# create a mask based on region selection (no thresholding here)
dirtyimagename = imagename+".image.tt0.pbcor"
exportfits(dirtyimagename, dirtyimagename+".fits", overwrite=True)
reg = pyregion.open('cleanbox_regions_SgrB2.reg')
imghdu = fits.open(dirtyimagename+".fits")[0]
#mask = reg.get_mask(imghdu)[None, None, :, :]
mask = reg.get_mask(header=wcs.WCS(imghdu.header).celestial.to_header(),
shape=imghdu.data.shape[2:])
imghdu.data = mask.astype('int16')
imghdu.header['BITPIX'] = 16
imghdu.writeto('cleanbox_mask_SgrB2.fits', clobber=True)
cleanbox_mask_image = 'cleanbox_mask_SgrB2.image'
importfits(fitsimage='cleanbox_mask_SgrB2.fits',
imagename=cleanbox_mask_image,
overwrite=True)
ia.open(cleanbox_mask_image)
ia.calcmask(mask=cleanbox_mask_image+" > 0.5",
name='cleanbox_mask')
ia.close()
cleanbox_mask = 'cleanbox_mask.mask'
makemask(mode='copy', inpimage=cleanbox_mask_image,
inpmask=cleanbox_mask_image+":cleanbox_mask",
output=cleanbox_mask,
overwrite=True)
mask = cleanbox_mask_image
def reg_to_mask(regfile, baseimage):
"""
This is like makemask(mode='copy', inpimage=baseimage, inpmask=regfile)
"""
casalog.post("Creating mask from regions {0} into base image {1}".format(
regfile, baseimage),
origin='reg_to_mask')
assert baseimage.endswith('.image') or baseimage.endswith('.image.tt0')
cleanbox_mask = baseimage.replace(".image.tt0",
".image").replace(".image", ".mask")
cleanbox_mask_image = baseimage
if not os.path.exists(cleanbox_mask) or not os.path.exists(
cleanbox_mask_image):
# create a mask based on region selection (no thresholding here)
dirtyimagename = baseimage
exportfits(dirtyimagename, dirtyimagename + ".fits", overwrite=True)
reg = regions.read_ds9(regfile)
imghdu = fits.open(dirtyimagename + ".fits")[0]
assert imghdu.data.shape[-1] != 1
assert imghdu.data.shape[-2] != 1
mask = get_mask(reg, imghdu)
assert mask.shape[0] > 1
assert mask.shape[1] > 1
assert mask.size > 1
imghdu.data = mask.astype('int16')
imghdu.header['BITPIX'] = 16
imghdu.writeto(cleanbox_mask + '.fits', clobber=True)
importfits(fitsimage=cleanbox_mask + '.fits',
imagename=cleanbox_mask_image,
overwrite=True)
ia.open(cleanbox_mask_image)
ia.calcmask(mask="'{0}' > 0.5".format(cleanbox_mask_image),
name='cleanbox_mask')
ia.close()
makemask(mode='copy',
inpimage=cleanbox_mask_image,
inpmask=cleanbox_mask_image + ":cleanbox_mask",
output=cleanbox_mask,
overwrite=True)
mask = cleanbox_mask
ia.open(mask)
stats = ia.statistics()
ia.close()
casalog.post("Resulting mask file is {0}".format(mask),
origin='reg_to_mask')
casalog.post("Mask sum = {0} out of {1}, or {2}%".format(
stats['sum'], stats['npts'], stats['sum'] / stats['npts'] * 100),
origin='reg_to_mask')
return mask
"""
fh0 = fits.open('../continuum/18A-229_mosaic_for_selfcal.model.tt0.fits')
fh1 = fits.open('../continuum/18A-229_mosaic_for_selfcal.model.tt1.fits')
bad = fh0[0].data < 0
fh0[0].data[bad] = 0
fh1[0].data[bad] = 0
fh0.writeto('../continuum/18A-229_mosaic_for_selfcal.model.tt0.noneg.fits',
overwrite=True)
fh1.writeto('../continuum/18A-229_mosaic_for_selfcal.model.tt1.noneg.fits',
overwrite=True)
importfits(
fitsimage=
'../continuum/18A-229_mosaic_for_selfcal.model.tt0.noneg.fits',
imagename='../continuum/18A-229_mosaic_for_selfcal.model.tt0.noneg',
defaultaxes=True,
defaultaxesvalues=[
fh0[0].header['CRVAL1'], fh0[0].header['CRVAL2'],
'4.59132771e+10Hz', 'I'
],
overwrite=True)
importfits(
fitsimage=
'../continuum/18A-229_mosaic_for_selfcal.model.tt1.noneg.fits',
imagename='../continuum/18A-229_mosaic_for_selfcal.model.tt1.noneg',
defaultaxes=True,
defaultaxesvalues=[
fh0[0].header['CRVAL1'], fh0[0].header['CRVAL2'],
'4.59132771e+10Hz', 'I'
],
overwrite=True)
imhead(
specmode='mfs',
deconvolver='mtmfs',
outframe='LSRK',
savemodel='none',
scales=[0, 3, 9, 27],
nterms=2,
selectdata=True,
)
makefits(imagename)
if not os.path.exists('cleanbox_mask_{0}.fits'.format(field_nospace)):
dirtyimage = imagename + '.image.tt0.pbcor'
if not os.path.exists(dirtyimage):
if os.path.exists(dirtyimage + ".fits"):
importfits(fitsimage=dirtyimage + ".fits",
imagename=dirtyimage)
else:
raise IOError("Missing dirty image file & dirty FITS image")
ia.open(dirtyimage)
ia.calcmask(mask=dirtyimage +
" > {0}".format(mask_threshold[field] / 1e3),
name='dirty_mask_{0}'.format(field_nospace))
ia.close()
makemask(mode='copy',
inpimage=dirtyimage,
inpmask=dirtyimage + ":dirty_mask_{0}".format(field_nospace),
output='dirty_mask_{0}.mask'.format(field_nospace),
overwrite=True)
mask = 'dirty_mask_{0}.mask'.format(field_nospace)