def ft_cal_sm(ov, sm):
assert isinstance(ov, Visibility), ov
assert isinstance(sm, SkyModel), sm
v = copy_visibility(ov)
v.data['vis'][...] = 0.0 + 0.0j
if len(sm.components) > 0:
if isinstance(sm.mask, Image):
comps = copy_skycomponent(sm.components)
comps = apply_beam_to_skycomponent(comps, sm.mask)
v = predict_skycomponent_visibility(v, comps)
else:
v = predict_skycomponent_visibility(v, sm.components)
if isinstance(sm.image, Image):
if numpy.max(numpy.abs(sm.image.data)) > 0.0:
if isinstance(sm.mask, Image):
model = copy_image(sm.image)
model.data *= sm.mask.data
else:
model = sm.image
v = predict_list_serial_workflow([v], [model],
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=gcfcf,
**kwargs)[0]
if docal and isinstance(sm.gaintable, GainTable):
bv = convert_visibility_to_blockvisibility(v)
bv = apply_gaintable(bv, sm.gaintable, inverse=True)
v = convert_blockvisibility_to_visibility(bv)
return v
def ft_ift_sm(ov, sm, g):
assert isinstance(ov, Visibility) or isinstance(ov,
BlockVisibility), ov
assert isinstance(sm, SkyModel), sm
if g is not None:
assert len(g) == 2, g
assert isinstance(g[0], Image), g[0]
assert isinstance(g[1], ConvolutionFunction), g[1]
v = copy_visibility(ov)
v.data['vis'][...] = 0.0 + 0.0j
if len(sm.components) > 0:
if isinstance(sm.mask, Image):
comps = copy_skycomponent(sm.components)
comps = apply_beam_to_skycomponent(comps, sm.mask)
v = predict_skycomponent_visibility(v, comps)
else:
v = predict_skycomponent_visibility(v, sm.components)
if isinstance(sm.image, Image):
if numpy.max(numpy.abs(sm.image.data)) > 0.0:
if isinstance(sm.mask, Image):
model = copy_image(sm.image)
model.data *= sm.mask.data
else:
model = sm.image
v = predict_list_serial_workflow([v], [model],
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=[g],
**kwargs)[0]
assert isinstance(sm.image, Image), sm.image
result = invert_list_serial_workflow([v], [sm.image],
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=[g],
**kwargs)[0]
if isinstance(sm.mask, Image):
result[0].data *= sm.mask.data
return result
def ft_cal_sm(obv, sm):
assert isinstance(obv, BlockVisibility), obv
bv = copy_visibility(obv)
bv.data['vis'][...] = 0.0 + 0.0j
assert len(sm.components) > 0
if isinstance(sm.mask, Image):
comps = copy_skycomponent(sm.components)
comps = apply_beam_to_skycomponent(comps, sm.mask)
bv = predict_skycomponent_visibility(bv, comps)
else:
bv = predict_skycomponent_visibility(bv, sm.components)
if docal and isinstance(sm.gaintable, GainTable):
bv = apply_gaintable(bv, sm.gaintable, inverse=True)
return bv
def ft_ift_sm(ov, sm):
assert isinstance(ov, Visibility), ov
v = copy_visibility(ov)
v.data['vis'][...] = 0.0 + 0.0j
if len(sm.components) > 0:
if isinstance(sm.mask, Image):
comps = copy_skycomponent(sm.components)
comps = apply_beam_to_skycomponent(comps, sm.mask)
v = predict_skycomponent_visibility(v, comps)
else:
v = predict_skycomponent_visibility(v, sm.components)
if isinstance(sm.image, Image):
if numpy.max(numpy.abs(sm.image.data)) > 0.0:
if isinstance(sm.mask, Image):
model = copy_image(sm.image)
model.data *= sm.mask.data
else:
model = sm.image
v = predict_list_serial_workflow([v], [model],
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=gcfcf,
**kwargs)[0]
assert isinstance(sm.image, Image), sm.image
result = invert_list_serial_workflow([v], [sm.image],
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=gcfcf,
**kwargs)[0]
if isinstance(sm.mask, Image):
result[0].data *= sm.mask.data
return result