def make_casa_testimage(infile, outname):
if not casaOK:
raise Exception("Attempted to make a CASA test image in a non-CASA "
"environment")
ia.fromfits(infile=infile, outfile=outname, overwrite=True)
ia.close()
cube = SpectralCube.read(infile)
if isinstance(cube, VaryingResolutionSpectralCube):
ia.open(outname)
# populate restoring beam emptily
ia.setrestoringbeam(major={'value':1.0, 'unit':'arcsec'},
minor={'value':1.0, 'unit':'arcsec'},
pa={'value':90.0, 'unit':'deg'},
channel=len(cube.beams)-1,
polarization=-1,
)
# populate each beam (hard assumption of 1 poln)
for channum, beam in enumerate(cube.beams):
casabdict = {'major': {'value':beam.major.to(u.deg).value, 'unit':'deg'},
'minor': {'value':beam.minor.to(u.deg).value, 'unit':'deg'},
'positionangle': {'value':beam.pa.to(u.deg).value, 'unit':'deg'}
}
ia.setrestoringbeam(beam=casabdict, channel=channum, polarization=0)
ia.close()
def make_casa_testimage(infile, outname):
infile = str(infile)
outname = str(outname)
if not casaOK:
raise Exception("Attempted to make a CASA test image in a non-CASA "
"environment")
ia = casatools.image()
ia.fromfits(infile=infile, outfile=outname, overwrite=True)
ia.unlock()
ia.close()
ia.done()
cube = SpectralCube.read(infile)
if isinstance(cube, VaryingResolutionSpectralCube):
ia.open(outname)
# populate restoring beam emptily
ia.setrestoringbeam(
major={
'value': 1.0,
'unit': 'arcsec'
},
minor={
'value': 1.0,
'unit': 'arcsec'
},
pa={
'value': 90.0,
'unit': 'deg'
},
channel=len(cube.beams) - 1,
polarization=-1,
)
# populate each beam (hard assumption of 1 poln)
for channum, beam in enumerate(cube.beams):
casabdict = {
'major': {
'value': beam.major.to(u.deg).value,
'unit': 'deg'
},
'minor': {
'value': beam.minor.to(u.deg).value,
'unit': 'deg'
},
'positionangle': {
'value': beam.pa.to(u.deg).value,
'unit': 'deg'
}
}
ia.setrestoringbeam(beam=casabdict,
channel=channum,
polarization=0)
ia.unlock()
ia.close()
ia.done()
def make_casa_testimage(infile, outname):
ia.fromfits(infile=infile, outfile=outname, overwrite=True)
ia.close()
def make_casa_mask(SpecCube,
outname,
append_to_image=True,
img=None,
add_stokes=True,
stokes_posn=None):
'''
Outputs the mask attached to the SpectralCube object as a CASA image, or
optionally appends the mask to a preexisting CASA image.
Parameters
----------
SpecCube : SpectralCube
SpectralCube object containing mask.
outname : str
Name of the outputted mask file.
append_to_image : bool, optional
Appends the mask to a given image.
img : str, optional
Image to be appended to. Must be specified if append_to_image is
enabled.
add_stokes: bool, optional
Adds a Stokes axis onto the wcs from SpecCube.
stokes_posn : int, optional
Sets the position of the new Stokes axis. Defaults to the last axis.
'''
try:
from taskinit import ia
except ImportError:
print("Cannot import casac. Must be run in a CASA environment.")
# Get the header info from the image
# There's not wcs_astropy2casa (yet), so create a temporary file for
# CASA to open.
temp = tempfile.NamedTemporaryFile()
# CASA is closing this file at some point so set it to manual delete.
temp2 = tempfile.NamedTemporaryFile(delete=False)
# Grab wcs
# Optionally re-add on the Stokes axis
if add_stokes:
my_wcs = SpecCube.wcs
if stokes_posn is None:
stokes_posn = my_wcs.wcs.naxis
new_wcs = add_stokes_axis_to_wcs(my_wcs, stokes_posn)
header = new_wcs.to_header()
# Transpose the shape so we're adding the axis at the place CASA will
# recognize. Then transpose back.
shape = SpecCube.shape[::-1]
shape = shape[:stokes_posn] + (1, ) + shape[stokes_posn:]
shape = shape[::-1]
else:
# Just grab the header from SpecCube
header = SpecCube.header
shape = SpecCube.shape
hdu = fits.PrimaryHDU(header=header, data=np.empty(shape, dtype='int16'))
hdu.writeto(temp.name)
ia.fromfits(infile=temp.name, outfile=temp2.name, overwrite=True)
temp.close()
cs = ia.coordsys()
ia.close()
temp2.close()
mask_arr = SpecCube.mask.include()
# Reshape mask with possible Stokes axis
mask_arr = mask_arr.reshape(shape)
# Transpose to match CASA axes
mask_arr = mask_arr.T
ia.newimagefromarray(outfile=outname, pixels=mask_arr.astype('int16'))
ia.open(outname)
ia.setcoordsys(cs.torecord())
ia.close()
if append_to_image:
if img is None:
raise TypeError(
"img argument must be specified to append the mask.")
ia.open(outname)
ia.calcmask(outname + ">0.5")
ia.close()
ia.open(img)
ia.maskhandler('copy', [outname + ":mask0", outname])
ia.maskhandler('set', outname)
ia.close()
def make_casa_mask(SpecCube, outname, append_to_image=True,
img=None, add_stokes=True, stokes_posn=None):
'''
Outputs the mask attached to the SpectralCube object as a CASA image, or
optionally appends the mask to a preexisting CASA image.
Parameters
----------
SpecCube : SpectralCube
SpectralCube object containing mask.
outname : str
Name of the outputted mask file.
append_to_image : bool, optional
Appends the mask to a given image.
img : str, optional
Image to be appended to. Must be specified if append_to_image is
enabled.
add_stokes: bool, optional
Adds a Stokes axis onto the wcs from SpecCube.
stokes_posn : int, optional
Sets the position of the new Stokes axis. Defaults to the last axis.
'''
try:
from taskinit import ia
except ImportError:
print("Cannot import casac. Must be run in a CASA environment.")
# Get the header info from the image
# There's not wcs_astropy2casa (yet), so create a temporary file for
# CASA to open.
temp = tempfile.NamedTemporaryFile()
# CASA is closing this file at some point so set it to manual delete.
temp2 = tempfile.NamedTemporaryFile(delete=False)
# Grab wcs
# Optionally re-add on the Stokes axis
if add_stokes:
my_wcs = SpecCube.wcs
if stokes_posn is None:
stokes_posn = my_wcs.wcs.naxis
new_wcs = add_stokes_axis_to_wcs(my_wcs, stokes_posn)
header = new_wcs.to_header()
# Transpose the shape so we're adding the axis at the place CASA will
# recognize. Then transpose back.
shape = SpecCube.shape[::-1]
shape = shape[:stokes_posn] + (1,) + shape[stokes_posn:]
shape = shape[::-1]
else:
# Just grab the header from SpecCube
header = SpecCube.header
shape = SpecCube.shape
hdu = fits.PrimaryHDU(header=header,
data=np.empty(shape, dtype='int16'))
hdu.writeto(temp.name)
ia.fromfits(infile=temp.name, outfile=temp2.name, overwrite=True)
temp.close()
cs = ia.coordsys()
ia.close()
temp2.close()
mask_arr = SpecCube.mask.include()
# Reshape mask with possible Stokes axis
mask_arr = mask_arr.reshape(shape)
# Transpose to match CASA axes
mask_arr = mask_arr.T
ia.newimagefromarray(outfile=outname,
pixels=mask_arr.astype('int16'))
ia.open(outname)
ia.setcoordsys(cs.torecord())
ia.close()
if append_to_image:
if img is None:
raise TypeError("img argument must be specified to append the mask.")
ia.open(outname)
ia.calcmask(outname+">0.5")
ia.close()
ia.open(img)
ia.maskhandler('copy', [outname+":mask0", outname])
ia.maskhandler('set', outname)
ia.close()
def make_casa_testimage(infile, outname):
ia.fromfits(infile=infile, outfile=outname, overwrite=True)
ia.close()
