def simulate():
direction = "J2000,0deg,%fdeg" % DEC
v.MS = II(
"${MSDIR}/KAT-7_${SYNTHESIS}h60s_${DEC}_${DFREQ}_${NCHAN}chans.ms")
ms.create_empty_ms(msname=MS,
freq0=FREQ0,
dfreq=DFREQ,
nchan=NCHAN,
synthesis=SYNTHESIS,
dtime=60,
direction=direction,
pos=ANTENNAS,
tel="kat-7")
tfile = tempfile.NamedTemporaryFile(suffix=".lsm.html")
tfile.flush()
tname = tfile.name
x.sh("tigger-convert --recenter=$direction $LSMREF $tname -f")
v.LSM = tname
mqt.msrun(II("${mqt.CATTERY}/Siamese/turbo-sim.py"),
job='_tdl_job_1_simulate_MS',
section="sim",
args=["${lsm.LSM_TDL}"])
tfile.close()
def stackem(start=1, stop=100):
v.MS = MS or II("${LSM:BASE}.MS")
DO_STEP = lambda step: step>=float(start) and step<=float(stop)
if not exists(MS) or MS_REDO:
ms.create_empty_ms(tel=OBSERVATORY, pos=ANTENNAS, direction=DIRECTION, synthesis=SYNTHESIS, dtime=DTIME,
freq0=FREQ0, dfreq=DFREQ)
reload(ms)
start = 1
if DO_STEP(1):
simsky()
im.make_image()
if DO_STEP(2):
model = Tigger.load(LSM)
radec = []
flux = 0
for src in model.sources:
ra = src.pos.ra
dec = src.pos.dec
radec.append( map(numpy.rad2deg, [ra,dec]))
flux += src.flux.I
flux /=len(model.sources)
sflux = stacker.stackem(im.DIRTY_IMAGE, radec, width=WIDTH)
_add("%.4g %.4g"%(flux, sflux), STACKFILE, delimeter="\n")
def simulate():
direction = "J2000,0deg,%fdeg"%DEC
v.MS = II("${MSDIR}/KAT-7_${SYNTHESIS}h60s_${DEC}_${DFREQ}_${NCHAN}chans.ms")
ms.create_empty_ms(msname=MS, freq0=FREQ0, dfreq=DFREQ, nchan=NCHAN, synthesis=SYNTHESIS,
dtime=60, direction=direction, pos=ANTENNAS, tel="kat-7")
tfile = tempfile.NamedTemporaryFile(suffix=".lsm.html")
tfile.flush()
tname = tfile.name
x.sh("tigger-convert --recenter=$direction $LSMREF $tname -f")
v.LSM = tname
mqt.msrun(II("${mqt.CATTERY}/Siamese/turbo-sim.py"),
job = '_tdl_job_1_simulate_MS',
section = "sim",
args = ["${lsm.LSM_TDL}"])
tfile.close()
def azishe(config='$CFG'):
# Get parameters from json file
with open(II(config)) as jsn_std:
jparams = json.load(jsn_std)
# Remove empty strings and convert unicode characters to strings
params = {}
for key, val in jparams.iteritems():
# Make sure all keys are strings
_key = str(key)
# ignore empty strings and comments
if val == "" or _key == "#":
pass
# convert unicode values to strings
elif isinstance(val, unicode):
params[_key] = str(val).lower()
else:
params[_key] = val
get_opts = lambda prefix: filter(lambda a: a[0].startswith(prefix),
params.items())
# Retrieve MS and imager options
ms_dict = dict([(key.split('ms_')[-1], val)
for (key, val) in get_opts('ms_')])
im_dict = dict([(key.split('im_')[-1], val)
for (key, val) in get_opts('im_')])
# Seperate deconvolution settings
_deconv = {}
for dcv in 'lwimager wsclean moresane casa'.split():
if params[dcv]:
_deconv.update({
dcv:
dict([(key.split(dcv + '_')[-1], val)
for (key, val) in get_opts(dcv + '_')])
})
# Set imaging options
im.IMAGER = imager.IMAGER = params['imager'].lower()
for opt in 'npix weight robust mode stokes'.split():
if opt in im_dict.keys():
setattr(im, opt, im_dict.pop(opt))
im.cellsize = '%farcsec' % (im_dict.pop('cellsize'))
im.stokes = im.stokes.upper()
weight_fov = im_dict.pop('weight_fov')
if weight_fov:
im.weight_fov = '%farcmin' % weight_fov
# Create empty MS
synthesis = ms_dict.pop('synthesis')
scalenoise = 1
if synthesis > 12:
scalenoise = math.sqrt(12.0 / synthesis)
msname = II('rodrigues%f.MS' % (time.time()))
obs = params['observatory'].lower()
antennas = _OBS[obs]
freq0 = ms_dict.pop('freq0') * 1e6
dfreq = ms_dict.pop('dfreq') * 1e3
direction = "J2000,%s,%s" % (ms_dict.pop('ra'), ms_dict.pop('dec'))
ms.create_empty_ms(msname=msname,
synthesis=synthesis,
freq0=freq0,
dfreq=dfreq,
tel=obs,
pos='%s/%s' % (OBSDIR, antennas),
direction=direction,
**ms_dict)
if exists(msname):
v.MS = msname
else:
abort(
"Something went wrong while creating the empty MS. Please check logs for details"
)
makedir(DESTDIR)
ms.plot_uvcov(ms=.1,
width=10,
height=10,
dpi=150,
save="$OUTFILE-uvcov.png")
# Set noise for simulation
spwtab = ms.ms(subtable="SPECTRAL_WINDOW")
freq0 = spwtab.getcol("CHAN_FREQ")[ms.SPWID, 0]
spwtab.close()
if params['add_noise']:
noise = compute_vis_noise(sefd=get_sefd(freq0)) * scalenoise
else:
noise = 0
# Simulate Visibilities
_katalog = params['katalog_id']
if _katalog:
katalog = '%s/%s' % (KATDIR, _KATALOG[params['katalog_id']])
lsmname = II('${OUTDIR>/}${MS:BASE}.lsm.html')
radius = float(params['radius'])
fluxrange = params['fluxrange'].split('-')
if len(fluxrange) > 1:
fluxrange = map(float, fluxrange)
elif len(fluxrange) == 1:
fluxrange = [0, float(fluxrange[0])]
select = ''
fits = verify_sky(katalog) == 'FITS'
if radius or fluxrange:
if radius: select += '--select="r<%fdeg" ' % radius
if fluxrange:
select += '--select="I<%f" ' % fluxrange[1]
select += '--select="I>%f" ' % fluxrange[0]
if not fits:
x.sh(
'tigger-convert $select --recenter=$direction $katalog $lsmname -f'
)
else:
from pyrap.measures import measures
dm = measures()
direction = dm.direction('J2000', ms_opts[ra], ms_opts[dec])
ra = np.rad2deg(direction['m0']['value'])
dec = np.rad2deg(direction['m1']['value'])
hdu = pyfits.open(temp_file)
hdu[0].hdr['CRVAL1'] = ra
hdu[0].hdr['CRVAL2'] = dec
hdu.writeto(tmp_file, clobber=True)
simsky(lsmname=lsmname,
tdlsec='turbo-sim:custom',
noise=noise,
column='CORRECTED_DATA')
skymodel = params['sky_model']
if skymodel:
simsky(lsmname=skymodel,
noise=0 if katalog else noise,
addToCol='CORRECTED_DATA')
## Finally Lets image
# make dirty map
im.make_image(psf=True, **im_dict)
# Deconvolve
for deconv in _deconv:
deconv = deconv.lower()
if deconv in STAND_ALONE_DECONV:
im.make_image(algorithm=deconv,
restore=_deconv[deconv],
restore_lsm=False,
**im_dict)
else:
im.IMAGER = deconv
im.make_image(dirty=False,
restore=_deconv[deconv],
restore_lsm=False,
**im_dict)
xo.sh('tar -czvf ${OUTDIR>/}${MS:BASE}.tar.gz $msname')
def azishe(config='$CFG'):
# Get parameters from json file
with open(II(config)) as jsn_std:
jparams = json.load(jsn_std)
# Remove empty strings and convert unicode characters to strings
params = {}
for key, val in jparams.iteritems():
# Make sure all keys are strings
_key = str(key)
# ignore empty strings and comments
if val=="" or _key=="#":
pass
# convert unicode values to strings
elif isinstance(val,unicode):
params[_key] = str(val).lower()
else:
params[_key] = val
get_opts = lambda prefix: filter(lambda a: a[0].startswith(prefix), params.items())
# Retrieve MS and imager options
ms_dict = dict([(key.split('ms_')[-1],val) for (key,val) in get_opts('ms_') ] )
im_dict = dict([(key.split('im_')[-1],val) for (key,val) in get_opts('im_') ] )
# Seperate deconvolution settings
_deconv = {}
for dcv in 'lwimager wsclean moresane casa'.split():
if params[dcv]:
_deconv.update( {dcv:dict([(key.split(dcv+'_')[-1],val) for (key,val) in get_opts(dcv+'_') ] )} )
# Set imaging options
im.IMAGER = imager.IMAGER = params['imager'].lower()
for opt in 'npix weight robust mode stokes'.split():
if opt in im_dict.keys():
setattr(im,opt,im_dict.pop(opt))
im.cellsize = '%farcsec'%(im_dict.pop('cellsize'))
im.stokes = im.stokes.upper()
weight_fov = im_dict.pop('weight_fov')
if weight_fov:
im.weight_fov = '%farcmin'%weight_fov
# Create empty MS
synthesis = ms_dict.pop('synthesis')
scalenoise = 1
if synthesis > 12:
scalenoise = math.sqrt(12.0/synthesis)
msname = II('rodrigues%f.MS'%(time.time()))
obs = params['observatory'].lower()
antennas = _OBS[obs]
freq0 = ms_dict.pop('freq0')*1e6
dfreq = ms_dict.pop('dfreq')*1e3
direction = "J2000,%s,%s"%(ms_dict.pop('ra'),ms_dict.pop('dec'))
ms.create_empty_ms(msname=msname,synthesis=synthesis,freq0=freq0,
dfreq=dfreq,tel=obs,pos='%s/%s'%(OBSDIR,antennas),
direction=direction,**ms_dict)
if exists(msname):
v.MS = msname
else:
abort("Something went wrong while creating the empty MS. Please check logs for details")
makedir(DESTDIR)
ms.plot_uvcov(ms=.1,width=10,height=10,dpi=150,save="$OUTFILE-uvcov.png")
# Set noise for simulation
spwtab = ms.ms(subtable="SPECTRAL_WINDOW")
freq0 = spwtab.getcol("CHAN_FREQ")[ms.SPWID,0]
spwtab.close()
if params['add_noise']:
noise = compute_vis_noise(sefd=get_sefd(freq0)) * scalenoise
else:
noise = 0
# Simulate Visibilities
_katalog = params['katalog_id']
if _katalog:
katalog = '%s/%s'%(KATDIR,_KATALOG[params['katalog_id']])
lsmname = II('${OUTDIR>/}${MS:BASE}.lsm.html')
radius = float(params['radius'])
fluxrange = params['fluxrange'].split('-')
if len(fluxrange)>1:
fluxrange = map(float,fluxrange)
elif len(fluxrange)==1:
fluxrange = [0,float(fluxrange[0])]
select = ''
fits = verify_sky(katalog) == 'FITS'
if radius or fluxrange:
if radius: select += '--select="r<%fdeg" '%radius
if fluxrange:
select += '--select="I<%f" '%fluxrange[1]
select += '--select="I>%f" '%fluxrange[0]
if not fits:
x.sh('tigger-convert $select --recenter=$direction $katalog $lsmname -f')
else:
from pyrap.measures import measures
dm = measures()
direction = dm.direction('J2000',ms_opts[ra],ms_opts[dec])
ra = np.rad2deg(direction['m0']['value'])
dec = np.rad2deg(direction['m1']['value'])
hdu = pyfits.open(temp_file)
hdu[0].hdr['CRVAL1'] = ra
hdu[0].hdr['CRVAL2'] = dec
hdu.writeto(tmp_file,clobber=True)
simsky(lsmname=lsmname,tdlsec='turbo-sim:custom',noise=noise,column='CORRECTED_DATA')
skymodel = params['sky_model']
if skymodel:
simsky(lsmname=skymodel,noise=0 if katalog else noise,addToCol='CORRECTED_DATA')
## Finally Lets image
# make dirty map
im.make_image(psf=True,**im_dict)
# Deconvolve
for deconv in _deconv:
deconv = deconv.lower()
if deconv in STAND_ALONE_DECONV:
im.make_image(algorithm=deconv,restore=_deconv[deconv],restore_lsm=False,**im_dict)
else:
im.IMAGER = deconv
im.make_image(dirty=False,restore=_deconv[deconv],restore_lsm=False,**im_dict)
xo.sh('tar -czvf ${OUTDIR>/}${MS:BASE}.tar.gz $msname')