def test_griddata_predict_awterm(self):
self.actualSetUp(zerow=False)
make_pb = functools.partial(create_pb_generic,
diameter=35.0,
blockage=0.0,
use_local=False)
pb = make_pb(self.model)
if self.persist:
export_image_to_fits(pb,
"%s/test_gridding_awterm_pb.fits" % self.dir)
gcf, cf = create_awterm_convolutionfunction(self.model,
make_pb=make_pb,
nw=100,
wstep=8.0,
oversampling=16,
support=32,
use_aaf=True)
griddata = create_griddata_from_image(self.model, nw=100, wstep=8.0)
griddata = fft_image_to_griddata(self.model, griddata, gcf)
newvis = degrid_visibility_from_griddata(self.vis,
griddata=griddata,
cf=cf)
qa = qa_visibility(newvis)
assert qa.data['rms'] < 120.0, str(qa)
self.plot_vis(newvis, 'awterm')
def test_griddata_predict_box(self):
self.actualSetUp(zerow=True)
gcf, cf = create_box_convolutionfunction(self.model)
griddata = create_griddata_from_image(self.model)
griddata = fft_image_to_griddata(self.model, griddata, gcf)
newvis = degrid_visibility_from_griddata(self.vis,
griddata=griddata,
cf=cf)
newvis.data['vis'][...] -= self.vis.data['vis'][...]
qa = qa_visibility(newvis)
assert qa.data['rms'] < 46.0, str(qa)
def test_griddata_predict_pswf(self):
self.actualSetUp(zerow=True)
gcf, cf = create_pswf_convolutionfunction(self.model,
support=6,
oversampling=256)
griddata = create_griddata_from_image(self.model)
griddata = fft_image_to_griddata(self.model, griddata, gcf)
newvis = degrid_visibility_from_griddata(self.vis,
griddata=griddata,
cf=cf)
newvis.data['vis'][...] -= self.vis.data['vis'][...]
qa = qa_visibility(newvis)
assert qa.data['rms'] < 0.7, str(qa)
def test_griddata_predict_box(self):
self.actualSetUp(zerow=True, image_pol=PolarisationFrame("stokesIQUV"))
gcf, cf = create_box_convolutionfunction(self.model)
modelIQUV = convert_stokes_to_polimage(self.model,
self.vis.polarisation_frame)
griddata = create_griddata_from_image(modelIQUV, self.vis)
griddata = fft_image_to_griddata(modelIQUV, griddata, gcf)
newvis = degrid_visibility_from_griddata(self.vis,
griddata=griddata,
cf=cf)
newvis.data['vis'][...] -= self.vis.data['vis'][...]
qa = qa_visibility(newvis)
assert qa.data['rms'] < 58.0, str(qa)
def test_griddata_predict_wterm(self):
self.actualSetUp(zerow=False)
gcf, cf = create_awterm_convolutionfunction(self.model,
nw=100,
wstep=10.0,
oversampling=16,
support=32,
use_aaf=True)
griddata = create_griddata_from_image(self.model, nw=100, wstep=10.0)
griddata = fft_image_to_griddata(self.model, griddata, gcf)
newvis = degrid_visibility_from_griddata(self.vis,
griddata=griddata,
cf=cf)
newvis.data['vis'][...] -= self.vis.data['vis'][...]
qa = qa_visibility(newvis)
self.plot_vis(newvis, 'wterm')
assert qa.data['rms'] < 11.0, str(qa)
def predict_2d(vis: Union[BlockVisibility, Visibility],
model: Image,
gcfcf=None,
**kwargs) -> Union[BlockVisibility, Visibility]:
""" Predict using convolutional degridding.
This is at the bottom of the layering i.e. all transforms are eventually expressed in terms of
this function. Any shifting needed is performed here.
:param vis: Visibility to be predicted
:param model: model image
:param gcfcf: (Grid correction function i.e. in image space, Convolution function i.e. in uv space)
:return: resulting visibility (in place works)
"""
if model is None:
return vis
assert isinstance(vis, Visibility) or isinstance(vis, BlockVisibility), vis
_, _, ny, nx = model.data.shape
if gcfcf is None:
gcf, cf = create_pswf_convolutionfunction(
model,
support=get_parameter(kwargs, "support", 8),
oversampling=get_parameter(kwargs, "oversampling", 127))
else:
gcf, cf = gcfcf
griddata = create_griddata_from_image(model, vis)
polmodel = convert_stokes_to_polimage(model, vis.polarisation_frame)
griddata = fft_image_to_griddata(polmodel, griddata, gcf)
if isinstance(vis, Visibility):
vis = degrid_visibility_from_griddata(vis, griddata=griddata, cf=cf)
else:
vis = degrid_blockvisibility_from_griddata(vis,
griddata=griddata,
cf=cf)
# Now we can shift the visibility from the image frame to the original visibility frame
svis = shift_vis_to_image(vis, model, tangent=True, inverse=True)
return svis
def test_griddata_predict_aterm(self):
self.actualSetUp(zerow=True)
make_pb = functools.partial(create_pb_generic,
diameter=35.0,
blockage=0.0,
use_local=False)
griddata = create_griddata_from_image(self.model)
gcf, cf = create_awterm_convolutionfunction(self.model,
make_pb=make_pb,
nw=1,
oversampling=16,
support=32,
use_aaf=True)
griddata = fft_image_to_griddata(self.model, griddata, gcf)
newvis = degrid_visibility_from_griddata(self.vis,
griddata=griddata,
cf=cf)
qa = qa_visibility(newvis)
assert qa.data['rms'] < 120.0, str(qa)
