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1import os 

2import sys 

3import shutil 

4import pprint as pp 

5import traceback 

6import time 

7import numpy as np 

8from matplotlib import pyplot as plt 

9 

10from casatasks import casalog 

11from casatools import table, ms, msmetadata 

12 

13import subprocess 

14 

15mst_local = ms() 

16tbt_local = table() 

17msmdt_local = msmetadata() 

18 

19class convertToMMS(): 

20 def __init__(self,\ 

21 inpdir=None, \ 

22 mmsdir=None, \ 

23 axis='auto', \ 

24 numsubms=4, 

25# createmslink=False, \ 

26 cleanup=False): 

27 

28 '''Run the partition task to create MMSs from a directory with MSs''' 

29 casalog.origin('convertToMMS') 

30 

31 self.inpdir = inpdir 

32 self.outdir = mmsdir 

33 self.axis = axis 

34 self.numsubms = numsubms 

35# self.createmslink = createmslink 

36 self.mmsdir = '/tmp/mmsdir' 

37 self.cleanup = cleanup 

38 

39 # Input directory is mandatory 

40 if self.inpdir is None: 

41 casalog.post('You must give an input directory to this script') 

42 self.usage() 

43 return 

44 

45 if not os.path.exists(self.inpdir): 

46 casalog.post('Input directory inpdir does not exist -> '+self.inpdir,'ERROR') 

47 self.usage() 

48 return 

49 

50 if not os.path.isdir(self.inpdir): 

51 casalog.post('Value of inpdir is not a directory -> '+self.inpdir,'ERROR') 

52 self.usage() 

53 return 

54 

55 

56 # Only work with absolute paths 

57 self.inpdir = os.path.abspath(self.inpdir) 

58 casalog.post('Will read input MS from '+self.inpdir) 

59 

60 # Verify output directory 

61 if self.outdir is None: 

62 self.mmsdir = os.path.join(os.getcwd(),'mmsdir') 

63 elif self.outdir == '/': 

64 casalog.post('inpdir is set to root!', 'WARN') 

65 self.mmsdir = os.path.join(os.getcwd(),'mmsdir') 

66 else: 

67 self.outdir = os.path.abspath(self.outdir) 

68 self.mmsdir = self.outdir 

69 

70 if self.mmsdir == self.inpdir: 

71 casalog.post('Output directory cannot be same of input directory','ERROR') 

72 return 

73 

74 # Cleanup output directory 

75 if self.cleanup: 

76 casalog.post('Cleaning up output directory '+self.mmsdir) 

77 if os.path.isdir(self.mmsdir): 

78 shutil.rmtree(self.mmsdir) 

79 

80 if not os.path.exists(self.mmsdir): 

81 os.makedirs(self.mmsdir) 

82 

83 

84 casalog.post('Will save output MMS to '+self.mmsdir) 

85 

86 # Walk through input directory 

87 files = os.walk(self.inpdir,followlinks=True).next() 

88 

89 # Get MS list 

90 mslist = [] 

91 mslist = self.getMSlist(files) 

92 

93 casalog.post('List of MSs in input directory') 

94 casalog.post(pp.pformat(mslist)) 

95 

96 # Get non-MS directories and other files 

97 nonmslist = [] 

98 nonmslist = self.getFileslist(files) 

99 

100 casalog.post('List of other files in input directory') 

101 casalog.post(pp.pformat(nonmslist)) 

102 

103 

104 # Create an MMS for each MS in list 

105 for ms in mslist: 

106 casalog.post('Will create an MMS for '+ms) 

107 ret = self.runPartition(ms, self.mmsdir, self.axis, self.numsubms) 

108 if not ret: 

109 sys.exit(2) 

110 

111 # Verify later if this is still needed 

112 time.sleep(10) 

113 

114 casalog.origin('convertToMMS') 

115 casalog.post('--------------- Successfully created MMS -----------------') 

116 

117 

118 # Copy non-MS files to MMS directory 

119 for nfile in nonmslist: 

120 bfile = os.path.basename(nfile) 

121 lfile = os.path.join(self.mmsdir, bfile) 

122 casalog.post('Copying non-MS file '+bfile) 

123# os.symlink(file, lfile) 

124# shutil.copytree(nfile, lfile, symlinks=False) 

125 os.system("cp -RL {0} {1}".format(nfile, lfile)) 

126 

127 

128 def getMSlist(self, files): 

129 '''Get a list of MSs from a directory. 

130 files -> a tuple that is returned by the following call: 

131 files = os.walk(self.inpdir,followlinks=True).next()  

132  

133 It will test if a directory is an MS and will only return 

134 true MSs, that have Type:Measurement Set in table.info. It will skip 

135 directories that start with . and those that do not end with 

136 extension .ms. 

137 ''' 

138 

139 topdir = files[0] 

140 mslist = [] 

141 

142 # Loop through list of directories 

143 for d in files[1]: 

144 # Skip . entries 

145 if d.startswith('.'): 

146 continue 

147 

148# if not d.endswith('.ms'): 

149# continue 

150 

151 # Full path for directory 

152 mydir = os.path.join(topdir,d) 

153 

154 # It is probably an MS 

155 if self.isItMS(mydir) == 1: 

156 mslist.append(mydir) 

157 

158 return mslist 

159 

160 def isItMS(self, mydir): 

161 '''Check the type of a directory. 

162 mydir --> full path of a directory. 

163 Returns 1 for an MS, 2 for a cal table and 3 for a MMS. 

164 If 0 is returned, it means any other type or an error.''' 

165 

166 ret = 0 

167 

168 # Listing of this directory 

169 ldir = os.listdir(mydir) 

170 

171 if not ldir.__contains__('table.info'): 

172 return ret 

173 

174 cmd1 = 'grep Type '+mydir+'/table.info' 

175 cmd2 = 'grep SubType '+mydir+'/table.info' 

176 mytype = subprocess.getoutput(cmd1).rstrip("\n") 

177 stype = subprocess.getoutput(cmd2).rstrip("\n") 

178 

179 # It is a cal table 

180 if mytype.__contains__('Calibration'): 

181 ret = 2 

182 

183 elif mytype.__contains__('Measurement'): 

184 # It is a Multi-MS 

185 if stype.__contains__('CONCATENATED'): 

186 # Further check 

187 if ldir.__contains__('SUBMSS'): 

188 ret = 3 

189 # It is an MS 

190 else: 

191 ret = 1 

192 

193 return ret 

194 

195 

196 def getFileslist(self, files): 

197 '''Get a list of non-MS files from a directory. 

198 files -> a tuple that is returned by the following call: 

199 files = os.walk(self.inpdir,followlinks=True).next()  

200  

201 It will return files and directories that are not MSs. It will skip 

202 files that start with . 

203 ''' 

204 

205 topdir = files[0] 

206 fileslist = [] 

207 

208 # Get other directories that are not MSs 

209 for d in files[1]: 

210 

211 # Skip . entries 

212 if d.startswith('.'): 

213 continue 

214 

215 # Skip MS directories 

216 if d.endswith('.ms'): 

217 continue 

218 

219 # Full path for directory 

220 mydir = os.path.join(topdir,d) 

221 

222 # It is not an MS 

223 if self.isItMS(mydir) != 1: 

224 fileslist.append(mydir) 

225 

226 

227 # Get non-directory files  

228 for f in files[2]: 

229 # Skip . entries 

230 if f.startswith('.'): 

231 continue 

232 

233 # Full path for file 

234 myfile = os.path.join(topdir, f) 

235 fileslist.append(myfile) 

236 

237 return fileslist 

238 

239 

240 def runPartition(self, ms, mmsdir, axis, subms): 

241 '''Run partition with default values to create an MMS. 

242 ms --> full pathname of the MS 

243 mmsdir --> directory to save the MMS to 

244 axis --> separationaxis to use (spw, scan, auto) 

245 subms --> number of subMss to create 

246 

247 ''' 

248 try: 

249 # CASA 6 

250 from casatasks import partition 

251 except ImportError: 

252 # CASA 5 

253 from tasks import partition 

254 

255 if not os.path.lexists(ms): 

256 return False 

257 

258 # Create MMS name 

259# bname = os.path.basename(ms) 

260# if bname.endswith('.ms'): 

261# mmsname = bname.replace('.ms','.mms') 

262# else: 

263# mmsname = bname+'.mms' 

264 

265 # Create MMS with the same name of the MS, but in a different location 

266 MSBaseName = os.path.basename(ms) 

267 MMSFullName = os.path.join(self.mmsdir, MSBaseName) 

268 if os.path.lexists(MMSFullName): 

269 casalog.post('Output MMS already exist -->'+MMSFullName,'ERROR') 

270 return False 

271 

272 casalog.post('Output MMS will be: '+MMSFullName) 

273 

274# mms = os.path.join(self.mmsdir, mmsname) 

275# if os.path.lexists(mms): 

276# casalog.post('Output MMS already exist -->'+mms,'ERROR') 

277# return False 

278 

279 # Check for remainings of corrupted mms 

280# corrupted = mms.replace('.mms','.data') 

281 corrupted = MMSFullName + '.data' 

282 if os.path.exists(corrupted): 

283 casalog.post('Cleaning up left overs','WARN') 

284 shutil.rmtree(corrupted) 

285 

286 # Run partition  

287 partition(vis=ms, outputvis=MMSFullName, createmms=True, datacolumn='all', flagbackup=False, 

288 separationaxis=axis, numsubms=subms) 

289 casalog.origin('convertToMMS') 

290 

291 # Check if MMS was created 

292 if not os.path.exists(MMSFullName): 

293 casalog.post('Cannot create MMS ->'+MMSFullName, 'ERROR') 

294 return False 

295 

296 # If requested, create a link to this MMS with the original MS name 

297# if createlink: 

298# here = os.getcwd() 

299# os.chdir(mmsdir) 

300# mmsname = os.path.basename(mms) 

301## lms = mmsname.replace('.mms', '.ms') 

302# casalog.post('Creating symbolic link to MMS') 

303## os.symlink(mmsname, lms) 

304# os.symlink(mmsname, bname) 

305# os.chdir(here) 

306 

307 return True 

308 

309 def usage(self): 

310 casalog.post('=========================================================================') 

311 casalog.post(' convertToMMS will create a directory with multi-MSs.') 

312 casalog.post('Usage:\n') 

313 casalog.post(' import partitionhelper as ph') 

314 casalog.post(' ph.convertToMMS(inpdir=\'dir\') \n') 

315 casalog.post('Options:') 

316 casalog.post(' inpdir <dir> directory with input MS.') 

317 casalog.post(' mmsdir <dir> directory to save output MMS. If not given, it will save ') 

318 casalog.post(' the MMS in a directory called mmsdir in the current directory.') 

319 casalog.post(" axis='auto' separationaxis parameter of partition (spw,scan,auto).") 

320 casalog.post(" numsubms=4 number of subMSs to create in output MMS") 

321 casalog.post(' cleanup=False if True it will remove the output directory before starting.\n') 

322 

323 casalog.post(' NOTE: this script will run using the default values of partition. It will try to ') 

324 casalog.post(' create an MMS for every MS in the input directory. It will skip non-MS directories ') 

325 casalog.post(' such as cal tables. If partition succeeds, the script will create a link to every ') 

326 casalog.post(' other directory or file in the output directory. ') 

327 casalog.post(' The script will not walk through sub-directories of inpdir. It will also skip ') 

328 casalog.post(' files or directories that start with a .') 

329 casalog.post('==========================================================================') 

330 return 

331 

332# 

333# -------------- HELPER functions for dealing with an MMS -------------- 

334# 

335# getMMSScans 'Get the list of scans of an MMS dictionary' 

336# getScanList 'Get the list of scans of an MS or MMS' 

337# getScanNrows 'Get the number of rows of a scan in a MS. It will add the  

338# nrows of all sub-scans.' 

339# getMMSScanNrows 'Get the number of rows of a scan in an MMS dictionary.' 

340# getSpwIds 'Get the Spw IDs of a scan.' 

341# getDiskUsage 'eturn the size in bytes of an MS in disk.' 

342# 

343# ---------------------------------------------------------------------- 

344 

345# def getNumberOf(msfile, item='row'): 

346# '''Using the msmd tool, it gets the number of 

347# scan, spw, antenna, baseline, field, state, 

348# channel, row in a MS or MMS''' 

349#  

350# md = msmdtool() # or msmd() in CASA 6 

351# try: 

352# md.open(msfile) 

353# except: 

354# casalog.post('Cannot open the msfile') 

355# return 0 

356#  

357# if item == 'row': 

358# numof = md.nrows() 

359# elif item == 'scan': 

360# numof = md.nscans() 

361# elif item == 'spw': 

362# numof = md.nspw() 

363# elif item == 'antenna': 

364# numof = md.nantennas() 

365# elif item == 'baseline': 

366# numof = md.nbaselines() 

367# elif item == 'channel': 

368# numof = md.nchan() 

369# elif item == 'field': 

370# numof = md.nfields() 

371# elif item == 'state': 

372# numof = md.nstates() 

373# else: 

374# numof = 0 

375#  

376# md.close() 

377# return numof 

378 

379 

380# NOTE 

381# There is a bug in ms.getscansummary() that does not give the scans for all  

382# observation Ids, but only for the last one. See CAS-4409 

383def getMMSScans(mmsdict): 

384 '''Get the list of scans of an MMS dictionary. 

385 mmsdict --> output dictionary from listpartition(MMS,createdict=true) 

386 Return a list of the scans in this MMS. ''' 

387 

388 if not isinstance(mmsdict, dict): 

389 casalog.post('ERROR: Input is not a dictionary', 'ERROR') 

390 return [] 

391 

392 tkeys = mmsdict.keys() 

393 scanlist = [] 

394 slist = set(scanlist) 

395 for k in tkeys: 

396 skeys = mmsdict[k]['scanId'].keys() 

397 for j in skeys: 

398 slist.add(j) 

399 

400 return list(slist) 

401 

402def getScanList(msfile, selection={}): 

403 '''Get the list of scans of an MS or MMS.  

404 msfile --> name of MS or MMS 

405 selection --> dictionary with data selection 

406  

407 Return a list of the scans in this MS/MMS. ''' 

408 

409 mst_local.open(msfile) 

410 if isinstance(selection, dict) and selection != {}: 

411 mst_local.msselect(items=selection) 

412 

413 scand = mst_local.getscansummary() 

414 mst_local.close() 

415 

416 scanlist = scand.keys() 

417 

418 return scanlist 

419 

420 

421def getScanNrows(msfile, myscan, selection={}): 

422 '''Get the number of rows of a scan in a MS. It will add the nrows of all sub-scans. 

423 This will not take into account any selection done on the MS. 

424 msfile --> name of the MS or MMS 

425 myscan --> scan ID (int) 

426 selection --> dictionary with data selection 

427  

428 Return the number of rows in the scan. 

429  

430 To compare with the dictionary returned by listpartition, do the following: 

431  

432 resdict = listpartition('file.mms', createdict=True) 

433 slist = ph.getMMSScans(thisdict) 

434 for s in slist: 

435 mmsN = ph.getMMSScanNrows(thisdict, s) 

436 msN = ph.getScanNrows('referenceMS', s) 

437 assert (mmsN == msN) 

438 ''' 

439 mst_local.open(msfile) 

440 if isinstance(selection, dict) and selection != {}: 

441 mst_local.msselect(items=selection) 

442 

443 scand = mst_local.getscansummary() 

444 mst_local.close() 

445 

446 Nrows = 0 

447 if not str(myscan) in scand: 

448 return Nrows 

449 

450 subscans = scand[str(myscan)] 

451 for ii in subscans.keys(): 

452 Nrows += scand[str(myscan)][ii]['nRow'] 

453 

454 return Nrows 

455 

456 

457def getMMSScanNrows(thisdict, myscan): 

458 '''Get the number of rows of a scan in an MMS dictionary. 

459 thisdict --> output dictionary from listpartition(MMS,createdict=true) 

460 myscan --> scan ID (int)  

461 Return the number of rows in the given scan. ''' 

462 

463 if not isinstance(thisdict, dict): 

464 casalog.post('ERROR: Input is not a dictionary', 'ERROR') 

465 return -1 

466 

467 tkeys = thisdict.keys() 

468 scanrows = 0 

469 for k in tkeys: 

470 if myscan in thisdict[k]['scanId']: 

471 scanrows += thisdict[k]['scanId'][myscan]['nrows'] 

472 

473 return scanrows 

474 

475 

476def getSpwIds(msfile, myscan, selection={}): 

477 '''Get the Spw IDs of a scan.  

478 msfile --> name of the MS or MMS 

479 myscan --> scan Id (int) 

480 selection --> dictionary with data selection 

481  

482 Return a list with the Spw IDs. Note that the returned spw IDs are sorted. 

483  

484 ''' 

485 import numpy as np 

486 

487 mst_local.open(msfile) 

488 if isinstance(selection, dict) and selection != {}: 

489 mst_local.msselect(items=selection) 

490 

491 scand = mst_local.getscansummary() 

492 mst_local.close() 

493 

494 spwlist = [] 

495 

496 if not str(myscan) in scand: 

497 return spwlist 

498 

499 subscans = scand[str(myscan)] 

500 aspws = np.array([],dtype=int) 

501 

502 for ii in subscans.keys(): 

503 sscanid = ii 

504 spwids = scand[str(myscan)][sscanid]['SpwIds'] 

505 aspws = np.append(aspws,spwids) 

506 

507 # Sort spws and remove duplicates 

508 aspws.sort() 

509 uniquespws = np.unique(aspws) 

510 

511 # Try to return a list 

512 spwlist = uniquespws.ravel().tolist() 

513 return spwlist 

514 

515 

516def getScanSpwSummary(mslist=[]): 

517 """ Get a consolidated dictionary with scan, spw, channel information 

518 of a list of MSs. It adds the nrows of all sub-scans of a scan. 

519  

520 Keyword arguments: 

521 mslist --> list with names of MSs 

522  

523 Returns a dictionary such as: 

524 mylist=['subms1.ms','subms2.ms'] 

525 outdict = getScanSpwSummary(mylist) 

526 outdict = {0: {'MS': 'subms1.ms', 

527 'scanId': {30: {'nchans': array([64, 64]), 

528 'nrows': 544, 

529 'spwIds': array([ 0, 1])}}, 

530 'size': '214M'}, 

531 1: {'MS': 'ngc5921.ms', 

532 'scanId': {1: {'nchans': array([63]), 

533 'nrows': 4509, 

534 'spwIds': array([0])}, 

535 2: {'nchans': array([63]), 

536 'nrows': 1890, 

537 'spwIds': array([0])}}, 

538 'size': '72M'}} 

539 """ 

540 

541 if mslist == []: 

542 return {} 

543 

544 # Create lists for scan and spw dictionaries of each MS 

545 msscanlist = [] 

546 msspwlist = [] 

547 

548 # List with sizes in bytes per sub-MS 

549 sizelist = [] 

550 

551 # Loop through all MSs 

552 for subms in mslist: 

553 try: 

554 mst_local.open(subms) 

555 scans = mst_local.getscansummary() 

556 msscanlist.append(scans) 

557 spws = mst_local.getspectralwindowinfo() 

558 msspwlist.append(spws) 

559 except Exception as exc: 

560 raise Exception('Cannot get scan/spw information from subMS: {0}'.format(exc)) 

561 finally: 

562 mst_local.close() 

563 

564 # Get the data volume in bytes per sub-MS 

565 sizelist.append(getDiskUsage(subms)) 

566 

567 # Get the information to list in output 

568 # Dictionary to return 

569 outdict = {} 

570 

571 for ims in range(mslist.__len__()): 

572 # Create temp dictionary for each sub-MS 

573 tempdict = {} 

574 msname = os.path.basename(mslist[ims]) 

575 tempdict['MS'] = msname 

576 tempdict['size'] = sizelist[ims] 

577 

578 # Get scan dictionary for this sub-MS 

579 scandict = msscanlist[ims] 

580 

581 # Get spw dictionary for this sub-MS 

582 # NOTE: the keys of spwdict.keys() are NOT the spw Ids 

583 spwdict = msspwlist[ims] 

584 

585 # The keys are the scan numbers 

586 scanlist = scandict.keys() 

587 

588 # Get information per scan 

589 tempdict['scanId'] = {} 

590 for scan in scanlist: 

591 newscandict = {} 

592 subscanlist = scandict[scan].keys() 

593 

594 # Get spws and nrows per sub-scan 

595 nrows = 0 

596 aspws = np.array([],dtype='int32') 

597 for subscan in subscanlist: 

598 nrows += scandict[scan][subscan]['nRow'] 

599 

600 # Get the spws for each sub-scan 

601 spwids = scandict[scan][subscan]['SpwIds'] 

602 aspws = np.append(aspws,spwids) 

603 

604 newscandict['nrows'] = nrows 

605 

606 # Sort spws and remove duplicates 

607 aspws.sort() 

608 uniquespws = np.unique(aspws) 

609 newscandict['spwIds'] = uniquespws 

610 

611 # Array to hold channels 

612 charray = np.empty_like(uniquespws) 

613 spwsize = np.size(uniquespws) 

614 

615 # Now get the number of channels per spw 

616 for ind in range(spwsize): 

617 spwid = uniquespws[ind] 

618 for sid in spwdict.keys(): 

619 if spwdict[sid]['SpectralWindowId'] == spwid: 

620 nchans = spwdict[sid]['NumChan'] 

621 charray[ind] = nchans 

622 continue 

623 

624 newscandict['nchans'] = charray 

625 tempdict['scanId'][int(scan)] = newscandict 

626 

627 

628 outdict[ims] = tempdict 

629 #casalog.post(pp.format(outdict)) 

630 

631 return outdict 

632 

633 

634def getMMSSpwIds(thisdict): 

635 '''Get the list of spws from an MMS dictionary. 

636 thisdict --> output dictionary from listpartition(MMS,createdict=true) 

637 Return a list of the spw Ids in the dictionary. ''' 

638 

639 import numpy as np 

640 

641 if not isinstance(thisdict, dict): 

642 casalog.post('ERROR: Input is not a dictionary', 'ERROR') 

643 return [] 

644 

645 tkeys = thisdict.keys() 

646 

647 aspws = np.array([],dtype='int32') 

648 for k in tkeys: 

649 scanlist = thisdict[k]['scanId'].keys() 

650 for s in scanlist: 

651 spwids = thisdict[k]['scanId'][s]['spwIds'] 

652 aspws = np.append(aspws, spwids) 

653 

654 # Sort spws and remove duplicates 

655 aspws.sort() 

656 uniquespws = np.unique(aspws) 

657 

658 # Try to return a list 

659 spwlist = uniquespws.ravel().tolist() 

660 

661 return spwlist 

662 

663def getSubMSSpwIds(subms, thisdict): 

664 

665 import numpy as np 

666 tkeys = thisdict.keys() 

667 aspws = np.array([],dtype='int32') 

668 mysubms = os.path.basename(subms) 

669 for k in tkeys: 

670 if thisdict[k]['MS'] == mysubms: 

671 # get the spwIds of this subMS 

672 scanlist = thisdict[k]['scanId'].keys() 

673 for s in scanlist: 

674 spwids = thisdict[k]['scanId'][s]['spwIds'] 

675 aspws = np.append(aspws, spwids) 

676 break 

677 

678 # Sort spws and remove duplicates 

679 aspws.sort() 

680 uniquespws = np.unique(aspws) 

681 

682 # Try to return a list 

683 spwlist = uniquespws.ravel().tolist() 

684 return spwlist 

685 

686def getDiskUsage(msfile): 

687 """Return the size in bytes of an MS or MMS in disk. 

688  

689 Keyword arguments: 

690 msfile --> name of the MS 

691 This function will return a value given by the command du -hs 

692 """ 

693 

694 from subprocess import Popen, PIPE, STDOUT 

695 

696 # Command line to run 

697 ducmd = 'du -hs {0}'.format(msfile) 

698 

699 p = Popen(ducmd, shell=True, stdin=None, stdout=PIPE, stderr=STDOUT, close_fds=True) 

700 o, e = p.communicate() ### previously 'sizeline = p.stdout.read()' here 

701 ### left process running... 

702 sizeline = o.decode( ).split( )[0] 

703 

704 # Create a list of the output string, which looks like this: 

705 # ' 75M\tuidScan23.data/uidScan23.0000.ms\n' 

706 # This will create a list with [size,sub-ms] 

707 mssize = sizeline.split() 

708 

709 return mssize[0] 

710 

711 

712def getSubtables(vis): 

713 theSubTables = [] 

714 tbt_local.open(vis) 

715 myKeyw = tbt_local.getkeywords() 

716 tbt_local.close() 

717 for k in myKeyw.keys(): 

718 theKeyw = myKeyw[k] 

719 if (type(theKeyw)==str and theKeyw.split(' ')[0]=='Table:' 

720 and not k=='SORTED_TABLE'): 

721 theSubTables.append(os.path.basename(theKeyw.split(' ')[1])) 

722 

723 return theSubTables 

724 

725 

726def makeMMS(outputvis, submslist, copysubtables=False, omitsubtables=[], parallelaxis=''): 

727 """Create a Multi-MS from a list of MSs 

728  

729 Keyword arguments: 

730 outputvis -- name of the output MMS 

731 submslist -- list of input subMSs to create the output from 

732 copysubtables -- True will copy the sub-tables from the first subMS to the others in the 

733 output MMS. Default to False. 

734 omitsubtables -- List of sub-tables to omit when copying to output MMS. They will be linked instead 

735 parallelasxis -- Optionally, set the value to be written to AxisType in table.info of the output MMS 

736 Usually this value comes from the separationaxis keyword of partition or mstransform. 

737  

738 Be AWARE that this function will remove the tables listed in submslist. 

739 """ 

740 

741 if os.path.exists(outputvis): 

742 raise ValueError('Output MS already exists') 

743 

744 if len(submslist)==0: 

745 raise ValueError('No SubMSs given') 

746 

747 ## make an MMS with all sub-MSs contained in a SUBMSS subdirectory 

748 origpath = os.getcwd() 

749 

750 try: 

751 try: 

752 mst_local.createmultims(outputvis, 

753 submslist, 

754 [], 

755 True, # nomodify 

756 False, # lock 

757 copysubtables, 

758 omitsubtables 

759 ) # when copying the subtables, omit these 

760 

761 except Exception: 

762 raise 

763 finally: 

764 mst_local.close() 

765 

766 # remove the SORTED_TABLE keywords because the sorting is not reliable after partitioning 

767 try: 

768 tbt_local.open(outputvis, nomodify=False) 

769 if 'SORTED_TABLE' in tbt_local.keywordnames(): 

770 tbt_local.removekeyword('SORTED_TABLE') 

771 tbt_local.close() 

772 

773 for thesubms in submslist: 

774 tbt_local.open(outputvis+'/SUBMSS/'+os.path.basename(thesubms), nomodify=False) 

775 if 'SORTED_TABLE' in tbt_local.keywordnames(): 

776 tobedel = tbt_local.getkeyword('SORTED_TABLE').split(' ')[1] 

777 tbt_local.removekeyword('SORTED_TABLE') 

778 os.system('rm -rf '+tobedel) 

779 tbt_local.close() 

780 except Exception: 

781 tbt_local.close() 

782 raise 

783 

784 # Create symbolic links to the subtables of the first SubMS in the reference MS (top one) 

785 os.chdir(outputvis) 

786 mastersubms = os.path.basename(submslist[0].rstrip('/')) 

787 thesubtables = getSubtables('SUBMSS/'+mastersubms) 

788 

789 for s in thesubtables: 

790 os.symlink('SUBMSS/'+mastersubms+'/'+s, s) 

791 

792 os.chdir('SUBMSS/'+mastersubms) 

793 

794 # Remove the SOURCE and HISTORY tables, which should not be linked 

795 thesubtables.remove('SOURCE') 

796 thesubtables.remove('HISTORY') 

797 

798 # Create sym links to all sub-tables in all subMSs 

799 for i in range(1,len(submslist)): 

800 thesubms = os.path.basename(submslist[i].rstrip('/')) 

801 os.chdir('../'+thesubms) 

802 

803 for s in thesubtables: 

804 os.system('rm -rf '+s) 

805 os.symlink('../'+mastersubms+'/'+s, s) 

806 

807 # Write the AxisType info in the MMS 

808 if parallelaxis != '': 

809 setAxisType(outputvis, parallelaxis) 

810 

811 except Exception as exc: 

812 os.chdir(origpath) 

813 raise ValueError('Problem in MMS creation: {0}'.format(exc)) 

814 

815 os.chdir(origpath) 

816 

817 return True 

818 

819def axisType(mmsname): 

820 """Get the axisType information from a Multi-MS. The AxisType information 

821 is usually added for Multi-MS with the axis which data is parallelized across. 

822  

823 Keyword arguments: 

824 mmsname -- name of the Multi-MS 

825 

826 It returns the value of AxisType or an empty string if it doesn't exist. 

827 """ 

828 

829 axis = '' 

830 

831 try: 

832 tbt_local.open(mmsname, nomodify=True) 

833 tbinfo = tbt_local.info() 

834 except Exception as exc: 

835 raise ValueError('Unable to open table {0}. Exception: {1}'.format(mmsname, exc)) 

836 finally: 

837 tbt_local.close() 

838 

839 if 'readme' in tbinfo: 

840 readme = tbinfo['readme'] 

841 readlist = readme.splitlines() 

842 for val in readlist: 

843 if val.__contains__('AxisType'): 

844 a,b,axis = val.partition('=') 

845 

846 return axis.strip() 

847 

848def setAxisType(mmsname, axis=''): 

849 """Set the AxisType keyword in a Multi-MS info. If AxisType already 

850 exists, it will be overwritten. 

851  

852 Keyword arguments: 

853 mmsname -- name of the Multi-MS 

854 axis -- parallel axis of the Multi-MS. Options: scan; spw or scan,spw 

855  

856 Return True on success, False otherwise. 

857 """ 

858 

859 import copy 

860 

861 if axis == '': 

862 raise ValueError('Axis value cannot be empty') 

863 

864 try: 

865 tbt_local.open(mmsname) 

866 tbinfo = tbt_local.info() 

867 except Exception as exc: 

868 raise ValueError('Unable to open table {0}. Exception: {1}'.format(mmsname, exc)) 

869 finally: 

870 tbt_local.close() 

871 

872 readme = '' 

873 # Save original readme 

874 if 'readme' in tbinfo: 

875 readme = tbinfo['readme'] 

876 

877 # Check if AxisType already exist and remove it 

878 if axisType(mmsname) != '': 

879 casalog.post('WARN: Will overwrite the existing AxisType value', 'WARN') 

880 readlist = readme.splitlines() 

881 newlist = copy.deepcopy(readlist) 

882 for val in newlist: 

883 if val.__contains__('AxisType'): 

884 readlist.remove(val) 

885 

886 # Recreate the string 

887 nr = '' 

888 for val in readlist: 

889 nr = nr + val + '\n' 

890 

891 readme = nr.rstrip() 

892 

893 

894 # Preset for axis info 

895 axisInfo = "AxisType = " 

896 axis.rstrip() 

897 axisInfo = axisInfo + axis + '\n' 

898 

899 # New readme 

900 newReadme = axisInfo + readme 

901 

902 # Create readme record 

903 readmerec = {'readme':newReadme} 

904 

905 try: 

906 tbt_local.open(mmsname, nomodify=False) 

907 tbt_local.putinfo(readmerec) 

908 except Exception as exc: 

909 raise ValueError('Unable to put readme info into table {0}. Exception: {1}'. 

910 format(mmsname, exc)) 

911 finally: 

912 tbt_local.close() 

913 

914 # Check if the axis was correctly added 

915 check_axis = axisType(mmsname) 

916 

917 if check_axis != axis: 

918 return False 

919 

920 return True 

921 

922def buildScanDDIMap(scanSummary, ddIspectralWindowInfo): 

923 """ 

924 Builds a scan->DDI map and 3 list of # visibilities per DDI, scan, field 

925 

926 :param scanSummary: scan summary dictionary as produced by the mstool (getscansummary) 

927 :param ddiSpectralWindowInfo: SPW info dictionary as produced by the mstool 

928 (getspectralwindowinfo()) 

929 :returns: a dict with a scan->ddi map, and three dict with # of visibilities per 

930 ddi, scan, and field. 

931 """ 

932 # Make an array for total number of visibilites per ddi and scan separatelly 

933 nVisPerDDI = {} 

934 nVisPerScan = {} 

935 nVisPerField = {} 

936 

937 # Iterate over scan list 

938 scanDdiMap = {} 

939 for scan in sorted(scanSummary): 

940 # Initialize scan sub-map 

941 scanDdiMap[scan] = {} 

942 # Iterate over timestamps for this scan 

943 for timestamp in scanSummary[scan]: 

944 # Get list of ddis for this timestamp 

945 DDIds = scanSummary[scan][timestamp]['DDIds'] 

946 fieldId = str(scanSummary[scan][timestamp]['FieldId']) 

947 # Get number of rows per ddi (assume all DDIs have the same number of rows) 

948 # In ALMA data WVR DDI has only one row per antenna but it is separated from the other DDIs 

949 nrowsPerDDI = scanSummary[scan][timestamp]['nRow'] / len(DDIds) 

950 # Iterate over DDIs for this timestamp 

951 for ddi in DDIds: 

952 # Convert to string to be used as a map key 

953 ddi = str(ddi) 

954 # Check if DDI entry is already present for this scan, otherwise initialize it 

955 if ddi not in scanDdiMap[scan]: 

956 scanDdiMap[scan][ddi] = {} 

957 scanDdiMap[scan][ddi]['nVis'] = 0 

958 scanDdiMap[scan][ddi]['fieldId'] = fieldId 

959 scanDdiMap[scan][ddi]['isWVR'] = ddIspectralWindowInfo[ddi]['isWVR'] 

960 # Calculate number of visibilities 

961 nvis = nrowsPerDDI*ddIspectralWindowInfo[ddi]['NumChan']*ddIspectralWindowInfo[ddi]['NumCorr'] 

962 # Add number of rows and vis from this timestamp 

963 scanDdiMap[scan][ddi]['nVis'] = scanDdiMap[scan][ddi]['nVis'] + nvis 

964 # Update ddi nvis 

965 if ddi not in nVisPerDDI: 

966 nVisPerDDI[ddi] = nvis 

967 else: 

968 nVisPerDDI[ddi] = nVisPerDDI[ddi] + nvis 

969 # Update scan nvis 

970 if scan not in nVisPerScan: 

971 nVisPerScan[scan] = nvis 

972 else: 

973 nVisPerScan[scan] = nVisPerScan[scan] + nvis 

974 # Update field nvis 

975 if fieldId not in nVisPerField: 

976 nVisPerField[fieldId] = nvis 

977 else: 

978 nVisPerField[fieldId] = nVisPerField[fieldId] + nvis 

979 

980 return scanDdiMap, nVisPerDDI, nVisPerScan, nVisPerField 

981 

982def getPartitionMap(msfilename, nsubms, selection={}, axis=['field','spw','scan'],plotMode=0): 

983 """Generates a partition scan/spw map to obtain optimal load balancing with the following criteria: 

984 

985 1st - Maximize the scan/spw/field distribution across sub-MSs 

986 2nd - Generate sub-MSs with similar size 

987 

988 In order to balance better the size of the subMSs the allocation process 

989 iterates over the scan,spw pairs in descending number of visibilities. 

990 

991 That is larger chunks are allocated first, and smaller chunks at the final 

992 stages so that they can be used to balance the load in a stable way 

993 

994 Keyword arguments: 

995 msname -- Input MS filename 

996 nsubms -- Number of subMSs 

997 selection -- Data selection dictionary 

998 axis -- Vector of strings containing the axis for load distribution (scan,spw,field) 

999 plotMode -- Integer in the range 0-3 to determine the plot generation mode 

1000 0 - Don't generate any plots 

1001 1 - Show plots but don't save them 

1002 2 - Save plots but don't show them 

1003 3 - Show and save plots 

1004 

1005 Returns a map of the sub-MSs with the corresponding scan/spw selections and the number of visibilities 

1006 """ 

1007 

1008 # Open ms tool 

1009 mst_local.open(msfilename) 

1010 

1011 # Apply data selection 

1012 if isinstance(selection, dict) and selection != {}: 

1013 mst_local.msselect(items=selection) 

1014 

1015 # Get list of DDIs and timestamps per scan 

1016 scanSummary = mst_local.getscansummary() 

1017 ddIspectralWindowInfo = mst_local.getspectralwindowinfo() 

1018 

1019 # Close ms tool 

1020 mst_local.close() 

1021 

1022 # Get list of WVR SPWs using the ms metadata tool 

1023 msmdt_local.open(msfilename) 

1024 wvrspws = msmdt_local.wvrspws() 

1025 msmdt_local.close() 

1026 

1027 # Mark WVR DDIs as identified by the ms metadata tool 

1028 for ddi in ddIspectralWindowInfo: 

1029 if ddIspectralWindowInfo[ddi] in wvrspws: 

1030 ddIspectralWindowInfo[ddi]['isWVR'] = True 

1031 else: 

1032 ddIspectralWindowInfo[ddi]['isWVR'] = False 

1033 

1034 scanDdiMap, nVisPerDDI, nVisPerScan, nVisPerField = buildScanDDIMap(scanSummary, 

1035 ddIspectralWindowInfo) 

1036 

1037 # Sort the scan/ddi pairs depending on the number of visibilities 

1038 ddiList = list() 

1039 scanList = list() 

1040 fieldList = list() 

1041 nVisList = list() 

1042 nScanDDIPairs = 0 

1043 for scan in scanDdiMap: 

1044 for ddi in scanDdiMap[scan]: 

1045 ddiList.append(ddi) 

1046 scanList.append(scan) 

1047 fieldList.append(scanDdiMap[scan][ddi]['fieldId']) 

1048 nVisList.append(scanDdiMap[scan][ddi]['nVis']) 

1049 nScanDDIPairs += 1 

1050 

1051 

1052 # Check that the number of available scan/ddi pairs is not greater than the number of subMSs 

1053 if nsubms > nScanDDIPairs: 

1054 casalog.post("Number of subMSs (%i) is greater than available scan,ddi pairs (%i), setting nsubms to %i" 

1055 % (nsubms,nScanDDIPairs,nScanDDIPairs),"WARN","getPartitionMap") 

1056 nsubms = nScanDDIPairs 

1057 

1058 ddiArray = np.array(ddiList) 

1059 scanArray = np.array(scanList) 

1060 nVisArray = np.array(nVisList) 

1061 

1062 nVisSortIndex = np.lexsort((ddiArray, scanArray, nVisArray)) 

1063 # argsort/lexsort return indices by increasing value. This reverses the indices by 

1064 # decreasing value 

1065 nVisSortIndex[:] = nVisSortIndex[::-1] 

1066 

1067 ddiArray = ddiArray[nVisSortIndex] 

1068 scanArray = scanArray[nVisSortIndex] 

1069 nVisArray = nVisArray[nVisSortIndex] 

1070 

1071 # Make a map for the contribution of each subMS to each scan 

1072 scanNvisDistributionPerSubMs = {} 

1073 for scan in scanSummary: 

1074 scanNvisDistributionPerSubMs[scan] = np.zeros(nsubms) 

1075 

1076 

1077 # Make a map for the contribution of each subMS to each ddi  

1078 ddiNvisDistributionPerSubMs = {} 

1079 for ddi in ddIspectralWindowInfo: 

1080 ddiNvisDistributionPerSubMs[ddi] = np.zeros(nsubms) 

1081 

1082 

1083 # Make a map for the contribution of each subMS to each field  

1084 fieldList = np.unique(fieldList) 

1085 fieldNvisDistributionPerSubMs = {} 

1086 for field in fieldList: 

1087 fieldNvisDistributionPerSubMs[field] = np.zeros(nsubms) 

1088 

1089 

1090 # Make an array for total number of visibilites per subms 

1091 nvisPerSubMs = np.zeros(nsubms) 

1092 

1093 

1094 # Initialize final map of scans/pw pairs per subms 

1095 submScanDdiMap = {} 

1096 for subms in range (0,nsubms): 

1097 submScanDdiMap[subms] = {} 

1098 submScanDdiMap[subms]['scanList'] = list() 

1099 submScanDdiMap[subms]['ddiList'] = list() 

1100 submScanDdiMap[subms]['fieldList'] = list() 

1101 submScanDdiMap[subms]['nVisList'] = list() 

1102 submScanDdiMap[subms]['nVisTotal'] = 0 

1103 

1104 

1105 # Iterate over the scan/ddi map and assign each pair to a subMS 

1106 for pair in range(len(ddiArray)): 

1107 

1108 ddi = ddiArray[pair] 

1109 scan = scanArray[pair] 

1110 field = scanDdiMap[scan][ddi]['fieldId'] 

1111 

1112 # Select the subMS that with bigger (scan/ddi/field gap) 

1113 # We use the average as a refLevel to include global structure information 

1114 # But we also take into account the actual max value in case we are distributing large uneven chunks 

1115 jointNvisGap = np.zeros(nsubms) 

1116 if 'scan' in axis: 

1117 refLevel = max(nVisPerScan[scan] // 

1118 nsubms,scanNvisDistributionPerSubMs[scan].max()) 

1119 jointNvisGap = jointNvisGap + refLevel - scanNvisDistributionPerSubMs[scan] 

1120 if 'spw' in axis: 

1121 refLevel = max(nVisPerDDI[ddi] // 

1122 nsubms,ddiNvisDistributionPerSubMs[ddi].max()) 

1123 jointNvisGap = jointNvisGap + refLevel - ddiNvisDistributionPerSubMs[ddi] 

1124 if 'field' in axis: 

1125 refLevel = max(nVisPerField[field] // 

1126 nsubms,fieldNvisDistributionPerSubMs[field].max()) 

1127 jointNvisGap = jointNvisGap + refLevel - fieldNvisDistributionPerSubMs[field] 

1128 

1129 optimalSubMs = np.where(jointNvisGap == jointNvisGap.max()) 

1130 optimalSubMs = optimalSubMs[0] # np.where returns a tuple 

1131 

1132 # In case of multiple candidates select the subms with minum number of total visibilities 

1133 if len(optimalSubMs) > 1: 

1134 subIdx = np.argmin(nvisPerSubMs[optimalSubMs]) 

1135 optimalSubMs = optimalSubMs[subIdx] 

1136 else: 

1137 optimalSubMs = optimalSubMs[0] 

1138 

1139 # Store the scan/ddi pair info in the selected optimal subms 

1140 nVis = scanDdiMap[scan][ddi]['nVis'] 

1141 nvisPerSubMs[optimalSubMs] = nvisPerSubMs[optimalSubMs] + nVis 

1142 submScanDdiMap[optimalSubMs]['scanList'].append(int(scan)) 

1143 submScanDdiMap[optimalSubMs]['ddiList'].append(int(ddi)) 

1144 submScanDdiMap[optimalSubMs]['fieldList'].append(field) 

1145 submScanDdiMap[optimalSubMs]['nVisList'].append(nVis) 

1146 submScanDdiMap[optimalSubMs]['nVisTotal'] = submScanDdiMap[optimalSubMs]['nVisTotal'] + nVis 

1147 

1148 # Also update the counters for the subms-scan and subms-ddi maps  

1149 scanNvisDistributionPerSubMs[scan][optimalSubMs] = scanNvisDistributionPerSubMs[scan][optimalSubMs] + nVis 

1150 ddiNvisDistributionPerSubMs[ddi][optimalSubMs] = ddiNvisDistributionPerSubMs[ddi][optimalSubMs] + nVis 

1151 fieldNvisDistributionPerSubMs[field][optimalSubMs] = fieldNvisDistributionPerSubMs[field][optimalSubMs] + nVis 

1152 

1153 

1154 # Generate plots 

1155 if plotMode > 0: 

1156 plt.close() 

1157 plotname_prefix = os.path.basename(msfilename) + ' axis ' + string.join(axis) 

1158 plotVisDistribution(nVisPerScan,scanNvisDistributionPerSubMs,plotname_prefix,'scan',plotMode=plotMode) 

1159 plotVisDistribution(nVisPerDDI,ddiNvisDistributionPerSubMs,plotname_prefix,'ddi',plotMode=plotMode) 

1160 plotVisDistribution(nVisPerField,fieldNvisDistributionPerSubMs,plotname_prefix,'field',plotMode=plotMode) 

1161 

1162 

1163 # Generate list of taql commands 

1164 for subms in submScanDdiMap: 

1165 # Initialize taql command 

1166 from collections import defaultdict 

1167 dmytaql = defaultdict(list) 

1168 

1169 for pair in range(len(submScanDdiMap[subms]['scanList'])): 

1170 # Get scan/ddi for this pair 

1171 ddi = submScanDdiMap[subms]['ddiList'][pair] 

1172 scan = submScanDdiMap[subms]['scanList'][pair] 

1173 dmytaql[ddi].append(scan) 

1174 

1175 mytaql = [] 

1176 for ddi, scans in dmytaql.items(): 

1177 scansel = '[' + ', '.join([str(x) for x in scans]) + ']' 

1178 mytaql.append(('(DATA_DESC_ID==%i && (SCAN_NUMBER IN %s))') % (ddi, scansel)) 

1179 

1180 mytaql = ' OR '.join(mytaql) 

1181 

1182 # Store taql 

1183 submScanDdiMap[subms]['taql'] = mytaql 

1184 

1185 

1186 # Return map of scan/ddi pairs per subMs 

1187 return submScanDdiMap 

1188 

1189 

1190def plotVisDistribution(nvisMap,idNvisDistributionPerSubMs,filename,idLabel,plotMode=1): 

1191 """Generates a plot to show the distribution of scans/wp across subMs. 

1192 The plot style is a stacked bar char, where the spw/scans with higher number of visibilities are shown at the bottom 

1193  

1194 Keyword arguments: 

1195 nvisMap -- Map of total numbe of visibilities per Id 

1196 idNvisDistributionPerSubMs -- Map of visibilities per subMS for each Id 

1197 filename -- Name of MS to be shown in the title and plot filename 

1198 idLabel -- idLabel to indicate the id (spw, scan) to be used for the figure title 

1199 plotMode -- Integer in the range 0-3 to determine the plot generation mode 

1200 0 - Don't generate any plots 

1201 1 - Show plots but don't save them 

1202 2 - Save plots but don't show them 

1203 2 - Show and save plots 

1204 """ 

1205 

1206 # Create a new figure 

1207 plt.ioff() 

1208 

1209 

1210 # If plot is not to be shown then use pre-define sized figure to 1585x1170 pizels with 75 DPI 

1211 # (we cannot maximize the window to the screen size) 

1212 if plotMode==2: 

1213 plt.figure(figsize=(21.13,15.6),dpi=75) # Size is given in inches 

1214 else: 

1215 plt.figure() 

1216 

1217 

1218 # Sort the id according to the total number of visibilities to that we can 

1219 # represent bigger the groups at the bottom and the smaller ones at the top 

1220 idx = 0 

1221 idArray = np.zeros(len(nvisMap)) 

1222 idNvisArray = np.zeros(len(nvisMap)) 

1223 for id in nvisMap: 

1224 idArray[idx] = int(id) 

1225 idNvisArray[idx] = nvisMap[id] 

1226 idx = idx + 1 

1227 

1228 idArraySortIndex = np.argsort(idNvisArray) 

1229 idArraySortIndex[:] = idArraySortIndex[::-1] 

1230 idArraySorted = idArray[idArraySortIndex] 

1231 

1232 

1233 # Initialize color vector to alternate cold/warm colors 

1234 nid = len(nvisMap) 

1235 colorVector = list() 

1236 colorRange = range(nid) 

1237 colorVectorEven = colorRange[::2] 

1238 colorVectorOdd = colorRange[1::2] 

1239 colorVectorOdd.reverse() 

1240 while len(colorVectorOdd) > 0 or len(colorVectorEven) > 0: 

1241 if len(colorVectorOdd) > 0: colorVector.append(colorVectorOdd.pop()) 

1242 if len(colorVectorEven) > 0: colorVector.append(colorVectorEven.pop()) 

1243 

1244 

1245 # Generate stacked bar plot 

1246 coloridx = 0 # color index 

1247 width = 0.35 # bar width 

1248 nsubms = len(idNvisDistributionPerSubMs[idNvisDistributionPerSubMs.keys()[0]]) 

1249 idx = np.arange(nsubms) # location of the bar centers in the horizontal axis 

1250 bottomLevel = np.zeros(nsubms) # Reference level for the bars to be stacked after the previous ones 

1251 legendidLabels = list() # List of legend idLabels 

1252 plotHandles=list() # List of plot handles for the legend 

1253 for id in idArraySorted: 

1254 

1255 id = str(int(id)) 

1256 

1257 idplot = plt.bar(idx, idNvisDistributionPerSubMs[id], width, bottom=bottomLevel, color=plt.cm.Paired(1.*colorVector[coloridx]/nid)) 

1258 

1259 # Update color index  

1260 coloridx = coloridx + 1 

1261 

1262 # Update legend lists 

1263 plotHandles.append(idplot) 

1264 legendidLabels.append(idLabel + ' ' + id) 

1265 

1266 # Update reference level 

1267 bottomLevel = bottomLevel + idNvisDistributionPerSubMs[id] 

1268 

1269 

1270 # Add legend 

1271 plt.legend( plotHandles, legendidLabels, bbox_to_anchor=(1.01, 1), loc=2, borderaxespad=0.) 

1272 

1273 

1274 # AQdd lable for y axis 

1275 plt.ylabel('nVis') 

1276 

1277 

1278 # Add x-ticks  

1279 xticks = list() 

1280 for subms in range(0,nsubms): 

1281 xticks.append('subMS-' + str(subms)) 

1282 plt.xticks(idx+width/2., xticks ) 

1283 

1284 

1285 # Add title 

1286 title = filename + ' distribution of ' + idLabel + ' visibilities across sub-MSs' 

1287 plt.title(title) 

1288 

1289 

1290 # Resize to full screen 

1291 if plotMode==1 or plotMode==3: 

1292 mng = plt.get_current_fig_manager() 

1293 mng.resize(*mng.window.maxsize()) 

1294 

1295 

1296 # Show figure 

1297 if plotMode==1 or plotMode==3: 

1298 plt.ion() 

1299 plt.show() 

1300 

1301 

1302 # Save plot 

1303 if plotMode>1: 

1304 title = title.replace(' ','-') + '.png' 

1305 plt.savefig(title) 

1306 

1307 

1308 # If plot is not to be shown then close it 

1309 if plotMode==2: 

1310 plt.close() 

1311 

1312 

1313 

1314