def mfs_image(**kwargs):
cmd, p = img_cmd(**kwargs)
# Perform MFS imaging
utils.log("...starting MFS image of {} data".format(p.mfstype), f=p.lf, verbose=p.verbose)
icmd = cmd + ['--image_mfs', '--msin', p.datafile, '--spw', p.spw]
if p.mfstype == 'resid':
icmd += ['--uvsub']
if p.source_ext == '':
source_ext = ''
else:
source_ext = '{}_'.format(p.source_ext)
if p.mfstype == '':
mfstype = ''
else:
mfstype = '_{}'.format(p.mfstype)
icmd += ['--source_ext', "{}{}".format(source_ext, mfstype)]
ecode = subprocess.check_call(icmd)
if p.mfstype == 'resid':
# Apply gaintables to make CORRECTED column as it was
utils.log("...reapplying gaintables to CORRECTED data", f=p.lf, verbose=p.verbose)
cmd2 = p.casa + ["-c", "{}/sky_cal.py".format(casa_scripts), "--msin", p.datafile, "--gaintables"] + p.gaintables
ecode = subprocess.check_call(cmd2)
def gen_model(**kwargs):
p = Dict2Obj(**kwargs)
utils.log("\n{}\n...Generating a Flux Model", f=p.lf, verbose=p.verbose)
# compile complist_gleam.py command
cmd = casa + ["-c", "{}/complist_gleam.py".format(casa_scripts)]
cmd += [
'--point_ra', p.source_ra, '--point_dec', p.latitude, '--outdir',
p.out_dir, '--gleamfile', p.gleamfile, '--radius', p.radius,
'--min_flux', p.min_flux, '--freqs', p.freqs, '--cell', p.cell,
'--imsize', p.imsize
]
if p.image:
cmd += ['--image']
if p.use_peak:
cmd += ['--use_peak']
if p.overwrite:
cmd += ['--overwrite']
if hasattr(p, 'regions'):
cmd += [
'--regions', p.regions, '--exclude', '--region_radius',
p.region_radius
]
if hasattr(p, 'file_ext'):
cmd += ['--ext', p.file_ext]
else:
p.file_ext = ''
cmd = map(str, cmd)
ecode = subprocess.call(cmd)
modelstem = os.path.join(p.out_dir, "gleam{}.cl".format(p.file_ext))
model = modelstem
if p.image:
model += ".image"
print(p.longitude)
print(p.latitude)
print(p.time)
# beam args
print(p.beamfile)
print(p.out_dir)
# pbcorrect
if p.pbcorr:
# Do primary beam correction
pbcorr(modelname=modelstem)
# importfits
cmd = p.casa + [
"-c", "importfits('{}', '{}', overwrite={})".format(
modelstem + '.pbcorr.fits', modelstem + '.pbcorr.image',
p.overwrite)
]
ecode = subprocess.call(cmd)
model = modelstem + ".pbcorr.image"
return model
def gen_model(**kwargs):
p = Dict2Obj(**kwargs)
utils.log("\n{}\n...Generating a Flux Model", f=p.lf, verbose=p.verbose)
# compile complist_gleam.py command
cmd = casa + ["-c", "{}/complist_gleam.py".format(casa_scripts)]
cmd += ['--point_ra', p.source_ra, '--point_dec', p.latitude, '--outdir', p.out_dir,
'--gleamfile', p.gleamfile, '--radius', p.radius, '--min_flux', p.min_flux,
'--freqs', p.freqs, '--cell', p.cell, '--imsize', p.imsize]
if p.image:
cmd += ['--image']
if p.use_peak:
cmd += ['--use_peak']
if p.overwrite:
cmd += ['--overwrite']
if hasattr(p, 'regions'):
cmd += ['--regions', p.regions, '--exclude', '--region_radius', p.region_radius]
if hasattr(p, 'file_ext'):
cmd += ['--ext', p.file_ext]
else:
p.file_ext = ''
cmd = map(str, cmd)
ecode = subprocess.check_call(cmd)
modelstem = os.path.join(p.out_dir, "gleam{}.cl".format(p.file_ext))
model = modelstem
if p.image:
model += ".image"
# pbcorrect
if p.pbcorr:
utils.log("...applying PB to model", f=p.lf, verbose=p.verbose)
assert p.image, "Cannot pbcorrect flux model without image == True"
cmd = ["pbcorr.py", "--lon", p.longitude, "--lat", p.latitude, "--time", p.time, "--pols"] \
+ [uvutils.polstr2num(pol) for pol in p.pols] \
+ ["--outdir", p.out_dir, "--multiply", "--beamfile", p.beamfile]
if p.overwrite:
cmd.append("--overwrite")
cmd.append(modelstem + '.fits')
# generate component list and / or image cube flux model
cmd = map(str, cmd)
ecode = subprocess.check_call(cmd)
modelstem = os.path.join(p.out_dir, modelstem)
# importfits
cmd = p.casa + ["-c", "importfits('{}', '{}', overwrite={})".format(modelstem + '.pbcorr.fits', modelstem + '.pbcorr.image', p.overwrite)]
ecode = subprocess.check_call(cmd)
model = modelstem + ".pbcorr.image"
return model
def image(**img_kwargs):
# Perform MFS of corrected data
if img_kwargs['image_mfs']:
kwargs = dict(
list(img_kwargs.items()) + list(global_vars(varlist).items()))
kwargs['mfstype'] = 'corr'
mfs_image(**kwargs)
# Perform MFS of model data
if img_kwargs['image_mdl']:
kwargs = dict(
list(img_kwargs.items()) + list(global_vars(varlist).items()))
mfile = "{}.model".format(datafile)
if not os.path.exists(mfile):
utils.log(
"Didn't split model from datafile, which is required to image the model",
f=lf,
verbose=verbose)
else:
kwargs['datafile'] = mfile
kwargs['mfstype'] = 'model'
mfs_image(**kwargs)
# Perform MFS of residual data
if img_kwargs['image_res']:
kwargs = dict(
list(img_kwargs.items()) + list(global_vars(varlist).items()))
kwargs['mfstype'] = 'resid'
mfs_image(**kwargs)
# Get spectral cube of corrected data
if img_kwargs['image_spec']:
kwargs = dict(
list(img_kwargs.items()) + list(global_vars(varlist).items()))
spec_image(**kwargs)
# Get spectral cube of model data
if img_kwargs['image_mdl_spec']:
kwargs = dict(
list(img_kwargs.items()) + list(global_vars(varlist).items()))
mfile = "{}.model".format(datafile)
if not os.path.exists(mfile):
utils.log(
"Didn't split model from datafile, which is required to image the model",
f=lf,
verbose=verbose)
else:
kwargs['datafile'] = mfile
spec_image(**kwargs)
def spec_image(**kwargs):
cmd, p = img_cmd(**kwargs)
# Perform Spectral Cube imaging
utils.log("...starting {} spectral cube imaging".format(p.datafile), f=p.lf, verbose=p.verbose)
icmd = cmd + ['--spec_cube', '--msin', p.datafile,
'--spec_start', str(p.spec_start), '--spec_end', str(p.spec_end),
'--spec_dchan', str(p.spec_dchan)]
if p.source_ext == '':
source_ext = ''
else:
source_ext = '{}_'.format(p.source_ext)
icmd += ['--source_ext', "{}spec".format(source_ext)]
ecode = subprocess.check_call(icmd)
# Collate output images and run a source extraction
img_cube_template = "{}.{}spec.chan????.image.fits".format(p.datafile, source_ext)
img_cube = sorted(glob.glob(img_cube_template))
if p.source_extract:
utils.log("...extracting {} from {} cube".format(p.source, img_cube_template), f=p.lf, verbose=p.verbose)
if len(img_cube) == 0:
utils.log("...no image cube files found, cannot extract spectrum", f=p.lf, verbose=p.verbose)
else:
cmd = ["source_extract.py", "--source", p.source, "--source_ra", p.source_ra, "--source_dec", p.source_dec,
"--radius", p.radius, '--pols'] + p.pols \
+ ["--outdir", p.out_dir, "--gaussfit_mult", p.gauss_mult, "--source_ext", p.source_ext]
if p.overwrite:
cmd += ["--overwrite"]
if p.plot_fit:
cmd += ["--plot_fit"]
cmd += img_cube
cmd = map(str, cmd)
ecode = subprocess.check_call(cmd)
def calibrate(**cal_kwargs):
kwargs = dict(cal_kwargs.items() + global_vars(varlist).items())
p = Dict2Obj(**kwargs)
# compile command
cmd = p.casa + ["-c", "{}/sky_cal.py".format(casa_scripts)]
cmd += ["--msin", p.datafile, "--out_dir", p.out_dir, "--model", p.model,
"--refant", p.refant, "--gain_spw", p.gain_spw, "--uvrange", p.uvrange, "--timerange",
p.timerange, "--ex_ants", p.ex_ants, "--gain_ext", p.gain_ext, '--bp_spw', p.bp_spw]
if p.source_ra is not None:
cmd += ["--source_ra", p.source_ra]
if p.source_dec is not None:
cmd += ["--source_dec", p.source_dec]
if isinstance(p.gaintables, list):
gtables = p.gaintables
else:
if p.gaintables in ['', None, 'None', 'none']:
gtables = []
else:
gtables = [p.gaintables]
if len(gtables) > 0:
cmd += ['--gaintables'] + gtables
if p.rflag:
cmd += ["--rflag"]
if p.KGcal:
cmd += ["--KGcal", "--KGsnr", p.KGsnr]
if p.Acal:
cmd += ["--Acal", "--Asnr", p.Asnr]
if p.BPcal:
cmd += ["--BPcal", "--BPsnr", p.BPsnr, "--bp_spw", p.bp_spw]
if p.BPsolnorm:
cmd += ['--BPsolnorm']
if p.split_cal:
cmd += ["--split_cal", "--cal_ext", p.cal_ext]
if p.split_model:
cmd += ["--split_model"]
cmd = [' '.join(_cmd) if type(_cmd) == list else str(_cmd) for _cmd in cmd]
utils.log("...starting calibration", f=p.lf, verbose=p.verbose)
ecode = subprocess.check_call(cmd)
# Gather gaintables
gext = ''
if p.gain_ext not in ['', None]:
gext = '.{}'.format(p.gain_ext)
gts = sorted(glob.glob("{}{}.?.cal".format(p.datafile, gext)) + glob.glob("{}{}.????.cal".format(p.datafile, gext)))
# export to calfits if desired
if p.export_gains:
utils.log("...exporting\n{}\n to calfits and combining into a single cal table".format('\n'.join(gts)), f=p.lf, verbose=p.verbose)
# do file checks
mirvis = os.path.splitext(p.datafile)[0]
gtsnpz = ["{}.npz".format(gt) for gt in gts]
if not os.path.exists(mirvis):
utils.log("...{} doesn't exist: cannot export gains to calfits".format(mirvis), f=p.lf, verbose=p.verbose)
elif len(gts) == 0:
utils.log("...no gaintables found, cannot export gains to calfits", f=p.lf, verbose=p.verbose)
elif not np.all([os.path.exists(gtnpz) for gtnpz in gtsnpz]):
utils.log("...couldn't find a .npz file for all input .cal tables, can't export to calfits", f=p.lf, verbose=p.verbose)
else:
calfits_fname = "{}.{}{}.calfits".format(os.path.basename(mirvis), p.source, p.gain_ext)
cmd = ['skynpz2calfits.py', "--fname", calfits_fname, "--uv_file", mirvis, '--out_dir', p.out_dir]
if p.overwrite:
cmd += ["--overwrite"]
# add a delay and phase solution
matchK = ["K.cal.npz" in gt for gt in gtsnpz]
matchGphs = ["Gphs.cal.npz" in gt for gt in gtsnpz]
if np.any(matchK):
cmd += ["--plot_dlys"]
cmd += ["--dly_files"] + [gtsnpz[i] for i, b in enumerate(matchK) if b == True]
if not np.any(matchGphs):
utils.log("...WARNING: A delay file {} was found, but no mean phase file, which is needed if a delay file is present.", f=lf, verbose=verbose)
if np.any(matchGphs):
cmd += ["--plot_phs"]
cmd += ["--phs_files"] + [gtsnpz[i] for i, b in enumerate(matchGphs) if b == True]
# add a mean amp solution
matchGamp = ["Gamp.cal.npz" in gt for gt in gtsnpz]
if np.any(matchGamp):
cmd += ["--plot_amp"]
cmd += ["--amp_files"] + [gtsnpz[i] for i, b in enumerate(matchGamp) if b == True]
# add a bandpass solution
matchB = ["B.cal.npz" in gt for gt in gtsnpz]
if np.any(matchB):
cmd += ["--plot_bp"]
cmd += ["--bp_files"] + [gtsnpz[i] for i, b in enumerate(matchB) if b == True]
# additional smoothing options
if p.smooth:
cmd += ["--bp_gp_smooth", "--bp_gp_max_dly", p.gp_max_dly]
if p.medfilt:
cmd += ["--bp_medfilt", "--medfilt_kernel", p.kernel]
if p.bp_broad_flags:
cmd += ["--bp_broad_flags", "--bp_flag_frac", p.bp_flag_frac]
if not p.verbose:
cmd += ['--silence']
cmd = map(str, cmd)
ecode = subprocess.check_call(cmd)
# convert calfits back to a single Btotal.cal table
if np.any(matchB):
# convert to cal
bfile = gts[matchB.index(True)]
btot_file = os.path.join(out_dir, "{}{}.Btotal.cal".format(os.path.basename(p.datafile), gext))
cmd = p.casa + ["-c", "{}/calfits_to_Bcal.py".format(casa_scripts), "--cfits", os.path.join(p.out_dir, calfits_fname), "--inp_cfile", bfile,"--out_cfile", btot_file]
if overwrite:
cmd += ["--overwrite"]
ecode = subprocess.check_call(cmd)
# replace gaintables with Btotal.cal
gts = [btot_file]
# append to gaintables
gtables += gts
return gtables
# Setup (Small) Global Variable Dictionary
varlist = ['datafile', 'verbose', 'overwrite', 'out_dir', 'casa', 'source_ra', 'source_dec', 'source',
'longitude', 'latitude', 'lf', 'gaintables']
def global_vars(varlist=[]):
d = []
for v in varlist:
try:
d.append((v, globals()[v]))
except KeyError:
continue
return dict(d)
# Print out parameter header
time = datetime.utcnow()
utils.log("Starting skycal_pipe.py on {}\n{}\n".format(time, '-'*60),
f=lf, verbose=verbose)
_cf = copy.copy(cf)
_cf.pop('algorithm')
utils.log(json.dumps(_cf, indent=1) + '\n', f=lf, verbose=verbose)
# Setup a dict->object converter
class Dict2Obj:
def __init__(self, **entries):
self.__dict__.update(entries)
#-------------------------------------------------------------------------------
# Search for a Source and Prepare Data for MS Conversion
#-------------------------------------------------------------------------------
if params['prep_data']:
# start block
time = datetime.utcnow()
