Coverage for /wheeldirectory/casa-6.7.0-11-py3.10.el8/lib/py/lib/python3.10/site-packages/casatools/__casac__/simulator.py: 42%

1# This file was automatically generated by SWIG (http://www.swig.org). 

2# Version 3.0.12 

3# 

4# Do not make changes to this file unless you know what you are doing--modify 

5# the SWIG interface file instead. 

6 

7from sys import version_info as _swig_python_version_info 

8if _swig_python_version_info >= (2, 7, 0): 

9 def swig_import_helper(): 

10 import importlib 

11 pkg = __name__.rpartition('.')[0] 

12 mname = '.'.join((pkg, '_simulator')).lstrip('.') 

13 try: 

14 return importlib.import_module(mname) 

15 except ImportError: 

16 return importlib.import_module('_simulator') 

17 _simulator = swig_import_helper() 

18 del swig_import_helper 

19elif _swig_python_version_info >= (2, 6, 0): 

20 def swig_import_helper(): 

21 from os.path import dirname 

22 import imp 

23 fp = None 

24 try: 

25 fp, pathname, description = imp.find_module('_simulator', [dirname(__file__)]) 

26 except ImportError: 

27 import _simulator 

28 return _simulator 

29 try: 

30 _mod = imp.load_module('_simulator', fp, pathname, description) 

31 finally: 

32 if fp is not None: 

33 fp.close() 

34 return _mod 

35 _simulator = swig_import_helper() 

36 del swig_import_helper 

37else: 

38 import _simulator 

39del _swig_python_version_info 

40 

41try: 

42 _swig_property = property 

43except NameError: 

44 pass # Python < 2.2 doesn't have 'property'. 

45 

46try: 

47 import builtins as __builtin__ 

48except ImportError: 

49 import __builtin__ 

50 

51def _swig_setattr_nondynamic(self, class_type, name, value, static=1): 

52 if (name == "thisown"): 

53 return self.this.own(value) 

54 if (name == "this"): 

55 if type(value).__name__ == 'SwigPyObject': 

56 self.__dict__[name] = value 

57 return 

58 method = class_type.__swig_setmethods__.get(name, None) 

59 if method: 

60 return method(self, value) 

61 if (not static): 

62 if _newclass: 

63 object.__setattr__(self, name, value) 

64 else: 

65 self.__dict__[name] = value 

66 else: 

67 raise AttributeError("You cannot add attributes to %s" % self) 

68 

69 

70def _swig_setattr(self, class_type, name, value): 

71 return _swig_setattr_nondynamic(self, class_type, name, value, 0) 

72 

73 

74def _swig_getattr(self, class_type, name): 

75 if (name == "thisown"): 

76 return self.this.own() 

77 method = class_type.__swig_getmethods__.get(name, None) 

78 if method: 

79 return method(self) 

80 raise AttributeError("'%s' object has no attribute '%s'" % (class_type.__name__, name)) 

81 

82 

83def _swig_repr(self): 

84 try: 

85 strthis = "proxy of " + self.this.__repr__() 

86 except __builtin__.Exception: 

87 strthis = "" 

88 return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,) 

89 

90try: 

91 _object = object 

92 _newclass = 1 

93except __builtin__.Exception: 

94 class _object: 

95 pass 

96 _newclass = 0 

97 

98class simulator(_object): 

99 """Proxy of C++ casac::simulator class.""" 

100 

101 __swig_setmethods__ = {} 

102 __setattr__ = lambda self, name, value: _swig_setattr(self, simulator, name, value) 

103 __swig_getmethods__ = {} 

104 __getattr__ = lambda self, name: _swig_getattr(self, simulator, name) 

105 __repr__ = _swig_repr 

106 

107 def __init__(self): 

108 """__init__(self) -> simulator""" 

109 this = _simulator.new_simulator() 

110 try: 

111 self.this.append(this) 

112 except __builtin__.Exception: 

113 self.this = this 

114 

115 def open(self, *args, **kwargs): 

116 """ 

117 open(self, _ms) -> bool 

118 

119 

120 

121 Summary: 

122 Construct a simulator tool and create a new MeasurementSet 

123 

124 Description: 

125 

126 

127 A simulator tool can either operate on an existing MeasurementSet, 

128 predicting and/or corrupting data on the existing uvw coordinates 

129 

130 -- to do that open the MS with sm.openfromms(msname). 

131 

132 or it can be used to create a new MeasurementSet from descriptions of 

133 the array configuration and the observational parameters 

134 

135 -- to create a new MS, use this method sm.open(msname). 

136 

137 You will also need to run setconfig, setfield, setspw, setspwindow, 

138 setfeed, and settimes. 

139 

140 Creating the actual (empty) MS is accomplished with sm.observe. 

141 Data can be subsequently sm.predict-ed and sm.corrupt-ed. 

142 

143 NOTE: sm.predict assumes the model image units are Jy/pixel, and 

144 in fact will overwrite the brightness units of the image itself! 

145 

146 

147 Input Parameters: 

148 ms MeasurementSet to be created 

149 

150 Example: 

151 

152 In this example, we read in the antenna coordinates from an ASCII file, 

153 and simulate a single-pointing VLA observation with a calibrator. 

154 Note that no primary beam attenuation will be applied (see sm.setvp). 

155 

156 tabname = 'VLAC.LOCAL.TAB' 

157 asciifile = 'VLAC.LOCAL.STN' 

158 mytab=table.create() 

159 mytab.fromascii(tabname, asciifile); 

160 xx=[]; yy:=[]; zz:=[]; diam:=[]; 

161 xx = mytab.getcol('X'); 

162 yy = mytab.getcol('Y'); 

163 zz = mytab.getcol('Z'); 

164 diam = mytab.getcol('DIAM'); 

165 # 

166 sm.open('NEW1.ms') 

167 # do configuration 

168 posvla = me.observatory('vla'); # me.observatory('ALMA') also works! 

169 sm.setconfig(telescopename='VLA', x=xx, y=yy, z=zz, dishdiameter=diam, 

170 mount='alt-az', antname='VLA', 

171 coordsystem='local', referencelocation=posvla); 

172 

173 # Initialize the spectral windows 

174 sm.setspwindow(spwname='CBand', freq='5GHz', 

175 deltafreq='50MHz', 

176 freqresolution='50MHz', 

177 nchannels=1, 

178 stokes='RR RL LR LL'); 

179 sm.setspwindow(spwname='LBand', freq='1.420GHz', 

180 deltafreq='3.2MHz', 

181 freqresolution='3.2MHz', 

182 nchannels=32, 

183 stokes='RR LL'); 

184 

185 # Initialize the source and calibrater 

186 sm.setfield(sourcename='My cal', 

187 sourcedirection=['J2000','00h0m0.0','+45.0.0.000'], 

188 calcode='A'); 

189 sm.setfield(sourcename='My source', 

190 sourcedirection=['J2000','01h0m0.0','+47.0.0.000']); 

191 

192 sm.setlimits(shadowlimit=0.001, elevationlimit='8.0deg'); 

193 sm.setauto(autocorrwt=0.0); 

194 

195 sm.settimes(integrationtime='10s', usehourangle=F, 

196 referencetime=me.epoch('utc', 'today')); 

197 

198 sm.observe('My cal', 'LBand', starttime='0s', stoptime='300s'); 

199 sm.observe('My source', 'LBand', starttime='310s', stoptime='720s'); 

200 sm.observe('My cal', 'CBand', starttime='720s', stoptime='1020s'); 

201 sm.observe('My source', 'CBand', starttime='1030s', stoptime='1500s'); 

202 

203 sm.setdata(spwid=1, fieldid=1); 

204 sm.predict(imagename='M31.MOD'); 

205 sm.setdata(spwid=2, fieldid=2); 

206 sm.predict(imagename='BigLBand.MOD'); 

207 sm.close(); 

208 

209 -------------------------------------------------------------------------------- 

210 

211 """ 

212 return _simulator.simulator_open(self, *args, **kwargs) 

213 

214 

215 def openfromms(self, *args, **kwargs): 

216 """ 

217 openfromms(self, _ms) -> bool 

218 

219 

220 

221 Summary: 

222 Construct a simulator tool using an already existing MS 

223 

224 Description: 

225 

226 

227 A simulator tool can either operate on an existing MeasurementSet, 

228 predicting and/or corrupting data on the existing uvw coordinates 

229 - to do that open the MS with sm.openfromms(msname) 

230 or it can be used to create a new MeasurementSet from descriptions of 

231 the array configuration and the observational parameters. 

232 - to create a new MS, use sm.open(msname). 

233 

234 NOTE: sm.predict assumes the model image units are Jy/pixel, and in 

235 fact will overwrite the brightness units of the image itself! 

236 

237 

238 Input Parameters: 

239 ms MeasurementSet to be processed 

240 

241 Example: 

242 

243 sm.openfromms('3C273XC1.MS'); 

244 sm.predict('3C273XC1.imagename'); 

245 sm.setnoise(simplenoise='10mJy'); 

246 sm.setgain(interval='100s', amplitude=0.01); 

247 sm.corrupt(); 

248 sm.close(); 

249 

250 -------------------------------------------------------------------------------- 

251 

252 """ 

253 return _simulator.simulator_openfromms(self, *args, **kwargs) 

254 

255 

256 def close(self): 

257 """ 

258 close(self) -> bool 

259 

260 

261 

262 Summary: 

263 Close the simulator tool 

264 

265 Description: 

266 

267 

268 Close tools and write data to disk. This is a synonym for done. 

269 

270 

271 -------------------------------------------------------------------------------- 

272 

273 """ 

274 return _simulator.simulator_close(self) 

275 

276 

277 def done(self): 

278 """ 

279 done(self) -> bool 

280 

281 

282 

283 Summary: 

284 Close the simulator tool 

285 

286 Description: 

287 

288 

289 Close tools and write data to disk. This is a synonym for done. 

290 

291 

292 -------------------------------------------------------------------------------- 

293 

294 """ 

295 return _simulator.simulator_done(self) 

296 

297 

298 def name(self): 

299 """ 

300 name(self) -> string 

301 

302 

303 

304 Summary: 

305 Provide the name of the attached MeasurementSet 

306 

307 Description: 

308 

309 

310 Returns the name of the attached MeasurementSet. 

311 

312 

313 -------------------------------------------------------------------------------- 

314 

315 """ 

316 return _simulator.simulator_name(self) 

317 

318 

319 def summary(self): 

320 """ 

321 summary(self) -> bool 

322 

323 

324 

325 Summary: 

326 Summarize the current state 

327 

328 Description: 

329 

330 

331 Writes a summary of the currently set properties to the default logger. 

332 

333 

334 -------------------------------------------------------------------------------- 

335 

336 """ 

337 return _simulator.simulator_summary(self) 

338 

339 

340 def type(self): 

341 """ 

342 type(self) -> string 

343 

344 

345 

346 Summary: 

347 Return the type of this tool 

348 

349 Description: 

350 

351 

352 This function returns the string `Simulator'. It is used so that in a 

353 script, you can make sure this variable is a simulator tool. 

354 

355 

356 -------------------------------------------------------------------------------- 

357 

358 """ 

359 return _simulator.simulator_type(self) 

360 

361 

362 def settimes(self, *args, **kwargs): 

363 """ 

364 settimes(self, _integrationtime, _usehourangle, _referencetime) -> bool 

365 

366 

367 

368 Summary: 

369 Set integration time, etc. 

370 

371 Description: 

372 

373 

374 This method sets values to be used in sm.observe. 

375 

376 If usehourangle=False, the start and stop times in sm.observe are 

377 referenced to referencetime. 

378 

379 If usehourangle=True, then in sm.observe, starttime/stoptime will be 

380 interpreted as startha/stopha. 

381 In that case, the start and stop times are calculated such that the 

382 start time is later than the reference time, but less than one day 

383 later. The hour angles refer to the first source observed. 

384 

385 

386 Input Parameters: 

387 integrationtime Integration time 

388 usehourangle Use starttime/stoptime as hour angles - else they are referenced to referencetime 

389 referencetime Reference time for starttime and stoptime. Epoch Measure . E.g me.epoch('UTC', '50000.0d')  

390 

391 -------------------------------------------------------------------------------- 

392 

393 """ 

394 return _simulator.simulator_settimes(self, *args, **kwargs) 

395 

396 

397 def observe(self, *args, **kwargs): 

398 """ 

399 observe(self, _sourcename, _spwname, _starttime, _stoptime, _add_observation, _state_sig, _state_ref, _state_cal, _state_load, _state_sub_scan, _state_obs_mode, _observer, _project) -> bool 

400 

401 

402 

403 Summary: 

404 Observe a given configuration 

405 

406 Description: 

407 

408 

409 Observe a given source with a given spectral window for the specified 

410 times, including start, stop, integration, and gap times. 

411 

412 If usehourangle=False (set with settimes), the start and stop times 

413 are referenced to referencetime. 

414 

415 If userhourangle=True, starttime/stoptime are interpreted as 

416 startha/stopha, the start and stop times are calculated such that the 

417 start time is later than the reference time, but less than one day 

418 later, and the hour angles refer to the first source observed. 

419 

420 setconfig, setspwindow, setfeed, and setfield must 

421 be run before observe can be run. 

422 

423 See also sm.observemany 

424 

425 

426 Input Parameters: 

427 sourcename Name of source or field (must be specified) 

428 spwname Unique user-supplied name for this spectral window 

429 starttime Start time referenced to referencetime, or start hour angle 

430 stoptime Stop time referenced to referencetime, or stop hour angle 

431 add_observation Add a new line to the OBSERVATION subtable for this call 

432 state_sig a new line will be added to STATE if the following don't match 

433 state_ref  

434 state_cal  

435 state_load  

436 state_sub_scan  

437 state_obs_mode  

438 observer  

439 project  

440 

441 -------------------------------------------------------------------------------- 

442 

443 """ 

444 return _simulator.simulator_observe(self, *args, **kwargs) 

445 

446 

447 def observemany(self, *args, **kwargs): 

448 """ 

449 observemany(self, _sourcenames, _spwname, _starttimes, _stoptimes, _directions, _add_observation, _state_sig, _state_ref, _state_cal, _state_load, _state_sub_scan, _state_obs_mode, _observer, _project) -> bool 

450 

451 

452 

453 Summary: 

454 Observe a given configuration 

455 

456 Description: 

457 

458 

459 Observe given sources with a given spectral window for the specified 

460 times, including start, stop, integration, and gap times. 

461 

462 If usehourangle=False (set with settimes), the start and stop times 

463 are referenced to referencetime. 

464 

465 If userhourangle=True, starttime/stoptime are interpreted as 

466 startha/stopha, the start and stop times are calculated such that the 

467 start time is later than the reference time, but less than one day 

468 later, and the hour angles refer to the first source observed. 

469 

470 See also sm.observe 

471 

472 

473 Input Parameters: 

474 sourcenames Name of sources 

475 spwname Unique user-supplied name for this spectral window 

476 starttimes Start times referenced to referencetime, or start hour angle 

477 stoptimes Stop time referenced to referencetime, or stop hour angle 

478 directions  

479 add_observation Add a new line to the OBSERVATION subtable for this call 

480 state_sig a new line will be added to STATE if the following don't match 

481 state_ref  

482 state_cal  

483 state_load  

484 state_sub_scan  

485 state_obs_mode  

486 observer  

487 project  

488 

489 -------------------------------------------------------------------------------- 

490 

491 """ 

492 return _simulator.simulator_observemany(self, *args, **kwargs) 

493 

494 

495 def setlimits(self, *args, **kwargs): 

496 """ 

497 setlimits(self, _shadowlimit, _elevationlimit) -> bool 

498 

499 

500 

501 Summary: 

502 Set limits for observing 

503 

504 Description: 

505 

506 

507 Data are flagged for two conditions: 

508 

509 - Below elevation limit: If either of the antennas point below the 

510 specified elevation limit then the data are flagged. The elevation is 

511 calculated correctly for antennas at different locations (such as 

512 occurs in VLBI). 

513 

514 - Shadowing: If one antenna shadows another such that the fractional 

515 (geometric) blockage is greater than the specified limit then the data 

516 are flagged. No correction for blockage is made for shadowed but 

517 non-flagged points. 

518 

519 

520 Input Parameters: 

521 shadowlimit Maximum fraction of geometrically shadowed area before flagging occurs 

522 elevationlimit Minimum elevation angle before flagging occurs 

523 

524 -------------------------------------------------------------------------------- 

525 

526 """ 

527 return _simulator.simulator_setlimits(self, *args, **kwargs) 

528 

529 

530 def setauto(self, *args, **kwargs): 

531 """ 

532 setauto(self, _autocorrwt) -> bool 

533 

534 

535 

536 Summary: 

537 Set autocorrelation weight 

538 

539 Description: 

540 

541 

542 

543 

544 Input Parameters: 

545 autocorrwt Weight to assign autocorrelations (0=none) 

546 

547 -------------------------------------------------------------------------------- 

548 

549 """ 

550 return _simulator.simulator_setauto(self, *args, **kwargs) 

551 

552 

553 def setconfig(self, *args, **kwargs): 

554 """ 

555 setconfig(self, _telescopename, _x, _y, _z, _dishdiameter, _offset, _mount, _antname, _padname, _coordsystem, _referencelocation) -> bool 

556 

557 

558 

559 Summary: 

560 Set the antenna configuration 

561 

562 Description: 

563 

564 

565 Set the positions of the antennas. 

566 - The name of the telescope will control which voltage pattern 

567 is applied to the data (see sm.setvp for details). 

568 - The diameter(s) will be written to the antenna subtable but 

569 ONLY affect the calculated visibilities in sm.predict if 

570 telescope=ALMA,ACA,OVRO, *and* ftmachine=mosaic 

571 (see sm.setvp for details). 

572 - simutil::readantenna can be used to read an antenna config. file 

573 which includes many existing observatories. 

574 see help for the simobserve task, or the example below 

575 

576 

577 Input Parameters: 

578 telescopename Name of the telescope we are simulating (determines VP) 

579 x Vector of x values of all antennas [m] 

580 y Vector of y values of all antennas [m] 

581 z Vector of z values of all antennas [m] 

582 dishdiameter Vector of diameters of all antennas [m] 

583 offset Vector of offset of all antennas [m] 

584 mount Vector of mount types of all antennas (recognized mounts are 'ALT-AZ', 'EQUATORIAL', 'X-Y', 'ORBITING', 'BIZARRE' 

585 antname Vector of names of all antennas 

586 padname Vector of names of pads or stations 

587 coordsystem Coordinate system of antenna positions [x,y,z], possibilities are 'global', 'local' , 'longlat' 

588 referencelocation Reference location [required for local coords] Position Measure of Coordinates of array location. E.g me.position('ITRF', '30.5deg', -20.2deg', 6000km') or me.observatory('ALMA')  

589 

590 Example: 

591 

592 # known antenna configurations are stored in the data repository, 

593 # for historical reasons under 'alma' even though this includes all 

594 # known observatories: 

595 configdir=casa.values()[0]['data']+'/alma/simmos/' 

596 

597 # please look in that directory if your observatory is present. 

598 # if so, simutil can be used to read the file: 

599 from simutil import simutil 

600 # a simutil must be instantiated to use most methods 

601 u=simutil() 

602 x,y,z,d,padnames,telescope,posobs = u.readantenna(configdir+'vla.a.cfg') 

603 

604 # note that readantenna converts the positions to earth-centered 

605 # global, from whatever format is in the configuration file, so 

606 # coordsystem='global' should be used in setconfig 

607 sm.setconfig(telescopename=telescope, x=x, y=y, z=z, 

608 dishdiameter=d.tolist(), 

609 mount=['alt-az'], antname=padnames, 

610 coordsystem='global', referencelocation=pospbs); 

611 

612 -------------------------------------------------------------------------------- 

613 

614 """ 

615 return _simulator.simulator_setconfig(self, *args, **kwargs) 

616 

617 

618 def setfeed(self, *args, **kwargs): 

619 """ 

620 setfeed(self, _mode, _x, _y, _pol) -> bool 

621 

622 

623 

624 Summary: 

625 Set the feed parameters 

626 

627 Description: 

628 

629 

630 Specify feed parameters. At this moment, you only have the choice 

631 between 'perfect R L' and 'perfect X Y' (i.e., you cannot invent 

632 your own corrupted feeds yet). Doesn't need to be run if you want 

633 perfect R and L feeds. 

634 

635 

636 Input Parameters: 

637 mode Mode for specifying feed parameters (currently, perfect only) 

638 x Some very secretive feed array parameter x 

639 y Some more very secretive feed array parameter y  

640 pol  

641 

642 -------------------------------------------------------------------------------- 

643 

644 """ 

645 return _simulator.simulator_setfeed(self, *args, **kwargs) 

646 

647 

648 def setfield(self, *args, **kwargs): 

649 """ 

650 setfield(self, _sourcename, _sourcedirection, _calcode, _distance) -> bool 

651 

652 

653 

654 Summary: 

655 Set one or more observed fields 

656 

657 Description: 

658 

659 

660 Set one or more observed fields, including name and coordinates. 

661 Can be invoked multiple times for a complex observation. 

662 Must be invoked at least once before sm.observe. 

663 

664 If the distance to the object is set then the phase term includes a 

665 curvature for the near-field effect at the center of the image. 

666 

667 

668 Input Parameters: 

669 sourcename Name of source or field (must be specified) 

670 sourcedirection Direction Measure of Coordinates of source to be observed. E.g me.direction('J2000', '30.5deg','-20.2deg').  

671 calcode Calibration code 

672 distance Distance to the object 

673 

674 Example: 

675 

676 sm.setconfig(telescopename=telescope, x=x, y=y, z=z, 

677 dishdiameter=d.tolist(), 

678 mount=['alt-az'], antname=padnames, 

679 coordsystem='global', referencelocation=pospbs); 

680 

681 sm.setspwindow(spwname='XBAND', freq='8GHz', deltafreq='50MHz', 

682 freqresolution='50MHz', nchannels=1, stokes='RR 

683 LL'); 

684 dir0 = me.direction('B1950', '16h00m0.0', '50d0m0.000') 

685 sm.setfield(sourcename='SIMU1', sourcedirection=dir0); 

686 sm.settimes(integrationtime='10s', usehourangle=True, 

687 referencetime=me.epoch('TAI', '2012/01/01/00:00:00')) 

688 sm.observe(sourcename='SIMU1', spwname='XBAND', 

689 starttime='0s', stoptime='3600s') 

690 

691 -------------------------------------------------------------------------------- 

692 

693 """ 

694 return _simulator.simulator_setfield(self, *args, **kwargs) 

695 

696 

697 def setmosaicfield(self, *args, **kwargs): 

698 """ 

699 setmosaicfield(self, _sourcename, _calcode, _fieldcenter, _xmosp, _ymosp, _mosspacing, _distance) -> bool 

700 

701 

702 

703 Summary: 

704 Set observed mosaic fields 

705 

706 Description: 

707 

708 

709 Set mosaic fields by internally invoking setfield multiple times. 

710 Currently only handle a rectangular mosaicing pattern. Either 

711 setfield or setmosaicfield must be invoked at least once before 

712 observe. 

713 

714 If the distance to the object is set then the phase term includes a 

715 curvature for the near-field effect at the center of the image. 

716 

717 

718 Input Parameters: 

719 sourcename Name of source or field (must be specified). 

720 calcode Calibration code 

721 fieldcenter Coordinates of mosaic field center 

722 xmosp Number of mosaic pointing in horizontal direction 

723 ymosp Number of mosaic pointing in vertical direction 

724 mosspacing Spacing between mosaic pointings 

725 distance Distance to the object 

726 

727 Example: 

728 

729 sm.setconfig(telescopename='VLA', x=xx, y=yy, z=zz, dishdiameter=diam, 

730 mount='alt-az', antname='VLA', 

731 coordsystem='local', referencelocation=dm.observatory('vla')); 

732 

733 sm.setspwindow(spwname='XBAND', freq='8GHz', deltafreq='50MHz', 

734 freqresolution='50MHz', nchannels=1, stokes='RR 

735 LL'); 

736 dir0 = me.direction('B1950', '16h00m0.0', '50d0m0.000') 

737 sm.setmosaicfield(sourcename='SIMU1', fieldcenter=dir0, 

738 xmosp=2, ymosp=2, mosspacing='154.5arcsec'); 

739 sm.settimes(integrationtime='10s'); 

740 sm.observe('SIMU1_1', 'XBAND', starttime='0s', stoptime='100s'); 

741 sm.observe('SIMU1_2', 'XBAND', starttime='110s', stoptime='210s'); 

742 sm.observe('SIMU1_3', 'XBAND', starttime='220s', stoptime='320s'); 

743 sm.observe('SIMU1_4', 'XBAND', starttime='330s', stoptime='430s'); 

744 

745 -------------------------------------------------------------------------------- 

746 

747 """ 

748 return _simulator.simulator_setmosaicfield(self, *args, **kwargs) 

749 

750 

751 def setspwindow(self, *args, **kwargs): 

752 """ 

753 setspwindow(self, _spwname, _freq, _deltafreq, _freqresolution, _refcode, _nchannels, _stokes) -> bool 

754 

755 

756 

757 Summary: 

758 Set one or more spectral windows 

759 

760 Description: 

761 

762 

763 Set one or more spectral windows for the observations, including 

764 starting frequency, number of channels, channel increment and 

765 resolution, and stokes parameters observed. Can be invoked 

766 multiple times for a complex observation. Must be invoked at 

767 least once before observe. 

768 

769 

770 Input Parameters: 

771 spwname Unique user-supplied name for this spectral window 

772 freq Starting frequency 

773 deltafreq Frequency increment per channel 

774 freqresolution Frequency resolution per channel 

775 refcode Spectral reference code e.g. LSRK, TOPO, BARY 

776 nchannels Number of channels 

777 stokes Stokes types to simulate 

778 

779 Example: 

780 

781 To simulate a two spectral window (or two IF's in VLA jargon) data 

782 set, use setpwid as follows (here we are simulating 16 channels, 50MHz 

783 wide channel for each spectral window) 

784 

785 

786 sm.setspwindow(spwname='CBAND', freq='2GHz', deltafreq='50MHz', 

787 freqresolution='50MHz', nchannels=16, stokes='RR LL'); 

788 

789 sm.setspwindow(spwname='SBAND', freq='5GHz', deltafreq='50MHz', 

790 freqresolution='50MHz', nchannels=16, stokes='RR LL'); 

791 

792 

793 Note that the spwname is used in observe to determine which spectral window 

794 to use. 

795 

796 -------------------------------------------------------------------------------- 

797 

798 """ 

799 return _simulator.simulator_setspwindow(self, *args, **kwargs) 

800 

801 

802 def setdata(self, *args, **kwargs): 

803 """ 

804 setdata(self, _spwid, _fieldid, _msselect) -> bool 

805 

806 

807 

808 Summary: 

809 Set the data parameters selection for subsequent processing 

810 

811 Description: 

812 

813 

814 This setup tool function selects which data are to be used 

815 subsequently. After invocation of setdata, only the selected data are 

816 operated on. 

817 

818 

819 Input Parameters: 

820 spwid Spectral Window Ids (0 relative) to select 

821 fieldid Field Ids (0 relative) to select 

822 msselect TAQL select string applied as a logical 'and' with the other selections 

823 

824 -------------------------------------------------------------------------------- 

825 

826 """ 

827 return _simulator.simulator_setdata(self, *args, **kwargs) 

828 

829 

830 def predict(self, *args, **kwargs): 

831 """ 

832 predict(self, _imagename, _complist, _incremental) -> bool 

833 

834 

835 

836 Summary: 

837 Predict astronomical data from an image or components 

838 

839 Description: 

840 

841 

842 Predict astronomical data from an image. The (u,v) coordinates 

843 already exist, either from a MeasurementSet we have read in or by 

844 generating the MeasurementSet coordinates and empty data through 

845 smobserve. This method calculates visibilities for those 

846 coordinates. 

847 

848 - predict(incremental=False) calculates new visibilities and 

849 replaces the DATA column, 

850 - predict(incremental=True) calculates new visibilities, adds 

851 them to the DATA column 

852 - predict for any value of incremental then sets CORRECTED_DATA 

853 equal to DATA, and MODEL_DATA to 1 

854 - predict assumes model image units are Jy/pixel, and in fact 

855 will overwrite the brightness units of the image itself! 

856 - treatment of primary beam depends critically on parameters set in 

857 sm.setvp() and sm.setoptions(ftmachine) - see help sm.setvp for 

858 details. For componentlists, if sm.setvp() is run prior to predict, then the spectral variation of each component in the componentlist will include the multiplicative term of the beam value for each channel frequency. So a flat spectrum component will show the frequency variation of the beam in the predicted visibilities. 

859 

860 

861 

862 Input Parameters: 

863 imagename Name of image from which to predict visibilities 

864 complist Name of component list 

865 incremental Add this model to the existing Data Visibilities? 

866 

867 -------------------------------------------------------------------------------- 

868 

869 """ 

870 return _simulator.simulator_predict(self, *args, **kwargs) 

871 

872 

873 def setoptions(self, *args, **kwargs): 

874 """ 

875 setoptions(self, _ftmachine, _cache, _tile, _gridfunction, _location, _padding, _facets, _maxdata, _wprojplanes) -> bool 

876 

877 

878 

879 Summary: 

880 Set various processing options 

881 

882 Description: 

883 

884 

885 Set options for predict. See also imager help. 

886 

887 To simulate single dish data, use gridft=SD and gridfunction=PB. 

888 

889 To invoke primary beam convolution in the uv domain, use 

890 ftmachine='mosaic'. This is the only option that allows 

891 heterogeneous array simulation - see the example below and 

892 help sm.setvp for more details. 

893 

894 

895 Input Parameters: 

896 ftmachine Fourier transform machine. Possibilities are 'ft', 'sd', 'mosaic' 

897 cache Size of gridding cache in complex pixels 

898 tile Size of a gridding tile in pixels (in 1 dimension) 

899 gridfunction Gridding function. String: 'SF'|'BOX'|'PB' 

900 location Location used in phase rotations. Position Measure of Coordinates of array location. E.g me.position('ITRF', '30.5deg', '-20.2deg', '6000km') or me.observatory('ALMA')  

901 padding Padding factor in image plane (>=1.0) 

902 facets Number of facets 

903 maxdata Maximum data to write to a single TSM file (MB) 

904 wprojplanes Number of projection planes when using wproject as the ft-machine 

905 

906 Example: 

907 

908 # set some options 

909 sm.setoptions(cache=10000000, tile=32, gridfunction='BOX', me.location('vla')) 

910 

911 

912 # set ftmachine to invoke uv-domain primary beam convolution, and use that 

913 # to simulate a heterogeneous ALMA 7m+12m array. 

914 from simutil import simutil 

915 u=simutil() 

916 configdir=casa.values()[0]['data']+'/alma/simmos/' 

917 x,y,z,d,padnames,telescope,posobs = u.readantenna(configdir+'alma.cycle5.1.cfg') 

918 x2,y2,z2,d2,padnames2,telescope2,posobs2 = u.readantenna(configdir+'aca.cycle5.cfg') 

919 

920 sm.open('new.het.alma.ms') 

921 sm.setconfig(telescopename='ALMA', 

922 x=np.append(x,x2),y=np.append(y,y2),z=np.append(z,z2), 

923 dishdiameter=np.append(d,d2), 

924 mount=['alt-az'], padname=np.append(padnames,padnames2).tolist(), 

925 coordsystem='global', referencelocation=posobs) 

926 sm.setspwindow(spwname='band1', freq='330GHz', 

927 deltafreq='1GHz',freqresolution='1GHz',nchannels=1,stokes='XX YY') 

928 sm.setfeed(mode='perfect X Y',pol=['']) 

929 sm.setlimits(shadowlimit=0.01, elevationlimit='10deg') 

930 sm.setauto(0.0) 

931 sm.setfield(sourcename='src1', 

932 sourcedirection='ICRS 10:00:00.00 -23.01.22', 

933 calcode='OBJ', distance='0m') 

934 sm.setfield(sourcename='src2', 

935 sourcedirection='ICRS 10:00:00.00 -23.01.32', 

936 calcode='OBJ', distance='0m') 

937 sm.settimes(integrationtime='10s', usehourangle=True, 

938 referencetime=me.epoch('TAI', '2012/01/01/00:00:00')) 

939 etime='600s' 

940 sm.observe(sourcename='src1', spwname='band1', 

941 starttime=qa.mul(-1,qa.quantity(etime)), 

942 stoptime=qa.quantity(0,'s')); 

943 sm.observe(sourcename='src2', spwname='band1', 

944 starttime=qa.quantity(0,'s'), 

945 stoptime=qa.quantity(etime)); 

946 sm.setoptions(ftmachine='mosaic') 

947 sm.predict(imagename='point.ra10.image') 

948 sm.done() 

949 

950 -------------------------------------------------------------------------------- 

951 

952 """ 

953 return _simulator.simulator_setoptions(self, *args, **kwargs) 

954 

955 

956 def setvp(self, *args, **kwargs): 

957 """ 

958 setvp(self, _dovp, _usedefaultvp, _vptable, _dosquint, _parangleinc, _skyposthreshold, _pblimit) -> bool 

959 

960 

961 

962 Summary: 

963 Set the voltage pattern model for subsequent processing 

964 

965 Description: 

966 

967 

968 Set the voltage pattern model (and hence, the primary beam) used 

969 for a Telecope. There are currently two ways to set the voltage 

970 pattern: by using the extensive list of defaults which the system 

971 knows about, or by creating a voltage pattern description with 

972 the vpmanager. If you are 

973 simulating a telescope which doesn't yet exist, you will need to 

974 supply a model voltage pattern using 

975 the vpmanager. 

976 

977 sm.predict behavior depends critically on the parameters here, and 

978 the ftmachine parameter set in sm.setoptions 

979 

980 sm.predict will always query the vpmanager for a primary beam/VP pattern. 

981 if usedefaultvp==True, it will reset the vpmanager first, so that 

982 the PB obtained will be the default for the given telescope name 

983 if usedefaultvp==False, it will check whether vptable is set, and if so, 

984 load that table into the vpmanager and use the beams therein. 

985 if usedefaultvp==False and vptable is not set, it will use whatever is 

986 already set in the vpmanager (see example below for overriding a 

987 default telescope beam). 

988 

989 What sm.predict does with the obtained PB depends on the ftmachine and 

990 dovp parameters: 

991 

992 if ftmachine=='mosaic': 

993 - a message 'Performing Mosaic Gridding' indicates that one is using 

994 uv domain convolution for simulating from images. 

995 - if the primary beam returned by the vpmanager is ALMA, ACA, or OVRO, 

996 heterogeneous gridding will be invoked, and the dish diameter set 

997 in sm.setconfig, or already in the antenna subtable, will be used 

998 to convolve sky model images. 

999 for ALMA or ACA, dish diameter =12m will use a 10.7m Airy pattern, 

1000 and dish diameter =7m will use a 6.25m Airy pattern. 

1001 see help sm.setoptions for an example. 

1002 - otherwise the PB returned by the vpmanager will be used. 

1003 - heterogeneous simulation only works at present from a sky model 

1004 image, NOT from sky model components. If you want to simulate a 

1005 heterogeneous array, please add components to an image using 

1006 ia.modify, and don't specify a component list in sm.predict. 

1007 Homogeneous array simulation from component lists works fine. 

1008 - IF dovp=True, the primary beam returned by the vpmanager will 

1009 be used to convolve sky model components. This is not automatically 

1010 invoked by ftmachine='mosaic', but needs to be set explicitly with 

1011 sm.setvp() if you are simulating from components in addition to or 

1012 instead of sky model images. 

1013 

1014 if ftmachine=='ft' (the default): 

1015 - a message 'Synthesis Gridding' indicates that if requested with 

1016 dovp==True, image domain PB convolution will be used. 

1017 - if dovp==True, the primary beam returned by the vpmanager will be 

1018 used to convolve sky model components and images. 

1019 

1020 

1021 

1022 Input Parameters: 

1023 dovp Multiply by the voltage pattern (ie, primary beam) when simulating 

1024 usedefaultvp Look up the default VP for this telescope and frequency? 

1025 vptable If usedefaultvp is false, provide a VP Table made with vpmanager 

1026 dosquint Activate the beam squint in the VP model 

1027 parangleinc Parallactice angle increment for squint application 

1028 skyposthreshold Position threshold on the sky for feed arrays ??  

1029 pblimit Primary beam limit to use in feed arrays ?  

1030 

1031 Example: 

1032 

1033 # use the default primary beam in subsequent sm.predict (according to 

1034 # whatever telescope name was set in sm.setconfig) 

1035 sm.setvp(dovp=True, usedefaultvp=True) 

1036 sm.predict(imagename='point.ra10.image',complist='point.cl') 

1037 

1038 # use an alternate VP table e.g. of the format created by vpmanager: 

1039 sm.setvp(dovp=True, usedefaultvp=False, vptable='MyAlternateVLAPBModel.TAB', dosquint=F); 

1040 sm.predict(imagename='point.ra10.image',complist='point.cl') 

1041 

1042 # set a VP and then use it overridding the default 

1043 # (if telescope='NGVLA' was used previously in setconfig, 

1044 # or if an MS was loaded with observatory name = 'NGVLA') 

1045 vp.setpbairy(telescope='NGVLA',dishdiam='10m',maxrad='5deg') 

1046 sm.setvp(dovp=True,usedefaultvp=False) 

1047 sm.predict(imagename='point.ra10.image',complist='point.cl') 

1048 

1049 -------------------------------------------------------------------------------- 

1050 

1051 """ 

1052 return _simulator.simulator_setvp(self, *args, **kwargs) 

1053 

1054 

1055 def corrupt(self): 

1056 """ 

1057 corrupt(self) -> bool 

1058 

1059 

1060 

1061 Summary: 

1062 Corrupt the data with visibility errors 

1063 

1064 Description: 

1065 

1066 

1067 Add errors specified by the set* functions (such as noise, gains, 

1068 polarization leakage, bandpass, etc) to the visibility data. The 

1069 errors are applied to the DATA and CORRECTED_DATA columns. 

1070 

1071 Note that corrupt handles only 

1072 visibility-plane effects, not image-plane effects such as pointing 

1073 errors and voltage patterns, which get applied in predict. Note, the 

1074 function applies errors to both cross- and auto-correlation data; The 

1075 auto-correlation data are corrupted properly only for the thermalnoise 

1076 set by setnoise. 

1077 

1078 

1079 Example: 

1080 

1081 sm,openfromms('3C273XC1.MS'); 

1082 sm.predict('3C273XC1.FAKE.IMAGE'); 

1083 sm.setnoise( mode='simplenoise', simplenoise='0.1Jy'); 

1084 sm.setpa( mode='calculate'); 

1085 sm.corrupt(); 

1086 

1087 -------------------------------------------------------------------------------- 

1088 

1089 """ 

1090 return _simulator.simulator_corrupt(self) 

1091 

1092 

1093 def reset(self): 

1094 """ 

1095 reset(self) -> bool 

1096 

1097 

1098 

1099 Summary: 

1100 Reset the corruption terms 

1101 

1102 Description: 

1103 

1104 

1105 Reset the visibility corruption terms: this means that corrupt 

1106 introduces no errors. 

1107 

1108 

1109 -------------------------------------------------------------------------------- 

1110 

1111 """ 

1112 return _simulator.simulator_reset(self) 

1113 

1114 

1115 def setbandpass(self, *args, **kwargs): 

1116 """ 

1117 setbandpass(self, _mode, _table, _interval, _amplitude) -> bool 

1118 

1119 

1120 

1121 Summary: 

1122 Set the bandpasses 

1123 

1124 Description: 

1125 

1126 

1127 Set the level of bandpass errors. The error distributions are normal, mean 

1128 zero, with the variances as specified. (Not yet implemented). 

1129 

1130 

1131 Input Parameters: 

1132 mode Mode of operation. String: 'calculate'|'table' 

1133 table Name of table 

1134 interval Coherence interval e.g. '1h' 

1135 amplitude Variances errors in amplitude and phase 

1136 

1137 -------------------------------------------------------------------------------- 

1138 

1139 """ 

1140 return _simulator.simulator_setbandpass(self, *args, **kwargs) 

1141 

1142 

1143 def setapply(self, *args, **kwargs): 

1144 """ 

1145 setapply(self, _table, _type, _t, _field, _interp, _calwt, _spwmap, _opacity) -> bool 

1146 

1147 

1148 

1149 Summary: 

1150 Arrange for corruption by existing cal tables 

1151 

1152 Description: 

1153 

1154 

1155 Arrange for corruption by existing cal tables, in a manner 

1156 exactly analogous to calibrater.setapply. 

1157 

1158 

1159 Input Parameters: 

1160 table Calibration table name 

1161 type Component type 

1162 t Interpolation interval (seconds) 

1163 field Select on field 

1164 interp Interpolation type (in time) 

1165 calwt Calibrate weights? 

1166 spwmap Spectral windows to apply 

1167 opacity Array-wide zenith opacity (for type='TOPAC') 

1168 

1169 -------------------------------------------------------------------------------- 

1170 

1171 """ 

1172 return _simulator.simulator_setapply(self, *args, **kwargs) 

1173 

1174 

1175 def setgain(self, *args, **kwargs): 

1176 """ 

1177 setgain(self, _mode, _table, _interval, _amplitude) -> bool 

1178 

1179 

1180 

1181 Summary: 

1182 Set the gains 

1183 

1184 Description: 

1185 

1186 

1187 Set the level of gain errors. Gain drift is implemented as 

1188 fractional brownian motion with rms amplitude as specified. 

1189 Interval is not currently used. 

1190 

1191 

1192 

1193 Input Parameters: 

1194 mode Mode of operation. String: 'fbm' 

1195 table Optional name of table to write 

1196 interval timescale for gain variations NOT USED 

1197 amplitude amplitude scale (RMS) for gain variations [real,imag] or scalar 

1198 

1199 -------------------------------------------------------------------------------- 

1200 

1201 """ 

1202 return _simulator.simulator_setgain(self, *args, **kwargs) 

1203 

1204 

1205 def settrop(self, *args, **kwargs): 

1206 """ 

1207 settrop(self, _mode, _table, _pwv, _deltapwv, _beta, _windspeed, _simint) -> bool 

1208 

1209 

1210 

1211 Summary: 

1212 Set tropospheric gain corruptions 

1213 

1214 Description: 

1215 

1216 

1217 Set up for corruption by the atmosphere - attenuation and increase in 

1218 noise. 

1219 

1220 

1221 Input Parameters: 

1222 mode Mode of operation - screen or individual antennas 

1223 table Name of optional cal table to write 

1224 pwv total precipitable water vapour in mm 

1225 deltapwv RMS PWV fluctuations *as a fraction of PWV parameter* 

1226 beta exponent of fractional brownian motion 

1227 windspeed wind speed for screen type corruption (m/s) 

1228 simint simulation time step interval (s) 

1229 

1230 -------------------------------------------------------------------------------- 

1231 

1232 """ 

1233 return _simulator.simulator_settrop(self, *args, **kwargs) 

1234 

1235