def set_impars(impars, line_name, vis, spwnames=None):
if line_name not in ('full', ) + spwnames:
local_impars = {}
if 'width' in linpars:
local_impars['width'] = linpars['width']
else:
# calculate the channel width
chanwidths = []
for vv in vis:
msmd.open(vv)
count_spws = len(msmd.spwsforfield(field))
chanwidth = np.max([np.abs(
effectiveResolutionAtFreq(vv,
spw='{0}'.format(i),
freq=u.Quantity(linpars['restfreq']).to(u.GHz),
kms=True)) for i in
range(count_spws)])
# second awful check b/c Todd's script failed for some cases
for spw in range(count_spws):
chanwidths_hz = msmd.chanwidths(int(spw))
chanfreqs_hz = msmd.chanfreqs(int(spw))
ckms = constants.c.to(u.km/u.s).value
if any(chanwidths_hz > (chanwidth / ckms)*chanfreqs_hz):
chanwidth = np.max(chanwidths_hz/chanfreqs_hz * ckms)
msmd.close()
chanwidths.append(chanwidth)
# chanwidth: mean? max?
chanwidth = np.mean(chanwidths)
logprint("Channel widths were {0}, mean = {1}".format(chanwidths,
chanwidth),
origin="almaimf_line_imaging")
if np.any(np.array(chanwidths) - chanwidth > 1e-4):
raise ValueError("Varying channel widths.")
local_impars['width'] = '{0:.2f}km/s'.format(np.round(chanwidth, 2))
local_impars['restfreq'] = linpars['restfreq']
# calculate vstart
vstart = u.Quantity(linpars['vlsr'])-u.Quantity(linpars['cubewidth'])/2
local_impars['start'] = '{0:.1f}km/s'.format(vstart.value)
local_impars['chanchunks'] = int(chanchunks)
local_impars['nchan'] = int((u.Quantity(line_parameters[field][line_name]['cubewidth'])
/ u.Quantity(local_impars['width'])).value)
if local_impars['nchan'] < local_impars['chanchunks']:
local_impars['chanchunks'] = local_impars['nchan']
impars.update(local_impars)
else:
impars['chanchunks'] = int(chanchunks)
if 'nchan' in impars:
# apparently you can't have nchan % chanchunks > 0
cc = impars['chanchunks']
while impars['nchan'] % cc > 0:
cc -= 1
impars['chanchunks'] = cc
return impars
def make_custom_mask(fieldname,
imname,
almaimf_code_path,
band_id,
rootdir="",
suffix=""):
regfn = os.path.join(
almaimf_code_path,
'clean_regions/{0}_{1}{2}.reg'.format(fieldname, band_id, suffix))
regs = regions.read_ds9(regfn)
logprint("Using region file {0} to create mask".format(regfn),
origin='make_custom_mask')
cube = SpectralCube.read(imname, format='casa_image')
image = cube[0]
if image.unit.is_equivalent(u.Jy / u.beam):
image = image * u.beam
else:
assert image.unit.is_equivalent(u.Jy), "Image must be in Jansky/beam."
mask_array = np.zeros(image.shape, dtype='bool')
for reg in regs:
threshold = u.Quantity(reg.meta['label'])
assert threshold.unit.is_equivalent(
u.Jy), "Threshold must by in mJy or Jy"
preg = reg.to_pixel(image.wcs)
msk = preg.to_mask()
mask_array[msk.bbox.slices] = (msk.multiply(image) >
threshold) | mask_array[msk.bbox.slices]
# CASA transposes arrays!!!!!
mask_array = mask_array.T
ia.open(imname)
assert np.all(ia.shape() == mask_array[:, :, None, None].shape
), "Failure: image shape doesn't match mask shape"
cs = ia.coordsys()
ia.close()
maskname = ('{fieldname}_{band_id}{suffix}_mask.mask'.format(
fieldname=fieldname, band_id=band_id, suffix=suffix))
# add a root directory if there is one
# (if rootdir == "", this just returns maskname)
maskname = os.path.join(rootdir, maskname)
assert ia.fromarray(outfile=maskname,
pixels=mask_array.astype('float')[:, :, None, None],
csys=cs.torecord(),
overwrite=True), "FAILURE in final mask creation step"
ia.close()
return maskname
if 'only_7m' not in locals():
if os.getenv('ONLY_7M') is not None:
only_7m = bool(os.getenv('ONLY_7M').lower() == 'true')
else:
only_7m = False
# load the list of continuum MSes from a file
# (this file has one continuum MS full path, e.g. /path/to/file.ms, per line)
with open('continuum_mses.txt', 'r') as fh:
continuum_mses = [x.strip() for x in fh.readlines()]
if os.getenv(
'DO_BSENS') is not None and os.getenv('DO_BSENS').lower() != 'false':
do_bsens = True
logprint("Using BSENS measurement set")
continuum_mses += [
x.replace('_continuum_merged.cal.ms', '_continuum_merged_bsens.cal.ms')
for x in continuum_mses
]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
band = 'B3' if 'B3' in basename else 'B6' if 'B6' in basename else 'ERROR'
# allow optional cmdline args to skip one or the other band
if os.getenv('BAND_TO_IMAGE'):
if band not in os.getenv('BAND_TO_IMAGE'):
if 'exclude_7m' not in locals():
if os.getenv('EXCLUDE_7M') is not None:
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
else:
exclude_7m = False
if 'only_7m' not in locals():
if os.getenv('ONLY_7M') is not None:
only_7m = bool(os.getenv('ONLY_7M').lower() == 'true')
else:
only_7m = False
if 'selfcal_field_id' not in locals():
if os.getenv('SELFCAL_FIELD_ID') is not None:
selfcal_field_id = list(map(int, os.getenv('SELFCAL_FIELD_ID').split(",")))
logprint("Using selfcal_field_id = {0}".format(selfcal_field_id),
origin='contim_selfcal')
else:
selfcal_field_id = None
elif selfcal_field_id is not None:
if not isinstance(selfcal_field_id, list):
selfcal_field_id = [selfcal_field_id]
for entry in selfcal_field_id:
assert isinstance(entry,int), "{0} is not an int".format(entry)
logprint("Using selfcal_field_id = {0}".format(selfcal_field_id),
origin='contim_selfcal')
logprint("Beginning selfcal script with exclude_7m={0} and only_7m={1}".format(exclude_7m, only_7m),
origin='contim_selfcal')
for scigoal in science_goal_dirs:
for group in glob.glob(scigoal + "/*"):
for member in glob.glob(os.path.join(group, "*")):
dirpath = member
scriptsforpi = glob.glob(
os.path.join(dirpath, "script/*scriptForPI.py"))
if len(scriptsforpi) == 1:
scriptforpi = scriptsforpi[0]
elif len(scriptsforpi) > 1:
raise ValueError(
"Too many scripts for PI in {0}".format(dirpath))
elif len(scriptsforpi) == 0:
logprint(
"Skipping directory {0} because it has no scriptForPI".
format(dirpath))
continue
curdir = os.getcwd()
if os.path.exists(os.path.join(dirpath, 'calibrated')):
logprint("Skipping script {0} in {1} because calibrated "
"exists".format(scriptforpi, dirpath),
origin='pipeline_runner')
elif os.path.exists(os.path.join(dirpath, 'calibration')):
os.chdir(os.path.join(dirpath, 'script'))
local_scriptforPI = os.path.basename(scriptforpi)
logprint("Running script {0} in {1}".format(
from metadata_tools import determine_imsize, determine_phasecenter, logprint
from tasks import tclean, exportfits, plotms
from taskinit import msmdtool
msmd = msmdtool()
imaging_root = "imaging_results"
if not os.path.exists(imaging_root):
os.mkdir(imaging_root)
if 'exclude_7m' not in locals():
if os.getenv('EXCLUDE_7M'):
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
else:
exclude_7m = False
logprint("exclude_7m={0}".format(exclude_7m), origin='almaimf_contimg_both')
# load the list of continuum MSes from a file
# (this file has one continuum MS full path, e.g. /path/to/file.ms, per line)
with open('continuum_mses.txt', 'r') as fh:
continuum_mses = [x.strip() for x in fh.readlines()]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
field = basename.split("_")[0]
if exclude_7m:
msmd.open(continuum_ms)
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
else:
exclude_7m = False
if 'only_7m' not in locals():
if os.getenv('ONLY_7M') is not None:
only_7m = bool(os.getenv('ONLY_7M').lower() == 'true')
else:
only_7m = False
if 'selfcal_field_id' not in locals():
if os.getenv('SELFCAL_FIELD_ID') is not None:
selfcal_field_id = list(
map(int,
os.getenv('SELFCAL_FIELD_ID').split(",")))
logprint("Using selfcal_field_id = {0}".format(selfcal_field_id),
origin='contim_selfcal')
else:
selfcal_field_id = None
elif selfcal_field_id is not None:
if not isinstance(selfcal_field_id, list):
selfcal_field_id = [selfcal_field_id]
for entry in selfcal_field_id:
assert isinstance(entry, int), "{0} is not an int".format(entry)
logprint("Using selfcal_field_id = {0}".format(selfcal_field_id),
origin='contim_selfcal')
def sethistory(prefix, selfcalpars=None, impars=None, selfcaliter=None):
for suffix in ('.image.tt0', '.image.tt0.pbcor', '.residual.tt0'):
if os.path.exists(prefix + suffix):
ia.open(prefix + suffix)
def make_custom_mask(fieldname,
imname,
almaimf_code_path,
band_id,
rootdir="",
suffix="",
do_bsens=False):
regfn = os.path.join(
almaimf_code_path,
'clean_regions/{0}_{1}{2}.reg'.format(fieldname, band_id, suffix))
if do_bsens:
regfnbsens = os.path.join(
almaimf_code_path, 'clean_regions/{0}_{1}{2}_bsens.reg'.format(
fieldname, band_id, suffix))
if os.path.exists(regfnbsens):
logprint('Using BSENS region: {0}'.format(regfn))
regfn = regfnbsens
suffix = suffix + '_bsens'
if not os.path.exists(regfn):
raise IOError("Region file {0} does not exist".format(regfn))
regs = regions.read_ds9(regfn)
logprint("Using region file {0} to create mask from image "
"{1}".format(regfn, imname),
origin='make_custom_mask')
cube = SpectralCube.read(imname, format='casa_image')
image = cube[0]
if image.unit.is_equivalent(u.Jy / u.beam):
image = image * u.beam
else:
assert image.unit.is_equivalent(u.Jy), "Image must be in Jansky/beam."
mask_array = np.zeros(image.shape, dtype='bool')
for reg in regs:
threshold = u.Quantity(reg.meta['label'])
assert threshold.unit.is_equivalent(
u.Jy), "Threshold must by in mJy or Jy"
preg = reg.to_pixel(image.wcs)
msk = preg.to_mask()
assert hasattr(image,
'unit'), "Image {imname} failed to have units".format(
imname=imname)
mimg = msk.multiply(image)
assert mimg is not None
assert hasattr(
mimg, 'unit'), "Masked Image {imname} failed to have units".format(
imname=imname)
assert mimg.unit.is_equivalent(u.Jy)
msk.cutout(mask_array)[:] = (mimg > threshold) | msk.cutout(mask_array)
# cutout does some extra check-for-overlap work
#mask_array[msk.bbox.slices] = (msk.multiply(image) > threshold) | mask_array[msk.bbox.slices]
# CASA transposes arrays!!!!!
mask_array = mask_array.T
ia.open(imname)
assert np.all(ia.shape() == mask_array[:, :, None, None].shape
), "Failure: image shape doesn't match mask shape"
cs = ia.coordsys()
ia.close()
maskname = ('{fieldname}_{band_id}{suffix}_mask.mask'.format(
fieldname=fieldname, band_id=band_id, suffix=suffix))
# add a root directory if there is one
# (if rootdir == "", this just returns maskname)
maskname = os.path.join(rootdir, maskname)
assert ia.fromarray(outfile=maskname,
pixels=mask_array.astype('float')[:, :, None, None],
csys=cs.torecord(),
overwrite=True), "FAILURE in final mask creation step"
ia.close()
return maskname
# load in the line parameter info
if line_name not in ('full', ) + spwnames:
linpars = line_parameters[field][line_name]
restfreq = u.Quantity(linpars['restfreq'])
vlsr = u.Quantity(linpars['vlsr'])
# check that the line is in range
ms.open(vis[0])
# assume spw is 0 because we're working on split data
freqs = ms.cvelfreqs(spwids=0, outframe='LSRK') * u.Hz
targetfreq = restfreq * (1 - vlsr / constants.c)
if freqs.min() > targetfreq or freqs.max() < targetfreq:
# Skip this spw: it is not in range
logprint(
"Skipped spectral window {0} for line {1} because it's out of range"
.format(spw, line_name),
origin='almaimf_line_imaging')
continue
else:
logprint("Matched spectral window {0} to line {1}".format(
spw, line_name),
origin='almaimf_line_imaging')
elif line_name in spwnames and line_name.lstrip("spw") != spw:
logprint(
"Skipped spectral window {0} because it's not {1}".format(
spw, line_name),
origin='almaimf_line_imaging')
continue
if exclude_7m:
# don't use variable name 'ms' in python2.7!
if 'exclude_7m' not in locals():
if os.getenv('EXCLUDE_7M') is not None:
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
else:
exclude_7m = False
# load the list of line MSes from a file
# these are all of the individually split windows,.....
with open('to_image.json', 'r') as fh:
to_image = json.load(fh)
for band in to_image:
logprint("Imaging fields {0} in band {1}".format(to_image[band].keys(),
band),
origin='almaimf_fullcont_imaging')
for field in to_image[band]:
# get all spectral windows for a given band (B3 or B6) for a specified
# field. These were split to allow for individual line imaging.
vis = list(
map(str, [
x for spw in to_image[band][field]
for x in to_image[band][field][spw]
]))
logprint("Will image MSes: \n{0}".format("\n".join(vis)),
origin='almaimf_fullcont_imaging')
# strip off .split
return impars
if exclude_7m:
arrayname = '12M'
elif only_7m:
arrayname = '7M'
else:
arrayname = '7M12M'
# global default: only do robust 0 for lines
robust = 0
logprint("Initializing line imaging with global parameters"
" exclude_7m={0}, only_7m={1}, band_list={2}, field_id={3}"
.format(exclude_7m, only_7m, band_list, field_id),
origin='almaimf_line_imaging')
for band in band_list:
for field in to_image[band]:
spwnames = tuple('spw{0}'.format(x) for x in to_image[band][field])
logprint("Found spectral windows {0} in band {1}: field {2}"
.format(to_image[band][field].keys(), band, field),
origin='almaimf_line_imaging')
if max(int(x) for x in to_image[band][field]) > 7:
raise ValueError("Found invalid spw numbers; ALMA-IMF data do not include >8 spws")
for spw in to_image[band][field]:
# python 2.7 specific hack: force 'field' to be a bytestring
# instead of a unicode string (CASA's lower-level functions
# can't accept unicode strings)
imaging_root = "imaging_results"
if not os.path.exists(imaging_root):
os.mkdir(imaging_root)
# set the 'chanchunks' parameter globally.
# CASAguides recommend chanchunks=-1, but this resulted in: 2018-09-05 23:16:34 SEVERE tclean::task_tclean:: Exception from task_tclean : Invalid Gridding/FTM Parameter set : Must have at least 1 chanchunk
chanchunks = os.getenv('CHANCHUNKS') or 16
# global default: only do robust 0 for lines
robust = 0
vis = os.getenv('VIS')
if vis is None:
raise ValueError("VIS not specified")
logprint("Running on vis {0}".format(vis))
ms.open(vis)
spwinfo = ms.getspectralwindowinfo()
spw_list = spwinfo.keys()
logprint("SPWs are {0}".format(spw_list))
field = 'BrickMaser'
for spw in spw_list:
if spwinfo[spw]['ChanWidth'] < 0:
reference_frequency = spwinfo[spw][
'RefFreq'] - spwinfo[spw]['ChanWidth'] * spwinfo[spw]['NumChan']
else:
reference_frequency = spwinfo[spw]['RefFreq']
freqname = int(reference_frequency / 1e9)
if not os.path.exists(imaging_root):
os.mkdir(imaging_root)
if 'exclude_7m' not in locals():
if os.getenv('EXCLUDE_7M') is not None:
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
else:
exclude_7m = False
if 'only_7m' not in locals():
if os.getenv('ONLY_7M') is not None:
only_7m = bool(os.getenv('ONLY_7M').lower() == 'true')
else:
only_7m = False
logprint("Beginning selfcal script with exclude_7m={0} and only_7m={1}".format(exclude_7m, only_7m),
origin='contim_selfcal')
# load the list of continuum MSes from a file
# (this file has one continuum MS full path, e.g. /path/to/file.ms, per line)
with open('continuum_mses.txt', 'r') as fh:
continuum_mses = [x.strip() for x in fh.readlines()]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
band = 'B3' if 'B3' in basename else 'B6' if 'B6' in basename else 'ERROR'
# allow optional cmdline args to skip one or the other band
x.replace('_continuum_merged.cal.ms', 'continuum_merged_bsens.cal.ms')
for x in continuum_mses
]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
band = 'B3' if 'B3' in basename else 'B6' if 'B6' in basename else 'ERROR'
# allow optional cmdline args to skip one or the other band
if os.getenv('BAND_TO_IMAGE'):
if band not in os.getenv('BAND_TO_IMAGE'):
logprint("Skipping band {0} because it is not in {1}".format(
band, os.getenv('BAND_TO_IMAGE')),
origin='almaimf_cont_imaging')
continue
logprint("Imaging only band {0}".format(os.getenv('BAND_TO_IMAGE')),
origin='almaimf_cont_imaging')
field = basename.split("_")[0]
if os.getenv('FIELD_ID'):
if field not in os.getenv('FIELD_ID'):
logprint("Skipping {0} because it is not in FIELD_ID={1}".format(
field, os.getenv('FIELD_ID')))
continue
suffix = "_bsens" if "bsens" in continuum_ms else ""
line_name = os.getenv('LINE_NAME').lower()
else:
raise ValueError("line_name was not defined")
# set the 'chanchunks' parameter globally.
# CASAguides recommend chanchunks=-1, but this resulted in: 2018-09-05 23:16:34 SEVERE tclean::task_tclean:: Exception from task_tclean : Invalid Gridding/FTM Parameter set : Must have at least 1 chanchunk
chanchunks = int(os.getenv('CHANCHUNKS') or 16)
# global default: only do robust 0 for lines
robust = 0
for band in band_list:
for field in to_image[band]:
spwnames = tuple('spw{0}'.format(x) for x in to_image[band][field])
logprint("Found spectral windows {0} in band {1}: field {2}".format(
to_image[band][field].keys(), band, field),
origin='almaimf_line_imaging')
for spw in to_image[band][field]:
# python 2.7 specific hack: force 'field' to be a bytestring
# instead of a unicode string (CASA's lower-level functions
# can't accept unicode strings)
field = str(field)
spw = str(spw)
band = str(band)
vis = list(map(str, to_image[band][field][spw]))
# load in the line parameter info
if line_name not in ('full', ) + spwnames:
linpars = line_parameters[field][line_name]
for field in to_image[band]:
for spw in to_image[band][field]:
vis = list(map(str, to_image[band][field][spw]))
if exclude_7m:
vis = [ms for ms in vis if not (is_7m(ms))]
suffix = '12M'
else:
suffix = '7M12M'
lineimagename = os.path.join(
imaging_root,
"{0}_{1}_spw{2}_{3}_lines".format(field, band, spw, suffix))
logprint(str(vis), origin='almaimf_line_imaging')
coosys, racen, deccen = determine_phasecenter(ms=vis, field=field)
phasecenter = "{0} {1}deg {2}deg".format(coosys, racen, deccen)
(dra, ddec, pixscale) = list(
determine_imsize(
ms=vis[0],
field=field,
phasecenter=(racen, deccen),
spw=0,
pixfraction_of_fwhm=1 / 3.,
exclude_7m=exclude_7m,
min_pixscale=0.1, # arcsec
))
imsize = [dra, ddec]
cellsize = ['{0:0.2f}arcsec'.format(pixscale)] * 2
def create_clean_model(
cubeimagename,
contimagename,
imaging_results_path,
contmodel_path=None,
):
#results_path = "./imaging_results/" # imaging_results frmo the pipeline
#contmodel_path = "./imaging_results_test_casatools/" #Path with input and temporary continuum models
if contmodel_path is None:
contmodel_path = imaging_results_path
# Create continuum_model.image.tt0 and .tt1 regridded to the cube spatial frame, but still with 1 spectral pix
tt0name = "{contmodelpath}/{contimagename}.model.tt0".format(
contimagename=contimagename, contmodelpath=contmodel_path)
tt1name = "{contmodelpath}/{contimagename}.model.tt1".format(
contimagename=contimagename, contmodelpath=contmodel_path)
if not os.path.exists(tt0name):
raise IOError(
"Continuum startmodel file {0} does not exist".format(tt0name))
temp_dict_cont_tt0 = imregrid(imagename=tt0name, template="get")
# not needed temp_dict_cont_tt1 = imregrid(imagename=tt1name, template="get")
# image has to exist, model should not exist!
# (if you ran tclean with niter=0, no model is created)
cubeinimagepath = ("{results_path}/{cubeimagename}.image".format(
results_path=imaging_results_path, cubeimagename=cubeimagename))
cubeoutmodelpath = ("{results_path}/{cubeimagename}.contcube.model".format(
results_path=imaging_results_path, cubeimagename=cubeimagename))
if not os.path.exists(cubeinimagepath):
raise IOError("Continuum startmodel file {0} does not exist".format(
cubeinimagepath))
temp_dict_line = imregrid(imagename=cubeinimagepath, template="get")
temp_dict_line['shap'][-1] = 1
temp_dict_line['csys']['spectral2'] = temp_dict_cont_tt0['csys'][
'spectral2']
temp_dict_line['csys']['worldreplace2'] = temp_dict_cont_tt0['csys'][
'worldreplace2']
tt0model = (
"{contmodel_path}/{cubeimagename}_continuum_model.image.tt0".format(
contmodel_path=contmodel_path, cubeimagename=cubeimagename))
tt1model = (
"{contmodel_path}/{cubeimagename}_continuum_model.image.tt1".format(
contmodel_path=contmodel_path, cubeimagename=cubeimagename))
imregrid(imagename=tt0name,
output=tt0model,
template=temp_dict_line,
overwrite=True)
imregrid(imagename=tt1name,
output=tt1model,
template=temp_dict_line,
overwrite=True)
# Use CASA tools to create a model cube from the continuum model
if os.path.exists(cubeoutmodelpath):
shutil.rmtree(cubeoutmodelpath)
shutil.copytree(cubeinimagepath, cubeoutmodelpath)
dict_line = imregrid(imagename=cubeoutmodelpath, template="get")
line_im = ia.newimagefromfile(cubeoutmodelpath)
#print(line_im.shape())
tt0_im = ia.newimagefromfile(tt0model)
#print(tt0_im.shape())
tt0_pixvalues = tt0_im.getchunk()
tt0_im.close()
tt1_im = ia.newimagefromfile(tt1model)
#print(tt1_im.shape())
tt1_pixvalues = tt1_im.getchunk()
tt1_im.close()
# From Eq. 2 of Rau & Cornwell (2011)
# temp_dict_cont_tt0['csys']['spectral2']['wcs']
# dict_line['csys']['spectral2']['wcs']
# dnu_plane: dnu with respect to cube reference freq.
# dnu: dnu with respect to tt0 continuum reference
for plane in range(dict_line['shap'][-1]):
logprint('Calculating continuum model for plane {}'.format(plane))
dnu_plane = (plane - dict_line['csys']['spectral2']['wcs']['crpix']
) * dict_line['csys']['spectral2']['wcs']['cdelt']
nu_plane = dict_line['csys']['spectral2']['wcs']['crval'] + dnu_plane
#print(dnu_plane, nu_plane)
factor = (nu_plane -
temp_dict_cont_tt0['csys']['spectral2']['wcs']['crval']
) / temp_dict_cont_tt0['csys']['spectral2']['wcs']['crval']
#print(factor)
plane_pixvalues = tt0_pixvalues + factor * tt1_pixvalues
blc = [0, 0, 0, plane]
#trc = [line_im.shape()[0]-1, line_im.shape()[1]-1, 0, plane]
line_im.putchunk(plane_pixvalues, blc=blc, replicate=False)
line_im.close()
return cubeoutmodelpath
# Commented block is for the case where only tt0 info is used
'''
if exclude_7m:
vis = [ms for ms in vis if not(is_7m(ms))]
arrayname = '12M'
else:
arrayname = '7M12M'
lineimagename = os.path.join(imaging_root,
"{0}_{1}_spw{2}_{3}_lines".format(field,
band,
spw,
arrayname))
logprint(str(vis), origin='almaimf_line_imaging')
coosys,racen,deccen = determine_phasecenter(ms=vis, field=field)
phasecenter = "{0} {1}deg {2}deg".format(coosys, racen, deccen)
(dra,ddec,pixscale) = list(determine_imsizes(mses=vis, field=field,
phasecenter=(racen,deccen),
spw=0, pixfraction_of_fwhm=1/3.,
exclude_7m=exclude_7m,
min_pixscale=0.1, # arcsec
))
imsize = [int(dra), int(ddec)]
cellsize = ['{0:0.2f}arcsec'.format(pixscale)] * 2
dirty_tclean_made_residual = False
# start with cube imaging
# split out the 12M-only data to make further processing slightly
# faster
new_continuum_ms = continuum_ms.replace(".cal.ms", "_12M.cal.ms")
split(vis=continuum_ms, outputvis=new_continuum_ms, antenna=antennae,
field=field, datacolumn='data')
continuum_ms = new_continuum_ms
else:
antennae = ""
arrayname = '7M12M'
if os.getenv("USE_SELFCAL_MS"):
selfcal_ms = basename+"_"+arrayname+"_selfcal.ms"
continuum_ms = selfcal_ms
logprint("Imaging MS {0} with array {1}".format(continuum_ms, arrayname),
origin='almaimf_cont_imaging')
coosys,racen,deccen = determine_phasecenter(ms=continuum_ms, field=field)
phasecenter = "{0} {1}deg {2}deg".format(coosys, racen, deccen)
(dra,ddec,pixscale) = list(determine_imsize(ms=continuum_ms, field=field,
phasecenter=(racen,deccen),
exclude_7m=exclude_7m,
spw=0, pixfraction_of_fwhm=1/4.))
imsize = [dra, ddec]
cellsize = ['{0:0.2f}arcsec'.format(pixscale)] * 2
contimagename = os.path.join(imaging_root, basename) + "_" + arrayname
# SKIP the plot
#if not os.path.exists(contimagename+".uvwave_vs_amp.png"):
# # make a diagnostic plot to show the UV distribution
import json
from metadata_tools import determine_imsize, determine_phasecenter, logprint
from tasks import tclean, exportfits, plotms, imstat, makemask
from taskinit import msmdtool
from taskinit import iatool
msmd = msmdtool()
ia = iatool()
imaging_root = "imaging_results"
if not os.path.exists(imaging_root):
os.mkdir(imaging_root)
if 'exclude_7m' not in locals():
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
logprint("exclude_7m={0}".format(exclude_7m),
origin='almaimf_cont_3sigtemplate')
# load the list of continuum MSes from a file
# (this file has one continuum MS full path, e.g. /path/to/file.ms, per line)
with open('continuum_mses.txt', 'r') as fh:
continuum_mses = [x.strip() for x in fh.readlines()]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
field = basename.split("_")[0]
if exclude_7m:
msmd.open(continuum_ms)
os.mkdir(imaging_root)
if 'exclude_7m' not in locals():
if os.getenv('EXCLUDE_7M') is not None:
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
else:
exclude_7m = False
if 'only_7m' not in locals():
if os.getenv('ONLY_7M') is not None:
only_7m = bool(os.getenv('ONLY_7M').lower() == 'true')
else:
only_7m = False
logprint("Beginning selfcal script with exclude_7m={0} and only_7m={1}".format(
exclude_7m, only_7m),
origin='contim_selfcal')
# load the list of continuum MSes from a file
# (this file has one continuum MS full path, e.g. /path/to/file.ms, per line)
with open('continuum_mses.txt', 'r') as fh:
continuum_mses = [x.strip() for x in fh.readlines()]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
band = 'B3' if 'B3' in basename else 'B6' if 'B6' in basename else 'ERROR'
# allow optional cmdline args to skip one or the other band
msmd = msmdtool()
ia = iatool()
imaging_root = "imaging_results"
if not os.path.exists(imaging_root):
os.mkdir(imaging_root)
if 'exclude_7m' not in locals():
if os.getenv('EXCLUDE_7M') is not None:
exclude_7m = bool(os.getenv('EXCLUDE_7M').lower() == 'true')
arrayname = '12M'
else:
exclude_7m = False
arrayname = '7M12M'
logprint("Beginning selfcal script with exclude_7m={0}".format(exclude_7m),
origin='contim_selfcal')
# load the list of continuum MSes from a file
# (this file has one continuum MS full path, e.g. /path/to/file.ms, per line)
with open('continuum_mses.txt', 'r') as fh:
continuum_mses = [x.strip() for x in fh.readlines()]
for continuum_ms in continuum_mses:
# strip off .cal.ms
basename = os.path.split(continuum_ms[:-7])[1]
band = 'B3' if 'B3' in basename else 'B6' if 'B6' in basename else 'ERROR'
# allow optional cmdline args to skip one or the other band
if os.getenv('BAND_TO_IMAGE'):
