def test_restored_list_facet(self):
self.actualSetUp(zerow=True)
centre = self.freqwin // 2
psf_image_list = invert_list_rsexecute_workflow(self.vis_list, self.model_list, context='2d', dopsf=True)
residual_image_list = residual_list_rsexecute_workflow(self.vis_list, self.model_list, context='2d')
restored_4facets_image_list = restore_list_rsexecute_workflow(self.model_list, psf_image_list,
residual_image_list,
restore_facets=4, psfwidth=1.0)
restored_4facets_image_list = rsexecute.compute(restored_4facets_image_list, sync=True)
restored_1facets_image_list = restore_list_rsexecute_workflow(self.model_list, psf_image_list,
residual_image_list,
restore_facets=1, psfwidth=1.0)
restored_1facets_image_list = rsexecute.compute(restored_1facets_image_list, sync=True)
if self.persist: export_image_to_fits(restored_4facets_image_list[0],
'%s/test_imaging_invert_%s_restored_4facets.fits' %
(self.dir, rsexecute.type()))
qa = qa_image(restored_4facets_image_list[centre])
assert numpy.abs(qa.data['max'] - 99.43438263927833) < 1e-7, str(qa)
assert numpy.abs(qa.data['min'] + 0.6328915148563354) < 1e-7, str(qa)
restored_4facets_image_list[centre].data -= restored_1facets_image_list[centre].data
if self.persist: export_image_to_fits(restored_4facets_image_list[centre],
'%s/test_imaging_invert_%s_restored_4facets_error.fits' %
(self.dir, rsexecute.type()))
qa = qa_image(restored_4facets_image_list[centre])
assert numpy.abs(qa.data['max']) < 1e-10, str(qa)
def test_deconvolve_and_restore_cube_mmclean_facets(self):
self.actualSetUp(add_errors=True)
dirty_imagelist = invert_list_rsexecute_workflow(self.vis_list, self.model_imagelist, context='2d',
dopsf=False, normalize=True)
psf_imagelist = invert_list_rsexecute_workflow(self.vis_list, self.model_imagelist, context='2d',
dopsf=True, normalize=True)
dirty_imagelist = rsexecute.persist(dirty_imagelist)
psf_imagelist = rsexecute.persist(psf_imagelist)
dec_imagelist = deconvolve_list_rsexecute_workflow(dirty_imagelist, psf_imagelist, self.model_imagelist,
niter=1000,
fractional_threshold=0.1, scales=[0, 3, 10],
algorithm='mmclean', nmoment=3, nchan=self.freqwin,
threshold=0.01, gain=0.7, deconvolve_facets=8,
deconvolve_overlap=8, deconvolve_taper='tukey')
dec_imagelist = rsexecute.persist(dec_imagelist)
residual_imagelist = residual_list_rsexecute_workflow(self.vis_list, model_imagelist=dec_imagelist,
context='2d')
residual_imagelist = rsexecute.persist(residual_imagelist)
restored_list = restore_list_rsexecute_workflow(model_imagelist=dec_imagelist, psf_imagelist=psf_imagelist,
residual_imagelist=residual_imagelist,
empty=self.model_imagelist)
restored = rsexecute.compute(restored_list, sync=True)[0]
if self.persist: export_image_to_fits(restored, '%s/test_imaging_%s_overlap_mmclean_restored.fits'
% (self.dir, rsexecute.type()))
def _invert_base(self,
context,
extra='',
fluxthreshold=1.0,
positionthreshold=1.0,
check_components=True,
facets=1,
vis_slices=1,
gcfcf=None,
dopsf=False,
**kwargs):
centre = self.freqwin // 2
dirty = invert_list_rsexecute_workflow(self.bvis_list,
self.model_list,
context=context,
dopsf=dopsf,
normalize=True,
facets=facets,
vis_slices=vis_slices,
gcfcf=gcfcf,
**kwargs)
dirty = rsexecute.compute(dirty, sync=True)[centre]
if self.persist:
if dopsf == True:
export_image_to_fits(
dirty[0], '%s/test_imaging_invert_%s%s_%s_psf.fits' %
(self.dir, context, extra, rsexecute.type()))
else:
export_image_to_fits(
dirty[0], '%s/test_imaging_invert_%s%s_%s_dirty.fits' %
(self.dir, context, extra, rsexecute.type()))
assert numpy.max(numpy.abs(dirty[0].data)), "Image is empty"
if check_components:
self._checkcomponents(dirty[0], fluxthreshold, positionthreshold)
def test_restored_list_noresidual(self):
self.actualSetUp(zerow=True)
centre = self.freqwin // 2
psf_image_list = invert_list_rsexecute_workflow(self.vis_list, self.model_list, context='2d', dopsf=True)
restored_image_list = restore_list_rsexecute_workflow(self.model_list, psf_image_list, psfwidth=1.0)
restored_image_list = rsexecute.compute(restored_image_list, sync=True)
if self.persist: export_image_to_fits(restored_image_list[centre],
'%s/test_imaging_invert_%s_restored_noresidual.fits' %
(self.dir, rsexecute.type()))
qa = qa_image(restored_image_list[centre])
assert numpy.abs(qa.data['max'] - 100.0) < 1e-7, str(qa)
assert numpy.abs(qa.data['min']) < 1e-7, str(qa)
def test_deconvolve_spectral(self):
self.actualSetUp(add_errors=True)
dirty_imagelist = invert_list_rsexecute_workflow(self.vis_list, self.model_imagelist, context='2d',
dopsf=False, normalize=True)
psf_imagelist = invert_list_rsexecute_workflow(self.vis_list, self.model_imagelist,
context='2d',
dopsf=True, normalize=True)
dirty_imagelist = rsexecute.persist(dirty_imagelist)
psf_imagelist = rsexecute.persist(psf_imagelist)
deconvolved = deconvolve_list_rsexecute_workflow(dirty_imagelist, psf_imagelist, self.model_imagelist,
niter=1000,
fractional_threshold=0.1, scales=[0, 3, 10],
threshold=0.1, gain=0.7)
deconvolved = rsexecute.persist(deconvolved)
deconvolved = rsexecute.compute(deconvolved, sync=True)
if self.persist: export_image_to_fits(deconvolved[0], '%s/test_imaging_%s_deconvolve_spectral.fits' %
(self.dir, rsexecute.type()))
def _predict_base(self, context='2d', extra='', fluxthreshold=1.0, facets=1, vis_slices=1,
gcfcf=None, **kwargs):
centre = self.freqwin // 2
vis_list = zero_list_rsexecute_workflow(self.vis_list)
vis_list = predict_list_rsexecute_workflow(vis_list, self.model_list, context=context,
vis_slices=vis_slices, facets=facets,
gcfcf=gcfcf, **kwargs)
vis_list = subtract_list_rsexecute_workflow(self.vis_list, vis_list)
vis_list = rsexecute.compute(vis_list, sync=True)
dirty = invert_list_rsexecute_workflow(vis_list, self.model_list, context=context, dopsf=False,
gcfcf=gcfcf, normalize=True, vis_slices=vis_slices)
dirty = rsexecute.compute(dirty, sync=True)[centre]
assert numpy.max(numpy.abs(dirty[0].data)), "Residual image is empty"
if self.persist: export_image_to_fits(dirty[0], '%s/test_imaging_predict_%s%s_%s_dirty.fits' %
(self.dir, context, extra, rsexecute.type()))
maxabs = numpy.max(numpy.abs(dirty[0].data))
assert maxabs < fluxthreshold, "Error %.3f greater than fluxthreshold %.3f " % (maxabs, fluxthreshold)
