def deconvolve(dirty, psf, model, facet, gthreshold, msk=None):
if prefix == '':
lprefix = "subimage %d" % facet
else:
lprefix = "%s, subimage %d" % (prefix, facet)
if nmoment > 0:
moment0 = calculate_image_frequency_moments(dirty)
this_peak = numpy.max(numpy.abs(
moment0.data[0, ...])) / dirty.data.shape[0]
else:
ref_chan = dirty.data.shape[0] // 2
this_peak = numpy.max(numpy.abs(dirty.data[ref_chan, ...]))
if this_peak > 1.1 * gthreshold:
kwargs['threshold'] = gthreshold
result, _ = deconvolve_cube(dirty,
psf,
prefix=lprefix,
mask=msk,
**kwargs)
if result.data.shape[0] == model.data.shape[0]:
result.data += model.data
return result
else:
return copy_image(model)
def deconvolve_subimage(dirty, psf):
assert isinstance(dirty, Image)
assert isinstance(psf, Image)
comp = deconvolve_cube(dirty, psf, **kwargs)
return comp[0]