def ptclean3(vis, imageprefix, imagesuffix, ncpu, twidth, doreg, usephacenter,
reftime, toTb, overwrite, selectdata, field, spw, timerange,
uvrange, antenna, scan, observation, intent, datacolumn, imsize,
cell, phasecenter, stokes, projection, startmodel, specmode,
reffreq, nchan, start, width, outframe, veltype, restfreq,
interpolation, gridder, facets, chanchunks, wprojplanes, vptable,
usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache,
computepastep, rotatepastep, pblimit, normtype, deconvolver,
scales, nterms, smallscalebias, restoration, restoringbeam, pbcor,
outlierfile, weighting, robust, npixels, uvtaper, niter, gain,
threshold, nsigma, cycleniter, cyclefactor, minpsffraction,
maxpsffraction, interactive, usemask, mask, pbmask,
sidelobethreshold, noisethreshold, lownoisethreshold,
negativethreshold, smoothfactor, minbeamfrac, cutthreshold,
growiterations, dogrowprune, minpercentchange, verbose, restart,
savemodel, calcres, calcpsf, parallel, subregion):
if not (type(ncpu) is int):
casalog.post('ncpu should be an integer')
ncpu = 8
if doreg:
# check if ephem and msinfo exist. If not, generate one on the fly
try:
ephem = hf.read_horizons(vis=vis)
except ValueError:
print("error in obtaining ephemeris")
try:
msinfo = hf.read_msinfo(vis)
except ValueError:
print("error in getting ms info")
else:
ephem = None
msinfo = None
if imageprefix:
workdir = os.path.dirname(imageprefix)
else:
workdir = './'
tmpdir = workdir + '/tmp/'
if not os.path.exists(tmpdir):
os.makedirs(tmpdir)
# get number of time pixels
ms.open(vis)
ms.selectinit()
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
ms.close()
if twidth < 1:
casalog.post('twidth less than 1. Change to 1')
twidth = 1
if twidth > len(tim):
casalog.post(
'twidth greater than # of time pixels in the dataset. Change to the timerange of the entire dateset'
)
twidth = len(tim)
# find out the start and end time index according to the parameter timerange
# if not defined (empty string), use start and end from the entire time of the ms
if not timerange:
btidx = 0
etidx = len(tim) - 1
else:
try:
(tstart, tend) = timerange.split('~')
bt_s = qa.convert(qa.quantity(tstart, 's'), 's')['value']
et_s = qa.convert(qa.quantity(tend, 's'), 's')['value']
# only time is given but not date, add the date (at 0 UT) from the first record
if bt_s < 86400. or et_s < 86400.:
bt_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
et_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
btidx = np.argmin(np.abs(tim - bt_s))
etidx = np.argmin(np.abs(tim - et_s))
# make the indice back to those bracket by the timerange
if tim[btidx] < bt_s:
btidx += 1
if tim[etidx] > et_s:
etidx -= 1
if etidx <= btidx:
print("ending time must be greater than starting time")
print("reinitiating to the entire time range")
btidx = 0
etidx = len(tim) - 1
except ValueError:
print("keyword 'timerange' has a wrong format")
btstr = qa.time(qa.quantity(tim[btidx], 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(tim[etidx], 's'), prec=9, form='fits')[0]
iterable = range(btidx, etidx + 1, twidth)
print('First time pixel: ' + btstr)
print('Last time pixel: ' + etstr)
print(str(len(iterable)) + ' images to clean...')
res = []
# partition
clnpart = partial(
clean_iter, tim, vis, imageprefix, imagesuffix, twidth, doreg,
usephacenter, reftime, ephem, msinfo, toTb, overwrite, selectdata,
field, spw, uvrange, antenna, scan, observation, intent, datacolumn,
imsize, cell, phasecenter, stokes, projection, startmodel, specmode,
reffreq, nchan, start, width, outframe, veltype, restfreq,
interpolation, gridder, facets, chanchunks, wprojplanes, vptable,
usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache,
computepastep, rotatepastep, pblimit, normtype, deconvolver, scales,
nterms, smallscalebias, restoration, restoringbeam, pbcor, outlierfile,
weighting, robust, npixels, uvtaper, niter, gain, threshold, nsigma,
cycleniter, cyclefactor, minpsffraction, maxpsffraction, interactive,
usemask, mask, pbmask, sidelobethreshold, noisethreshold,
lownoisethreshold, negativethreshold, smoothfactor, minbeamfrac,
cutthreshold, growiterations, dogrowprune, minpercentchange, verbose,
restart, savemodel, calcres, calcpsf, parallel, subregion, tmpdir)
timelapse = 0
t0 = time()
# parallelization
if ncpu > 1:
import multiprocessing as mprocs
casalog.post('Perform clean in parallel ...')
print('Perform clean in parallel ...')
pool = mprocs.Pool(ncpu)
res = pool.map(clnpart, iterable)
pool.close()
pool.join()
else:
casalog.post('Perform clean in single process ...')
print('Perform clean in single process ...')
for i in iterable:
res.append(clnpart(i))
t1 = time()
timelapse = t1 - t0
print('It took %f secs to complete' % timelapse)
# repackage this into a single dictionary
results = {
'Succeeded': [],
'BeginTime': [],
'EndTime': [],
'ImageName': []
}
for r in res:
results['Succeeded'].append(r[0])
results['BeginTime'].append(r[1])
results['EndTime'].append(r[2])
results['ImageName'].append(r[3])
if os.path.exists(tmpdir):
os.system('rm -rf ' + tmpdir)
return results
def ptclean(vis, imageprefix, imagesuffix, ncpu, twidth, doreg, usephacenter,
reftime, toTb, overwrite, outlierfile, field, spw, selectdata,
timerange, uvrange, antenna, scan, observation, intent, mode,
resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc, painc,
aterm, psterm, mterm, wbawp, conjbeams, epjtable, interpolation,
niter, gain, threshold, psfmode, imagermode, ftmachine, mosweight,
scaletype, multiscale, negcomponent, smallscalebias, interactive,
mask, nchan, start, width, outframe, veltype, imsize, cell,
phasecenter, restfreq, stokes, weighting, robust, uvtaper,
outertaper, innertaper, modelimage, restoringbeam, pbcor, minpb,
usescratch, noise, npixels, npercycle, cyclefactor, cyclespeedup,
nterms, reffreq, chaniter, flatnoise, allowchunk):
if not (type(ncpu) is int):
casalog.post('ncpu should be an integer')
ncpu = 8
if doreg:
# check if ephem and msinfo exist. If not, generate one on the fly
try:
ephem = hf.read_horizons(vis)
except ValueError:
print("error in obtaining ephemeris")
try:
msinfo = hf.read_msinfo(vis)
except ValueError:
print("error in getting ms info")
else:
ephem = None
# get number of time pixels
ms.open(vis)
ms.selectinit()
timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True)
tim = timfreq['time']
# dt = tim[1]-tim[0] #need to change to median of all time intervals
dt = np.median(np.diff(tim))
freq = timfreq['axis_info']['freq_axis']['chan_freq'].flatten()
ms.close()
if twidth < 1:
casalog.post('twidth less than 1. Change to 1')
twidth = 1
if twidth > len(tim):
casalog.post(
'twidth greater than # of time pixels in the dataset. Change to the timerange of the entire dateset'
)
twidth = len(tim)
# find out the start and end time index according to the parameter timerange
# if not defined (empty string), use start and end from the entire time of the ms
if not timerange:
btidx = 0
etidx = len(tim) - 1
else:
try:
(tstart, tend) = timerange.split('~')
bt_s = qa.convert(qa.quantity(tstart, 's'), 's')['value']
et_s = qa.convert(qa.quantity(tend, 's'), 's')['value']
# only time is given but not date, add the date (at 0 UT) from the first record
if bt_s < 86400. or et_s < 86400.:
bt_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
et_s += np.fix(
qa.convert(qa.quantity(tim[0], 's'),
'd')['value']) * 86400.
btidx = np.argmin(np.abs(tim - bt_s))
etidx = np.argmin(np.abs(tim - et_s))
# make the indice back to those bracket by the timerange
if tim[btidx] < bt_s:
btidx += 1
if tim[etidx] > et_s:
etidx -= 1
if etidx <= btidx:
print "ending time must be greater than starting time"
print "reinitiating to the entire time range"
btidx = 0
etidx = len(tim) - 1
except ValueError:
print "keyword 'timerange' has a wrong format"
btstr = qa.time(qa.quantity(tim[btidx], 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(tim[etidx], 's'), prec=9, form='fits')[0]
iterable = range(btidx, etidx + 1, twidth)
print 'First time pixel: ' + btstr
print 'Last time pixel: ' + etstr
print str(len(iterable)) + ' images to clean...'
res = []
# partition
clnpart = partial(
clean_iter, tim, freq, vis, imageprefix, imagesuffix, ncpu, twidth,
doreg, usephacenter, reftime, ephem, msinfo, toTb, overwrite,
outlierfile, field, spw, selectdata, uvrange, antenna, scan,
observation, intent, mode, resmooth, gridmode, wprojplanes, facets,
cfcache, rotpainc, painc, aterm, psterm, mterm, wbawp, conjbeams,
epjtable, interpolation, niter, gain, threshold, psfmode, imagermode,
ftmachine, mosweight, scaletype, multiscale, negcomponent,
smallscalebias, interactive, mask, nchan, start, width, outframe,
veltype, imsize, cell, phasecenter, restfreq, stokes, weighting,
robust, uvtaper, outertaper, innertaper, modelimage, restoringbeam,
pbcor, minpb, usescratch, noise, npixels, npercycle, cyclefactor,
cyclespeedup, nterms, reffreq, chaniter, flatnoise, allowchunk)
timelapse = 0
t0 = time()
# parallelization
para = 1
if para:
casalog.post('Perform clean in parallel ...')
pool = mprocs.Pool(ncpu)
# res = pool.map_async(clnpart, iterable)
res = pool.map(clnpart, iterable)
pool.close()
pool.join()
else:
for i in iterable:
res.append(clnpart(i))
t1 = time()
timelapse = t1 - t0
print 'It took %f secs to complete' % timelapse
# repackage this into a single dictionary
results = {
'Succeeded': [],
'BeginTime': [],
'EndTime': [],
'ImageName': []
}
for r in res:
results['Succeeded'].append(r[0])
results['BeginTime'].append(r[1])
results['EndTime'].append(r[2])
results['ImageName'].append(r[3])
return results
def clean_iter(
tim, vis, imageprefix, imagesuffix, twidth, doreg, usephacenter,
reftime, ephem, msinfo, toTb, overwrite, selectdata, field, spw,
uvrange, antenna, scan, observation, intent, datacolumn, imsize, cell,
phasecenter, stokes, projection, startmodel, specmode, reffreq, nchan,
start, width, outframe, veltype, restfreq, interpolation, gridder,
facets, chanchunks, wprojplanes, vptable, usepointing, mosweight,
aterm, psterm, wbawp, conjbeams, cfcache, computepastep, rotatepastep,
pblimit, normtype, deconvolver, scales, nterms, smallscalebias,
restoration, restoringbeam, pbcor, outlierfile, weighting, robust,
npixels, uvtaper, niter, gain, threshold, nsigma, cycleniter,
cyclefactor, minpsffraction, maxpsffraction, interactive, usemask,
mask, pbmask, sidelobethreshold, noisethreshold, lownoisethreshold,
negativethreshold, smoothfactor, minbeamfrac, cutthreshold,
growiterations, dogrowprune, minpercentchange, verbose, restart,
savemodel, calcres, calcpsf, parallel, subregion, tmpdir, btidx):
from tclean_cli import tclean_cli as tclean
from split_cli import split_cli as split
bt = btidx # 0
if bt + twidth < len(tim) - 1:
et = btidx + twidth - 1
else:
et = len(tim) - 1
if bt == 0:
bt_d = tim[bt] - ((tim[bt + 1] - tim[bt]) / 2)
else:
bt_d = tim[bt] - ((tim[bt] - tim[bt - 1]) / 2)
if et == (len(tim) - 1) or et == -1:
et_d = tim[et] + ((tim[et] - tim[et - 1]) / 2)
else:
et_d = tim[et] + ((tim[et + 1] - tim[et]) / 2)
timerange = qa.time(qa.quantity(bt_d, 's'), prec=9, form='ymd')[0] + '~' + \
qa.time(qa.quantity(et_d, 's'), prec=9, form='ymd')[0]
btstr = qa.time(qa.quantity(bt_d, 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(et_d, 's'), prec=9, form='fits')[0]
print('cleaning timerange: ' + timerange)
image0 = btstr.replace(':', '').replace('-', '')
imname = imageprefix + image0 + imagesuffix
# ms_tmp = tmpdir + image0 + '.ms'
# print('checkpoint 1')
# # split(vis=vis, outputvis=ms_tmp, field=field, scan=scan, antenna=antenna, timerange=timerange,
# # datacolumn=datacolumn)
# ms.open(vis)
# print('checkpoint 1-1')
# ms.split(ms_tmp,field=field, scan=scan, baseline=antenna, time=timerange,whichcol=datacolumn)
# print('checkpoint 1-2')
# ms.close()
# print('checkpoint 2')
if overwrite or (len(glob.glob(imname + '*')) == 0):
os.system('rm -rf {}*'.format(imname))
try:
tclean(vis=vis,
selectdata=selectdata,
field=field,
spw=spw,
timerange=timerange,
uvrange=uvrange,
antenna=antenna,
scan=scan,
observation=observation,
intent=intent,
datacolumn=datacolumn,
imagename=imname,
imsize=imsize,
cell=cell,
phasecenter=phasecenter,
stokes=stokes,
projection=projection,
startmodel=startmodel,
specmode=specmode,
reffreq=reffreq,
nchan=nchan,
start=start,
width=width,
outframe=outframe,
veltype=veltype,
restfreq=restfreq,
interpolation=interpolation,
gridder=gridder,
facets=facets,
chanchunks=chanchunks,
wprojplanes=wprojplanes,
vptable=vptable,
usepointing=usepointing,
mosweight=mosweight,
aterm=aterm,
psterm=psterm,
wbawp=wbawp,
conjbeams=conjbeams,
cfcache=cfcache,
computepastep=computepastep,
rotatepastep=rotatepastep,
pblimit=pblimit,
normtype=normtype,
deconvolver=deconvolver,
scales=scales,
nterms=nterms,
smallscalebias=smallscalebias,
restoration=restoration,
restoringbeam=restoringbeam,
pbcor=pbcor,
outlierfile=outlierfile,
weighting=weighting,
robust=robust,
npixels=npixels,
uvtaper=uvtaper,
niter=niter,
gain=gain,
threshold=threshold,
nsigma=nsigma,
cycleniter=cycleniter,
cyclefactor=cyclefactor,
minpsffraction=minpsffraction,
maxpsffraction=maxpsffraction,
interactive=interactive,
usemask=usemask,
mask=mask,
pbmask=pbmask,
sidelobethreshold=sidelobethreshold,
noisethreshold=noisethreshold,
lownoisethreshold=lownoisethreshold,
negativethreshold=negativethreshold,
smoothfactor=smoothfactor,
minbeamfrac=minbeamfrac,
cutthreshold=cutthreshold,
growiterations=growiterations,
dogrowprune=dogrowprune,
minpercentchange=minpercentchange,
verbose=verbose,
restart=restart,
savemodel=savemodel,
calcres=calcres,
calcpsf=calcpsf,
parallel=parallel)
# print('checkpoint 3')
if pbcor:
clnjunks = [
'.flux', '.mask', '.model', '.psf', '.residual', '.pb',
'.sumwt', '.image'
]
else:
clnjunks = [
'.flux', '.mask', '.model', '.psf', '.residual', '.pb',
'.sumwt', '.image.pbcor'
]
for clnjunk in clnjunks:
if os.path.exists(imname + clnjunk):
shutil.rmtree(imname + clnjunk)
if pbcor:
os.system('mv {} {}'.format(imname + '.image.pbcor',
imname + '.image'))
except:
print('error in cleaning image: ' + btstr)
return [False, btstr, etstr, '']
else:
print(imname + ' exists. Clean task aborted.')
if doreg and not os.path.isfile(imname + '.fits'):
# ephem.keys()
# msinfo.keys()
try:
# check if ephemfile and msinfofile exist
if not ephem:
print(
"ephemeris info does not exist, querying from JPL Horizons on the fly"
)
ephem = hf.read_horizons(vis=vis)
if not msinfo:
print("ms info not provided, generating one on the fly")
msinfo = hf.read_msinfo(vis)
hf.imreg(vis=vis,
ephem=ephem,
msinfo=msinfo,
timerange=timerange,
reftime=reftime,
imagefile=imname + '.image',
fitsfile=imname + '.fits',
toTb=toTb,
scl100=False,
usephacenter=usephacenter,
subregion=subregion)
if os.path.exists(imname + '.fits'):
shutil.rmtree(imname + '.image')
return [True, btstr, etstr, imname + '.fits']
else:
return [False, btstr, etstr, '']
except:
print('error in registering image: ' + btstr)
return [False, btstr, etstr, imname + '.image']
else:
if os.path.exists(imname + '.image'):
return [True, btstr, etstr, imname + '.image']
else:
return [False, btstr, etstr, '']
def clean_iter(
tim, freq, vis, imageprefix, imagesuffix, ncpu, twidth, doreg,
usephacenter, reftime, ephem, msinfo, toTb, overwrite, outlierfile,
field, spw, selectdata, uvrange, antenna, scan, observation, intent,
mode, resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc,
painc, aterm, psterm, mterm, wbawp, conjbeams, epjtable, interpolation,
niter, gain, threshold, psfmode, imagermode, ftmachine, mosweight,
scaletype, multiscale, negcomponent, smallscalebias, interactive, mask,
nchan, start, width, outframe, veltype, imsize, cell, phasecenter,
restfreq, stokes, weighting, robust, uvtaper, outertaper, innertaper,
modelimage, restoringbeam, pbcor, minpb, usescratch, noise, npixels,
npercycle, cyclefactor, cyclespeedup, nterms, reffreq, chaniter,
flatnoise, allowchunk, btidx):
from taskinit import ms
from taskinit import qa
# from __casac__.quanta import quanta as qa
from __main__ import default, inp
#from clean import clean
from clean_cli import clean_cli as clean
bt = btidx # 0
if bt + twidth < len(tim) - 1:
et = btidx + twidth - 1
else:
et = len(tim) - 1
# tim_d = tim/3600./24.-np.fix(tim/3600./24.)
if bt == 0:
bt_d = tim[bt] - ((tim[bt + 1] - tim[bt]) / 2)
else:
bt_d = tim[bt] - ((tim[bt] - tim[bt - 1]) / 2)
if et == (len(tim) - 1) or et == -1:
et_d = tim[et] + ((tim[et] - tim[et - 1]) / 2)
else:
et_d = tim[et] + ((tim[et + 1] - tim[et]) / 2)
#
# bt_d=tim[bt]
# et_d=tim[et]+0.005
timerange = qa.time(qa.quantity(bt_d, 's'), prec=9, form='ymd')[0] + '~' + \
qa.time(qa.quantity(et_d, 's'), prec=9, form='ymd')[0]
tmid = (bt_d + et_d) / 2.
btstr = qa.time(qa.quantity(bt_d, 's'), prec=9, form='fits')[0]
etstr = qa.time(qa.quantity(et_d, 's'), prec=9, form='fits')[0]
print 'cleaning timerange: ' + timerange
image0 = btstr.replace(':', '').replace('-', '')
imname = imageprefix + image0 + imagesuffix
if overwrite or (len(glob.glob(imname + '*')) == 0):
# inp(taskname = 'clean')
os.system('rm -rf {}*'.format(imname))
try:
clean(vis=vis,
imagename=imname,
outlierfile=outlierfile,
field=field,
spw=spw,
selectdata=selectdata,
timerange=timerange,
uvrange=uvrange,
antenna=antenna,
scan=scan,
observation=str(observation),
intent=intent,
mode=mode,
resmooth=resmooth,
gridmode=gridmode,
wprojplanes=wprojplanes,
facets=facets,
cfcache=cfcache,
rotpainc=rotpainc,
painc=painc,
psterm=psterm,
aterm=aterm,
mterm=mterm,
wbawp=wbawp,
conjbeams=conjbeams,
epjtable=epjtable,
interpolation=interpolation,
niter=niter,
gain=gain,
threshold=threshold,
psfmode=psfmode,
imagermode=imagermode,
ftmachine=ftmachine,
mosweight=mosweight,
scaletype=scaletype,
multiscale=multiscale,
negcomponent=negcomponent,
smallscalebias=smallscalebias,
interactive=interactive,
mask=mask,
nchan=nchan,
start=start,
width=width,
outframe=outframe,
veltype=veltype,
imsize=imsize,
cell=cell,
phasecenter=phasecenter,
restfreq=restfreq,
stokes=stokes,
weighting=weighting,
robust=robust,
uvtaper=uvtaper,
outertaper=outertaper,
innertaper=innertaper,
modelimage=modelimage,
restoringbeam=restoringbeam,
pbcor=pbcor,
minpb=minpb,
usescratch=usescratch,
noise=noise,
npixels=npixels,
npercycle=npercycle,
cyclefactor=cyclefactor,
cyclespeedup=cyclespeedup,
nterms=nterms,
reffreq=reffreq,
chaniter=chaniter,
flatnoise=flatnoise,
allowchunk=False)
clnjunks = ['.flux', '.mask', '.model', '.psf', '.residual']
for clnjunk in clnjunks:
if os.path.exists(imname + clnjunk):
shutil.rmtree(imname + clnjunk)
except:
print('error in cleaning image: ' + btstr)
return [False, btstr, etstr, '']
else:
print imname + ' exists. Clean task aborted.'
if doreg and not os.path.isfile(imname + '.fits'):
#ephem.keys()
#msinfo.keys()
try:
# check if ephemfile and msinfofile exist
if not ephem:
print(
"ephemeris info does not exist, querying from JPL Horizons on the fly"
)
ephem = hf.read_horizons(vis)
if not msinfo:
print("ms info not provided, generating one on the fly")
msinfo = hf.read_msinfo(vis)
hf.imreg(vis=vis,
ephem=ephem,
msinfo=msinfo,
timerange=timerange,
reftime=reftime,
imagefile=imname + '.image',
fitsfile=imname + '.fits',
toTb=toTb,
scl100=False,
usephacenter=usephacenter)
if os.path.exists(imname + '.fits'):
shutil.rmtree(imname + '.image')
return [True, btstr, etstr, imname + '.fits']
else:
return [False, btstr, etstr, '']
except:
print('error in registering image: ' + btstr)
return [False, btstr, etstr, imname + '.image']
else:
if os.path.exists(imname + '.image'):
return [True, btstr, etstr, imname + '.image']
else:
return [False, btstr, etstr, '']
