within a sliding time window 

158 -- calculate the median rms across time 

159 windows, deviations of local rms from this 

160 median, and the median deviation  

161 -- flag if local rms is larger than 

162 timedevscale x (medianRMS + medianDev) 

163  

164 Step 2 : Spectral analysis (for each time) 

165 -- calculate avg of real and imag 

166 visibilities and their rms across channels 

167 -- calculate the deviation of each channel 

168 from this avg, and the median-deviation 

169 -- flag if deviation is larger than 

170 freqdevscale x medianDev 

171  

172 It is recommended to extend the flags after 

173 running this algorithm. See the sub-parameter 

174 extendflags below. 

175  

176 Note that by default the flag implementation in 

177 CASA is able to calculate the thresholds and 

178 apply them on-the-fly (OTF). There is a 

179 significant performancegain with this approach, 

180 as the visibilities don't have to be read 

181 twice,and therefore is highly 

182 recommended. Otherwise it is possible 

183 toreproduce the AIPS usage pattern by doing a 

184 first run with 'calculate' mode and a second 

185 run with 'apply' mode. The advantage of this 

186 approach is that the thresholdsare calculated 

187 using the data from all scans, instead of 

188 calculating them for one scan only. 

189  

190 For more information and examples of 'rflag', 

191 see the task pages of rflag in CASA Docs 

192 (https://casa.nrao.edu/casadocs/) 

193  

194  

195 \* 'antint': Flag integrations if all baselines to 

196 a specified antenna are flagged 

197  

198 This mode flag all integrations in which a 

199 specified antenna is flagged. This mode 

200 operates for an spectral window. It flags any 

201 integration in which all baselines to a 

202 specified antenna are flagged, but only if this 

203 condition is satisfied in a fraction of 

204 channels within the spectral window of interest 

205 greater than a nominated fraction. For 

206 simplicity, it assumes that all polarization 

207 products must be unflagged for a baseline to be 

208 deemed unflagged. The antint mode implements 

209 the flagging approach introduced in 

210 'antintflag' 

211 (https://doi.org/10.5281/zenodo.163546) 

212  

213 The motivating application for introducing this 

214 mode is removal of data that will otherwise 

215 lead to changes in reference antenna during 

216 gain calibration, which will in turn lead to 

217 corrupted polarization. 

218  

219  

220 \* 'extend': Extend and/or grow flags beyond what 

221 the basic algorithms detect. This mode will 

222 extend the accumulated flags available in the 

223 MS, regardless of which algorithm created them. 

224  

225 It is recommended that any autoflag (tfcrop, 

226 rflag) algorithm be followed up by a flag 

227 extension. 

228  

229 Extensions will apply only within the selected 

230 data, according to the settings of 

231 extendpols,growtime,growfreq,growaround, 

232 flagneartime,flagnearfreq. 

233  

234 Note : Runtime summary counts in the logger can 

235 sometimes report larger flag percentages than 

236 what is actually flagged. This is because 

237 extensions onto already-flagged data-points are 

238 counted as new flags. An accurate flag count 

239 can be obtained via the summary mode. 

240  

241  

242 \* 'unflag': Unflag according to the data 

243 selection specified. 

244  

245  

246 \* 'summary': List the number of rows and flagged 

247 data points for the MS's meta-data. The 

248 resulting summary will be returned as a Python 

249 dictionary. 

250 autocorr Flag only the auto-correlations? 

251 Subparameter of mode='manual' 

252 Default: False 

253 Options: False|True 

254  

255 NOTE: this parameter is only active when set to 

256 True. If set to False it does NOT mean "do not 

257 flag auto-correlations". When set to True, it 

258 will only flag data from a processor of type 

259 CORRELATOR. 

260 inpfile Input ASCII file, list of files or Python list of strings 

261 with flag commands. 

262 Subparameter of mode='list' 

263 Default: '' 

264 Options: [] with flag commands or  

265 [] with filenames or  

266 '' with a filename. 

267  

268 The parser will be strict and accept only valid 

269 flagdata parameters in the list. The parser 

270 evaluates the commands in the list and considers 

271 only existing Python types.It will check each 

272 parameter name and type and exit with an error if 

273 any of them is wrong.  

274  

275 NOTE: There should be no whitespace between 

276 KEY=VALUE since the parser first breaks command 

277 lines on whitespace, then on "=". Use only one 

278 whitespace to separate the parameters (no 

279 commas). 

280 reason Select flag commands based on REASON(s) 

281 Subparameter of mode='list' 

282 Default: 'any' (all flags regardless of reason) 

283 Can be a string, or list of strings 

284  

285 Examples:  

286 reason='FOCUS_ERROR' 

287 reason=['FOCUS_ERROR','SUBREFLECTOR_ERROR'] 

288  

289 If inpfile is a list of files, the reasons given 

290 in this parameter will apply to all the files. 

291  

292 NOTE: what is within the string is literally 

293 matched, e.g. reason='' matches only blank 

294 reasons, and reason = 

295 'FOCUS_ERROR,SUBREFLECTOR_ERROR' matches this 

296 compound reason string only. 

297 tbuff A time buffer or list of time buffers to pad the 

298 timerange parameters in flag commands. 

299 Subparameter of mode='list' 

300 Default: 0.0 (it will not apply any time padding) 

301  

302 When a list of 2 time buffers is given, it will 

303 subtract the first value from the lower time and 

304 the second value will be added to the upper time 

305 in the range. The 2 time buffer values can be 

306 different, allowing to have an irregular time 

307 buffer padding to time ranges. If the list 

308 contains only one time buffer, it will use it to 

309 subtract from t0 and add to t1. If more than one 

310 list of input files is given, tbuff will apply to 

311 all of the flag commands that have timerange 

312 parameters in the files. Each tbuff value should 

313 be a Float number given in seconds. 

314  

315 Examples: 

316 tbuff=[0.5, 0.8]  

317 inpfile=['online.txt','userflags.txt'] 

318  

319 The timeranges in the online.txt file are 

320 first converted to seconds. Then, 0.5 is 

321 subtracted from t0 and 0.8 is added to t1, 

322 where t0 and t1 are the two intervals given in 

323 timerange. Similarly, tbuff will be applied to 

324 any timerange in userflags.txt.  

325  

326 IMPORTANT: This parameter assumes that timerange 

327 = t0 ~ t1, therefore it will not work if only t0 

328 or t1 is given. 

329  

330 NOTE: The most common use-case for tbuff is to 

331 apply the online flags that are created by 

332 importasdm when savecmds=True. The value of a 

333 regular time buffer should be 

334 tbuff=0.5\*max(integration time). 

335 spw Select spectral window/channels 

336 Default: '' (all spectral windows and channels) 

337  

338 Examples: 

339 spw='0~2,4'; spectral windows 0,1,2,4 (all channels) 

340 spw='<2'; spectral windows less than 2 (i.e. 0,1) 

341 spw='0:5~61'; spw 0, channels 5 to 61 

342 spw='0,10,3:3~45'; spw 0,10 all channels, spw 

343 3 - chans 3 to 45. 

344 spw='0~2:2~6'; spw 0,1,2 with channels 2 

345 through 6 in each. 

346 spw = '\*:3~64' channels 3 through 64 for all sp id's 

347 spw = ' :3~64' will NOT work. 

348  

349 NOTE: For modes clip, tfcrop and rflag, 

350 channel-ranges can be excluded from flagging by 

351 leaving them out of the selection range. This is 

352 a way to protect known spectral-lines from being 

353 flagged by the autoflag algorithms. For example, 

354 if spectral-lines fall in channels 6~9, set the 

355 selection range to spw='0:0~5;10~63'. 

356 field Select field using field id(s) or field name(s) 

357 Default: '' (all fields) 

358  

359 Use 'go listobs' to obtain the list id's or 

360 names. If field string is a non-negative integer, 

361 it is assumed a field index, otherwise, it is 

362 assumed a field name. 

363  

364 Examples: 

365 field='0~2'; field ids 0,1,2 

366 field='0,4,5~7'; field ids 0,4,5,6,7 

367 field='3C286,3C295'; field named 3C286 and 

368 3C295 

369 field = '3,4C\*'; field id 3, all names 

370 starting with 4C 

371 antenna Select data based on antenna/baseline 

372 Subparameter of selectdata=True 

373 Default: '' (all) 

374  

375 If antenna string is a non-negative integer, it 

376 is assumed an antenna index, otherwise, it is 

377 assumed as an antenna name 

378  

379 Examples:  

380 antenna='5&6'; baseline between antenna 

381 index 5 and index 6. 

382 antenna='VA05&VA06'; baseline between VLA 

383 antenna 5 and 6. 

384 antenna='5&6;7&8'; baselines with 

385 indices 5-6 and 7-8 

386 antenna='5'; all baselines with antenna index 

387 5 

388 antenna='05'; all baselines with antenna 

389 number 05 (VLA old name) 

390 antenna='5,6,10'; all baselines with antennas 

391 5,6,10 index numbers 

392  

393 NOTE: for some antenna-based calibration tables, 

394 selecting baselines with the & syntax do not 

395 apply. 

396 uvrange Select data by baseline length. 

397 Default = '' (all) 

398  

399 Examples: 

400 uvrange='0~1000klambda'; uvrange from 0-1000 kilo-lambda 

401 uvrange='>4klambda';uvranges greater than 4 kilo-lambda 

402 uvrange='0~1000km'; uvrange in kilometers 

403  

404 NOTE: uvrange selection is not supported for cal tables. 

405 timerange Select data based on time range 

406 Subparameter of selectdata=True 

407 Default = '' (all) 

408  

409 Examples: 

410 timerange = 

411 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' 

412 (Note: if YYYY/MM/DD is missing date defaults 

413 to first day in data set.) 

414 timerange='09:14:0~09:54:0' picks 40 min on 

415 first day  

416 timerange= '25:00:00~27:30:00' picks 1 hr to 3 

417 hr 30min on NEXT day 

418 timerange='09:44:00' pick data within one 

419 integration of time 

420 timerange='>10:24:00' data after this time 

421 correlation Select data based on correlation 

422 Default: '' ==> all 

423 Options: Any of 'ABS', 'ARG', 'REAL', 'IMAG', 

424 'NORM' followed by any of 'ALL', 'I', 'XX', 'YY', 

425 'RR', 'LL', 'WVR' ('WVR' = water vapour 

426 radiometer of ALMA data). 

427  

428 Example: correlation="XX,YY". 

429  

430 For modes clip, tfcrop or rflag, the default 

431 means ABS_ALL. 

432 If the input is cal table that does not contain 

433 a complex data column, the default will fall back 

434 to REAL_ALL. 

435 For calibration tables, the solutions are: 

436 'Sol1', 'Sol2', Sol3, Sol4. 

437 When using the 'ARG' option, the values of 

438 parameters such as clipminmax are expeced in 

439 units of radians. 

440  

441 NOTE: correlation selection is not supported for 

442 modes other than clip, tfcrop or rflag in cal 

443 tables. 

444 scan Scan number range 

445 Subparameter of selectdata=True 

446 Default: '' = all 

447 intent Select observing intent 

448 Default: '' (no selection by intent) 

449  

450 Example: intent='\*BANDPASS\*' (selects data 

451 labelled with BANDPASS intent) 

452  

453 NOTE: intent selection is not supported for cal 

454 tables. 

455 array Selection based on the antenna array 

456 Default: '' (all) 

457  

458 NOTE: array selection is not supported for cal 

459 tables. 

460 observation Select by observation ID(s) 

461 Subparameter of selectdata=True 

462 Default: '' = all 

463  

464 Example: observation='0~2,4' 

465 feed Selection based on the feed: Not yet implemented 

466 clipminmax Range to use for clipping 

467 Subparameter of mode='clip' 

468 Default: [] (it will flag only NaN and Infs) 

469  

470 It will always flag the NaN/Inf data, even when a range is specified.  

471  

472 Example: [0.0,1.5] 

473 datacolumn Data column to image (data or observed, corrected) 

474 Subparameter of mode='clip|tfcrop|rflag' 

475 Default:'corrected' 

476 Options: data, corrected, model, weight, etc. 

477  

478 If 'corrected' does not exist, it will use 'data' 

479 instead 

480 clipoutside Clip outside the range? 

481 Subparameter of mode='clip' 

482 Default: True 

483 Options: True|False 

484 channelavg Pre-average data across channels before analyzing 

485 visibilities for flagging 

486 Subparameter of mode='clip|tfcrop|rflag' 

487 Default: False 

488 Options: False|True 

489  

490 Pre-average data across channels before analyzing 

491 visibilities for flagging. Partially flagged data 

492 is not be included in the average unless all 

493 data contributing to a given output channel is 

494 flagged. If present, WEIGHT_SPECTRUM / 

495 SIGMA_SPECTRUM are used to compute a weighted 

496 average (WEIGHT_SPECTRUM for CORRECTED_DATA and 

497 SIGMA_SPECTRUM for DATA). 

498  

499 NOTE: Pre-average across channels is not 

500 supported for calibration tables 

501 chanbin Bin width for channel average in number of input channels 

502 Subparameter of mode='clip|tfcrop|rflag' 

503 Default: 1 

504  

505 Bin width for channel average in number of input 

506 channels. If a list is given, each bin applies to 

507 one of the selected SPWs. When chanbin is set to 

508 1 all input channels are used for the average 

509 to produce a single output channel, this 

510 behaviour aims to preserve backwards 

511 compatibility with the previous pre-averaging 

512 feature of clip mode. 

513 timeavg Pre-average data across time before analyzing 

514 visibilities for flagging. 

515 Subparameter of mode='clip|tfcrop|rflag' 

516 Default: False 

517 Options: False|True 

518  

519 Pre-average data across time before analyzing 

520 visibilities for flagging. Partially flagged data 

521 is not be included in the average unless all 

522 data contributing to a given output channel is 

523 flagged. If present, WEIGHT_SPECTRUM / 

524 SIGMA_SPECTRUM are used to compute a weighted 

525 average (WEIGHT_SPECTRUM for CORRECTED_DATA and 

526 SIGMA_SPECTRUM for DATA). Otherwise WEIGHT/SIGMA 

527 are used to average together data from different 

528 integrations. 

529  

530 NOTE: Pre-average across time is not 

531 supported for calibration tables 

532 timebin Bin width for time average in seconds 

533 Subparameter of mode='clip|tfcrop|rflag' 

534 Default: '0s' 

535 clipzeros Clip zero-value data 

536 Subparameter of mode='clip' 

537 Default: False 

538 Options: False|True 

539 quackinterval Time in seconds from scan beginning or end to flag. 

540 Subparameter of mode='quack' 

541 Default: 1.0 

542  

543 Note: Make time slightly smaller than the desired 

544 time. 

545 quackmode Quack mode flags the region of the scan given by one of the 

546 options below using the time set at quackinterval. 

547 Subparameter of mode='quack' 

548 Default: 'beg' 

549 Options:  

550 'beg' : flag an interval at the beginning of scan 

551 'endb': flag an interval at the end of scan 

552 'tail': flag all but an interval at the beginning of scan 

553 'end' : flag all but an interval at end of scan 

554  

555 Visual representation of quack mode flagging one 

556 scan with 1s duration. The following diagram 

557 shows what is flagged for each quack mode when 

558 quackinterval is set to 0.25s. The flagged part 

559 is represented by crosses (+++++++++) 

560  

561 scan with 1s duration 

562 -------------------------------------------- 

563 beg 

564 +++++++++++--------------------------------- 

565 endb 

566 ---------------------------------+++++++++++ 

567 tail 

568 -----------+++++++++++++++++++++++++++++++++ 

569 end 

570 +++++++++++++++++++++++++++++++++----------- 

571 quackincrement Increment quack flagging in time taking into account 

572 flagged data or not. 

573 Subparameter of mode='quack' 

574 Default: False 

575 Options: False|True 

576  

577 False: the quack interval is counted from the 

578 scan boundaries, as determined by the quackmode 

579 parameter, regardless of if data has been flagged 

580 or not. 

581 True: the quack interval is counted from the 

582 first unflagged data in the scan. 

583  

584 NOTE: on adding quack to a command in 'list' 

585 mode: quackincrement = True works based on the 

586 state of prior flagging, and unless it is the 

587 first item in the list the agent doing the 

588 quacking in list mode doesn't know about the 

589 state of prior flags. In this case, the command 

590 with quackincrement=True will be ignored and the 

591 task will issue a WARNING. 

592 tolerance Amount of shadowing allowed (or tolerated), in meters.  

593 Subparameter of mode='shadow' 

594 Default: 0.0 

595  

596 A positive number allows antennas to overlap in 

597 projection. A negative number forces antennas 

598 apart in projection. Zero implies a distance of 

599 radius_1+radius_2 between antenna centers. 

600 addantenna File name or dictionary with additional antenna names, 

601 positions and diameters 

602 Subparameter of mode='shadow' 

603 Default: '' 

604  

605 It can be either a file name with additional 

606 antenna names, positions and diameters, or a 

607 Python dictionary with the same information. You 

608 can use the flaghelper functions to create the 

609 dictionary from a file.  

610  

611 To create a dictionary inside casapy. 

612 > import flaghelper as fh 

613 > antdic = fh.readAntennaList(antfile) 

614  

615 Where antfile is a text file in disk that 

616 contains information such as: 

617 name=VLA01 

618 diameter=25.0 

619 position=[-1601144.96146691, -5041998.01971858, 

620 3554864.76811967] 

621 name=VLA02 

622 diameter=25.0 

623 position=[-1601105.7664601889, 

624 -5042022.3917835914, 3554847.245159178] 

625 lowerlimit Lower limiting elevation (in degrees) 

626 Subparameter of mode='elevation' 

627 Default: 0.0 

628  

629 Lower limiting elevation in degrees. Data coming 

630 from a baseline where one or both antennas were 

631 pointing at a strictly lower elevation (as 

632 function of time), will be flagged. 

633 upperlimit Upper limiting elevation (in degrees) 

634 Subparameter of mode='elevation' 

635 Default: 90.0 

636  

637 Upper limiting elevation in degrees. Data coming 

638 from a baseline where one or both antennas were 

639 pointing at a strictly higher elevation (as 

640 function of time), will be flagged. 

641 ntime Timerange (in seconds or minutes) over which to buffer 

642 data before running the algorithm.  

643 Subparameter of mode='tfcrop|rflag|extend' 

644 Default: 'scan' 

645 Options: 'scan' or any other float value or 

646 string containing the units. 

647  

648 The dataset will be iterated through in 

649 time-chunks defined here. 

650  

651 Example: ntime='1.5min'; 1.2 (taken in 

652 seconds) 

653  

654 WARNING: if ntime='scan' and combinescans=True, 

655 all the scans will be loaded at once, thus 

656 requesting a lot of memory depending on the 

657 available spws. 

658 combinescans Accumulate data across scans depending on the value of 

659 ntime. 

660 Subparameter of mode='tfcrop|rflag|extend' 

661 Default: False 

662 Options: False|True 

663  

664 This parameter should be set to True only when 

665 ntime is specified as a time-interval (not 

666 'scan'). When set to True, it will remove SCAN 

667 from the sorting columns, therefore it will only 

668 accumulate across scans if ntime is not set to 

669 'scan'. 

670 timecutoff Flagging thresholds in units of deviation from the fit 

671 Subparameter of mode='tfcrop' 

672 Default: 4.0 

673  

674 Flag all data-points further than N-stddev from 

675 the fit. This threshold catches time-varying RFI 

676 spikes (narrow and broad-band), but will not 

677 catch RFI that is persistent in time. 

678  

679 Flagging is done in upto 5 iterations. The stddev 

680 calculation is adaptive and converges to a value 

681 that reflects only the data and no RFI. At each 

682 iteration, the same relative threshold is applied 

683 to detect flags. (Step (3) of the algorithm). 

684 freqcutoff Flag threshold in frequency. 

685 Subparameter of mode='tfcrop' 

686 Default: 3.0 

687  

688 Flag all data-points further than N-stddev from 

689 the fit. Same as timecutoff, but along the 

690 frequency-dimension. This threshold catches 

691 narrow-band RFI that may or may not be persistent 

692 in time. 

693 timefit Fitting function for the time direction (poly/line) 

694 Subparameter of mode='tfcrop' 

695 Default: 'line' 

696 Options: line|poly 

697  

698 'line': fit is a robust straight-line fit across 

699 the entire timerange (defined by 'ntime'). 

700 'poly': fit is a robust piece-wise polynomial fit 

701 across the timerange. 

702  

703 NOTE: A robust fit is computed in upto 5 

704 iterations. At each iteration, the stddev between 

705 the data and the fit is computed, values beyond 

706 N-stddev are flagged, and the fit and stddev are 

707 re-calculated with the remaining points. This 

708 stddev calculation is adaptive, and converges to 

709 a value that reflects only the data and no RFI. 

710 It also provides a varying set of flagging 

711 thresholds, that allows deep flagging only when 

712 the fit best represents the true data. 

713  

714 Choose 'poly' only if the visibilities are 

715 expected to vary significantly over the timerange 

716 selected by 'ntime', or if there is a lot of 

717 strong but intermittent RFI. 

718 freqfit Fitting function for the frequency direction (poly/line) 

719 Subparameter of mode='tfcrop' 

720 Default: 'poly' 

721 Options: line|poly 

722  

723 Same as for the 'timefit' parameter. 

724  

725 Choose 'line' only if you are operating on 

726 bandpass-corrected data, or residuals,and expect 

727 that the bandshape is linear. The 'poly' option 

728 works better on uncalibrated bandpasses with 

729 narrow-band RFI spikes. 

730 maxnpieces Number of pieces in the polynomial-fits (for "freqfit" or 

731 "timefit" = "poly") 

732 Subparameter of mode='tfcrop' 

733 Default: 7 

734 Options: 1-9 

735  

736 This parameter is used only if 'timefit' or 

737 'freqfit' are chosen as 'poly'. If there is 

738 significant broad-band RFI, reduce this 

739 number. Using too many pieces could result in the 

740 RFI being fitted in the 'clean' bandpass. In 

741 later stages of the fit, a third-order polynomial 

742 is fit per piece, so for best results, please 

743 ensure that nchan/maxnpieces is at-least 10. 

744 flagdimension Choose the directions along which to perform flagging 

745 Subparameter of mode='tfcrop' 

746 Default: 'freqtime' (first flag along frequency, 

747 and then along time)  

748 Options: 'time', 'freq', 'timefreq', 'freqtime' 

749  

750 For most cases, 'freqtime' or 'timefreq' are 

751 appropriate, and differences between these 

752 choices are apparant only if RFI in one dimension 

753 is significantly stronger than the other. The 

754 goal is to flag the dominant RFI first. 

755 If there are very few (less than 5) channels of 

756 data, then choose 'time'. Similarly for 'freq'. 

757 usewindowstats Use sliding-window statistics to find additional flags. 

758 Subparameter of mode='tfcrop' 

759 Default: 'none'  

760 Options: 'none', 'sum', 'std', 'both'  

761  

762 NOTE: This is experimental! 

763 The 'sum' option chooses to flag a point, if the 

764 mean-value in a window centered on that point 

765 deviates from the fit by more than N-stddev/2.0.  

766  

767 NOTE: stddev is calculated between the data and 

768 fit as explained in Step (2). This option is an 

769 attempt to catch broad-band or time-persistent 

770 RFI that the above polynomial fits will 

771 mistakenly fit as the clean band. It is an 

772 approximation to the sumThreshold method found to 

773 be effective by Offringa et.al (2010) for LOFAR 

774 data. The 'std' option chooses to flag a point, 

775 if the 'local' stddev calculated in a window 

776 centered on that point is larger than 

777 N-stddev/2.0. This option is an attempt to catch 

778 noisy RFI that is not excluded in the polynomial 

779 fits, and which increases the global stddev, and 

780 results in fewer flags (based on the N-stddev 

781 threshold). 

782 halfwin Half-width of sliding window to use with "usewindowstats" 

783 (1,2,3). 

784 Subparameter of mode='tfcrop' 

785 Default: 1 (a 3-point window size) 

786 Options: 1, 2, 3 

787  

788 NOTE: This is experimental! 

789 extendflags Extend flags along time, frequency and correlation. 

790 Subparameter of mode='tfcrop|rflag' 

791 Default: True 

792 Options: True|False 

793  

794 NOTE: It is usually helpful to extend the flags 

795 along time, frequency, and correlation using this 

796 parameter, which will run the "extend" mode after 

797 "tfcrop" and extend the flags if more than 50% of 

798 the timeranges are already flagged, and if more 

799 than 80% of the channels are already flagged. It 

800 will also extend the flags to the other 

801 polarizations. The user may also set extendflags 

802 to False and run the "extend" mode in a second 

803 step within the same flagging run: 

804  

805 Example: cmd=["mode='tfcrop' freqcutoff=3.0 

806 usewindowstats='sum' extendflags=False", 

807 "mode='extend' extendpols=True growtime=50.0 

808 growaround=True"] 

809 flagdata(vis, mode='list', inpfile=cmd) 

810 winsize Number of timesteps in the sliding time window ( fparm(1) 

811 in AIPS ) 

812 Subparameter of mode='rflag' 

813 Default: 3 

814 timedev Time-series noise estimate ( noise in AIPS ) 

815 Subparameter of mode='rflag' 

816 Default: [] 

817  

818 Examples:  

819 timedev = 0.5 : Use this noise-estimate to 

820 calculate flags. Do not recalculate. 

821 timedev = [ [1,9,0.2], [1,10,0.5] ] : Use 

822 noise-estimate of 0.2 for field 1, spw 9, and 

823 noise-estimate of 0.5 for field 1, spw 10. 

824 timedev = [] : Auto-calculate noise 

825 estimates.  

826 'tdevfile.txt' : Auto-calculate noise 

827 estimates and write them into a file with the 

828 name given (any string will be interpreted as 

829 a file name which will be checked for 

830 existence). 

831 freqdev Spectral noise estimate ( scutoff in AIPS ) 

832 Subparameter of mode='rflag' 

833 Default: [] 

834  

835 This step depends on having a relatively-flat 

836 bandshape. Same parameter-options as 'timedev'. 

837 timedevscale Threshold scaling for timedev( fparm(9) in AIPS ). 

838 For Step 1 (time analysis), flag a point if local 

839 rms around it is larger than 'timedevscale' x 

840 'timedev' (fparm(0) in AIPS) 

841 Subparameter of mode='rflag' 

842 Default: 5.0 

843  

844 This scale parameter is only applied when 

845 flagging (action='apply') and displaying reports 

846 (display option). It is not used when the 

847 thresholds are simply calculated and saved into 

848 files (action='calculate', as in the two-passes 

849 usage pattern of AIPS) 

850 freqdevscale Threshold scaling for freqdev (fparm(10) in AIPS ).  

851 For Step 2 (spectral analysis), flag a point if 

852 local rms around it is larger than 'freqdevscale' 

853 x 'freqdev' (fparm(10) in AIPS) 

854 Subparameter of mode='rflag' 

855 Default: 5.0 

856  

857 Similarly as with timedevscale, freqdevscale is 

858 used when applying flags and displaying 

859 reports. It is not used when the thresholds are 

860 simply calculated and saved into files 

861 (action='calculate', as in the two-passes usage 

862 pattern of AIPS) 

863 spectralmax Flag whole spectrum if 'freqdev' is greater than 

864 spectralmax ( fparm(6) in AIPS ) 

865 Subparameter of mode='rflag' 

866 Default: 1E6 

867 spectralmin Flag whole spectrum if 'freqdev' is less than spectralmin 

868 ( fparm(5) in AIPS ) 

869 Subparameter of mode='rflag' 

870 Default: 0.0 

871 antint_ref_antenna Antenna of interest. Baselines with this antenna will be 

872 checked for flagged channels. 

873 Subparameter of mode='antint' 

874  

875 Note that this is not the same as the general 

876 'antenna' parameter of flagdata. The parameter 

877 antint_ref_antenna is mandatory with the 'antint' 

878 mode and chooses the antenna for which the 

879 fraction of channels flagged will be checked. 

880 minchanfrac Minimum fraction of flagged channels required for a 

881 baseline to be deemed as flagged 

882 Subparameter of mode='antint' 

883 Takes values between 0-1 (float). 

884  

885 In this mode flagdata does the following for 

886 every point in time. It checks the fraction of 

887 channels flagged for any of the polarization 

888 products and for every baseline to the antenna of 

889 interest. If the fraction is higher than this 

890 'minchanfrac' threshold then the data are flagged 

891 for this pont in time (this includes all the rows 

892 selected with the flagdata command that have that 

893 timestamp). 

894 This parameter will be ignored if spw specifies a 

895 channel. 

896 verbose Print timestamps of flagged integrations to the log 

897 Subparameter of mode='antint' 

898  

899 Examples:  

900 flagdata(vis, ..., spw='9', 

901 antint_ref_antenna='ea01') 

902 flagdata(vis, ..., spw='9', 

903 antint_ref_antenna='ea01', minchanfrac=0.3, 

904 verbose=True) ==> reduce the fraction of 

905 channels that are required to be flagged, and 

906 print information for every integration that 

907 is flagged. 

908 extendpols Extend flags to all selected correlations 

909 Subparameter of mode='extend' 

910 Default: True 

911 Options: True|False 

912  

913 For example, to extend flags from RR to only 

914 RL and LR, a data-selection of 

915 correlation='RR,LR,RL' is required along with 

916 extendpols=True. 

917 growtime For any channel, flag the entire timerange in the current 

918 2D chunk (set by 'ntime') if more than X% of the timerange is already 

919 flagged. 

920 Subparameter of mode='extend' 

921 Default: 50.0 

922 Options: 0.0 - 100.0 

923  

924 This option catches the low-intensity parts of 

925 time-persistent RFI. 

926 growfreq For any timestep, flag all channels in the current 2D 

927 chunk (set by data-selection) if more than X% of the channels are 

928 already flagged. 

929 Subparameter of mode='extend' 

930 Default: 50.0 

931 Options: 0.0 - 100.0 

932  

933 This option catches broad-band RFI that is 

934 partially identified by earlier steps. 

935 growaround Flag a point based on the number of flagged points around it. 

936 Subparameter of mode='extend' 

937 Default: False 

938 Options: False|True 

939  

940 For every un-flagged point on the 2D time/freq 

941 plane, if more than four surrounding points are 

942 already flagged, flag that point. This option 

943 catches some wings of strong RFI spikes. 

944 flagneartime Flag points before and after every flagged one, in the 

945 time-direction. 

946 Subparameter of mode='extend' 

947 Default: False 

948 Options: False|True 

949  

950 NOTE: This can result in excessive flagging. 

951 flagnearfreq Flag points before and after every flagged one, in the 

952 frequency-direction 

953 Subparameter of mode='extend' 

954 Default: False 

955 Options: False|True 

956  

957 NOTE: This can result in excessive flagging 

958 minrel Minimum number of flags (relative) to include in 

959 histogram 

960 Subparameter of mode='summary' 

961 Default: 0.0 

962 maxrel Maximum number of flags (relative) to include in 

963 histogram 

964 Subparameter of mode='summary' 

965 Default: 1.0 

966 minabs Minimum number of flags (absolute, inclusive) to include 

967 in histogram 

968 Subparameter of mode='summary' 

969 Default: 0 

970 maxabs Maximum number of flags (absolute, inclusive) to include 

971 in histogram 

972 Subparameter of mode='summary' 

973 Default: -1 

974  

975 To indicate infinity, use any negative number. 

976 spwchan List the number of flags per spw and per channel. 

977 Subparameter of mode='summary' 

978 Default: False 

979 Options: False|True 

980 spwcorr List the number of flags per spw and per correlation. 

981 Subparameter of mode='summary' 

982 Default: False 

983 Options: False|True 

984 basecnt Count the number of flags per baseline. The counts are added to the 

985 return result dictionary (in the 'baseline'' key) and also printed 

986 to the log. In addition, counts per antenna/scan are also reported 

987 and added to the result dictionary (key 'antenna:scan'). 

988 Subparameter of mode='summary' 

989 Default: False 

990 Options: False|True 

991 fieldcnt Produce a separated breakdown per field 

992 Subparameter of mode='summary' 

993 Default: False 

994 Options: False|True 

995 name Name for this summary, to be used as a key in the 

996 returned Python dictionary 

997 Subparameter of mode='summary' 

998 Default: 'Summary' 

999  

1000 It is possible to call the summary mode multiple 

1001 times in list mode. When calling the summary mode 

1002 as a command in a list, one can give different 

1003 names to each one of them so that they can be 

1004 easily pulled out of the summary's dictionary. 

1005  

1006 In summary mode, the task returns a dictionary of flagging statistics. 

1007  

1008 Example 1: 

1009 s = flagdata(..., mode='summary') 

1010 Then s will be a dictionary which contains 

1011 s['total'] : total number of data 

1012 s['flagged'] : amount of flagged data 

1013  

1014 Example 2:  

1015 Two summary commands in list mode, intercalating a 

1016 manual flagging command. 

1017 s = flagdata(..., mode='list', 

1018 inpfile=["mode='summary' name='InitFlags'", 

1019 "mode='manual' autocorr=True", "mode='summary' 

1020 name='Autocorr'"]) 

1021  

1022 The dictionary returned in 's' will contain two 

1023 dictionaries, one for each of the two summary 

1024 modes.  

1025 s['report0']['name'] : 'InitFlags' 

1026 s['report1']['name'] : 'Autocorr' 

1027 action Action to perform in MS/cal table or in the input list of 

1028 parameters. 

1029 Default: 'apply' 

1030 Options: 'none', 'apply','calculate' 

1031  

1032 - 'apply': Apply the flags to the MS. 

1033 - 'calculate': Only calculate the flags but do 

1034 not write them to the MS. This is useful if 

1035 used together with the display to analyse the 

1036 results before writing to the MS. 

1037 - '': When set to empty, the underlying tool will 

1038 not be executed and no flags will be 

1039 produced. No data selection will be done 

1040 either. This is useful when used together with 

1041 the parameter savepars to only save the current 

1042 parameters (or list of parameters) to the 

1043 FLAG_CMD sub-table or to an external file. 

1044 display Display data and/or end-of-MS reports at runtime. 

1045 Subparameter of action='apply|calculate' 

1046 Default: 'none' 

1047 Options: 'none', 'data', 'report', 'both' 

1048  

1049 - 'none': will not display anything. 

1050 - 'data': display data and flags per-chunk at 

1051 run-time, within an interactive GUI. 

1052 This option opens a GUI to show the 2D 

1053 time-freq planes of the data with old and new 

1054 flags, for all correlations per baseline. 

1055 -- The GUI allows stepping through all 

1056 baselines (prev/next) in the current chunk (set 

1057 by 'ntime'), and stepping to the next-chunk. 

1058 -- The 'flagdata' task can be quit from the 

1059 GUI, in case it becomes obvious that the 

1060 current set of parameters is just wrong. 

1061 -- There is an option to stop the display but 

1062 continue flagging. 

1063 - 'report': displays end-of-MS reports on the 

1064 screen. 

1065 - 'both': displays data per chunk and end-of-MS 

1066 reports on the screen 

1067 flagbackup Automatically backup flags before the run? 

1068 Default: True 

1069 Options: True|False 

1070  

1071 Flagversion names are chosen automatically, and 

1072 are based on the mode being used. 

1073 savepars Save the current parameters to the FLAG_CMD table of the 

1074 MS or to an output text file? 

1075 Default: False 

1076 Options: False|True 

1077  

1078 Note that when display is set to anything other 

1079 than 'none', savepars will be disabled. This is 

1080 done because in an interactive mode, the user may 

1081 skip data which may invalidate the initial input 

1082 parameters and there is no way to save the 

1083 interactive commands. When the input is a 

1084 calibration table it is only possible to save the 

1085 parameters to a file. 

1086 cmdreason A string containing a reason to save to the FLAG_CMD 

1087 table or to an output text file given by the outfile sub-parameter. 

1088 Subparameter of savepars=True 

1089 Default: '' (no reason will be added to output) 

1090  

1091 If the input contains any reason, they will be 

1092 replaced with this one. At the moment it is not 

1093 possible to add more than one reason.  

1094  

1095 Example: cmdreason='CLIP_ZEROS' 

1096 outfile Name of output file to save current parameters. If empty, 

1097 save to FLAG_CMD 

1098 Subparameter of savepars=True 

1099 Default: '' (save the parameters to the FLAG_CMD 

1100 table of the MS) 

1101  

1102 Example: outfile='flags.txt' will save the 

1103 parameters in a text file. 

1104 overwrite Overwrite the existing file given in 'outfile' 

1105 Default: True 

1106 Options: True|False 

1107  

1108 The default True will remove the existing file 

1109 given in 'outfile' and save the current flag 

1110 commands to a new file with the same name. When 

1111 set to False, the task will exit with an error 

1112 message if the file exist. 

1113 writeflags Internal hidden parameter. Do not modify. 

1114 RETURNS void 

1115 

1116 --------- examples ----------------------------------------------------------- 

1117 

1118  

1119  

1120 For more information, see the task pages of flagdata in CASA Docs: 

1121 https://casadocs.readthedocs.io 

1122 

1123 

1124 """ 

1125 

1126 _info_group_ = """flagging""" 

1127 _info_desc_ = """All-purpose flagging task based on data-selections and flagging modes/algorithms.""" 

1128 

1129 def __call__( self, vis='', mode='manual', autocorr=False, inpfile='', reason='any', tbuff=float(0.0), spw='', field='', antenna='', uvrange='', timerange='', correlation='', scan='', intent='', array='', observation='', feed='', clipminmax=[ ], datacolumn='DATA', clipoutside=True, channelavg=False, chanbin=int(1), timeavg=False, timebin='0s', clipzeros=False, quackinterval=float(1.0), quackmode='beg', quackincrement=False, tolerance=float(0.0), addantenna='', lowerlimit=float(0.0), upperlimit=float(90.0), ntime='scan', combinescans=False, timecutoff=float(4.0), freqcutoff=float(3.0), timefit='line', freqfit='poly', maxnpieces=int(7), flagdimension='freqtime', usewindowstats='none', halfwin=int(1), extendflags=True, winsize=int(3), timedev='', freqdev='', timedevscale=float(5.0), freqdevscale=float(5.0), spectralmax=float(1E6), spectralmin=float(0.0), antint_ref_antenna='', minchanfrac=float(0.6), verbose=False, extendpols=True, growtime=float(50.0), growfreq=float(50.0), growaround=False, flagneartime=False, flagnearfreq=False, minrel=float(0.0), maxrel=float(1.0), minabs=int(0), maxabs=int(-1), spwchan=False, spwcorr=False, basecnt=False, fieldcnt=False, name='Summary', action='apply', display='', flagbackup=True, savepars=False, cmdreason='', outfile='', overwrite=True, writeflags=True ): 

1130 schema = {'vis': {'type': 'cReqPath', 'coerce': _coerce.expand_path}, 'mode': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'tfcrop', 'extend', 'manualflag', 'quack', 'clip', 'manual', 'shadow', 'summary', 'antint', 'list', 'unflag', 'rflag', 'elevation' ]}, 'autocorr': {'type': 'cBool'}, 'inpfile': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'reason': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'tbuff': {'anyof': [{'type': 'cFloat', 'coerce': _coerce.to_float}, {'type': 'cFloatVec', 'coerce': [_coerce.to_list,_coerce.to_floatvec]}]}, 'spw': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'field': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'antenna': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'uvrange': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'timerange': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'correlation': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'scan': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'intent': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'array': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'observation': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cInt'}]}, 'feed': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'clipminmax': {'type': 'cFloatVec', 'coerce': [_coerce.to_list,_coerce.to_floatvec]}, 'datacolumn': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'clipoutside': {'anyof': [{'type': 'cBool'}, {'type': 'cBoolVec', 'coerce': [_coerce.to_list,_coerce.to_boolvec]}]}, 'channelavg': {'anyof': [{'type': 'cBool'}, {'type': 'cBoolVec', 'coerce': [_coerce.to_list,_coerce.to_boolvec]}]}, 'chanbin': {'anyof': [{'type': 'cInt'}, {'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}]}, 'timeavg': {'anyof': [{'type': 'cBool'}, {'type': 'cBoolVec', 'coerce': [_coerce.to_list,_coerce.to_boolvec]}]}, 'timebin': {'type': 'cStr', 'coerce': _coerce.to_str}, 'clipzeros': {'type': 'cBool'}, 'quackinterval': {'anyof': [{'type': 'cFloat', 'coerce': _coerce.to_float}, {'type': 'cFloatVec', 'coerce': [_coerce.to_list,_coerce.to_floatvec]}, {'type': 'cInt'}, {'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}]}, 'quackmode': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'quackincrement': {'anyof': [{'type': 'cBool'}, {'type': 'cBoolVec', 'coerce': [_coerce.to_list,_coerce.to_boolvec]}]}, 'tolerance': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'addantenna': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cDict'}]}, 'lowerlimit': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'upperlimit': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'ntime': {'anyof': [{'type': 'cFloat', 'coerce': _coerce.to_float}, {'type': 'cStr', 'coerce': _coerce.to_str}]}, 'combinescans': {'type': 'cBool'}, 'timecutoff': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'freqcutoff': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'timefit': {'type': 'cStr', 'coerce': _coerce.to_str}, 'freqfit': {'type': 'cStr', 'coerce': _coerce.to_str}, 'maxnpieces': {'type': 'cInt'}, 'flagdimension': {'type': 'cStr', 'coerce': _coerce.to_str}, 'usewindowstats': {'type': 'cStr', 'coerce': _coerce.to_str}, 'halfwin': {'type': 'cInt'}, 'extendflags': {'type': 'cBool'}, 'winsize': {'type': 'cInt'}, 'timedev': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'freqdev': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'timedevscale': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'freqdevscale': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'spectralmax': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'spectralmin': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'antint_ref_antenna': {'type': 'cStr', 'coerce': _coerce.to_str}, 'minchanfrac': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'verbose': {'type': 'cBool'}, 'extendpols': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'growtime': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'growfreq': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'growaround': {'type': 'cBool'}, 'flagneartime': {'type': 'cBool'}, 'flagnearfreq': {'type': 'cBool'}, 'minrel': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'maxrel': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'minabs': {'type': 'cInt'}, 'maxabs': {'type': 'cInt'}, 'spwchan': {'type': 'cBool'}, 'spwcorr': {'type': 'cBool'}, 'basecnt': {'type': 'cBool'}, 'fieldcnt': {'type': 'cBool'}, 'name': {'type': 'cStr', 'coerce': _coerce.to_str}, 'action': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'apply', 'calculate', 'none', '' ]}, 'display': {'type': 'cStr', 'coerce': _coerce.to_str}, 'flagbackup': {'type': 'cBool'}, 'savepars': {'type': 'cBool'}, 'cmdreason': {'type': 'cStr', 'coerce': _coerce.to_str}, 'outfile': {'type': 'cStr', 'coerce': _coerce.to_str}, 'overwrite': {'type': 'cBool'}, 'writeflags': {'type': 'cBool'}}