def deconvolve(d, p, m):
c, resid = deconvolve_cube(d[0],
p[0],
m,
threshold=0.01,
fracthresh=0.01,
window_shape='quarter',
niter=100,
gain=0.1,
algorithm='hogbom-complex')
r = restore_cube(c, p[0], resid)
return r
if __name__ == '__main__':
results_dir = rascil_path('test_results')
bvt = create_blockvisibility_from_ms(rascil_path('data/vis/sim-2.ms'), start_chan=35, end_chan=39)[0]
bvt.configuration.diameter[...] = 35.0
vt = convert_blockvisibility_to_visibility(bvt)
vt = convert_visibility_to_stokes(vt)
a2r = numpy.pi / (180.0 * 3600.0)
model = create_image_from_visibility(vt, cellsize=20.0 * a2r, npixel=512,
polarisation_frame=PolarisationFrame('stokesIQUV'))
dirty, sumwt = invert_list_serial_workflow([vt], [model], context='2d')[0]
psf, sumwt = invert_list_serial_workflow([vt], [model], context='2d', dopsf=True)[0]
export_image_to_fits(dirty, '%s/rascil_imaging_sim_2_dirty.fits' % (results_dir))
export_image_to_fits(psf, '%s/rascil_imaging_sim_2_psf.fits' % (results_dir))
# Deconvolve using msclean
comp, residual = deconvolve_cube(dirty, psf, niter=10000, threshold=0.001,
fractional_threshold=0.001,
algorithm='msclean',
window_shape='quarter', gain=0.7,
scales=[0, 3, 10, 30])
restored = restore_cube(comp, psf, residual)
print(qa_image(restored))
export_image_to_fits(restored, '%s/rascil_imaging_sim_2_restored.fits' % (results_dir))
export_image_to_fits(residual, '%s/rascil_imaging_sim_2_residual.fits' % (results_dir))