def predict_skymodel_list_serial_workflow(vis_list,
skymodel_list,
context,
vis_slices=1,
facets=1,
gcfcf=None,
**kwargs):
"""Predict from a skymodel, iterating over both the vis_list and skymodel
The visibility and image are scattered, the visibility is predicted on each part, and then the
parts are assembled.
:param vis_list:
:param skymodel_list: skymodel list
:param vis_slices: Number of vis slices (w stack or timeslice)
:param facets: Number of facets (per axis)
:param context: Type of processing e.g. 2d, wstack, timeslice or facets
:param gcfcg: tuple containing grid correction and convolution function
:param kwargs: Parameters for functions in components
:return: List of vis_lists
"""
def extract_comps(sm):
return sm.components
def extract_image(sm):
return sm.images[0]
comp = [extract_comps(sm) for sm in skymodel_list]
images = [extract_image(sm) for sm in skymodel_list]
dft_vis_list = zero_list_serial_workflow(vis_list)
dft_vis_list = [
predict_skycomponent_visibility(dft_vis_list[i], comp[i])
for i, _ in enumerate(dft_vis_list)
]
fft_vis_list = zero_list_serial_workflow(vis_list)
fft_vis_list = predict_list_serial_workflow(fft_vis_list,
images,
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=gcfcf,
**kwargs)
def vis_add(v1, v2):
vout = copy_visibility(v1)
vout.data['vis'] += v2.data['vis']
return vout
return [
vis_add(dft_vis_list[i], fft_vis_list[i])
for i, _ in enumerate(dft_vis_list)
]
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_serial_workflow(self.vis_list)
vis_list = predict_list_serial_workflow(vis_list,
self.model_list,
context=context,
vis_slices=vis_slices,
facets=facets,
gcfcf=gcfcf,
**kwargs)
vis_list = subtract_list_serial_workflow(self.vis_list, vis_list)
dirty = invert_list_serial_workflow(vis_list,
self.model_list,
context='2d',
dopsf=False,
gcfcf=gcfcf,
normalize=True)[centre]
assert numpy.max(numpy.abs(dirty[0].data)), "Residual image is empty"
export_image_to_fits(
dirty[0], '%s/test_imaging_predict_%s%s_serial_dirty.fits' %
(self.dir, context, extra))
maxabs = numpy.max(numpy.abs(dirty[0].data))
assert maxabs < fluxthreshold, "Error %.3f greater than fluxthreshold %.3f " % (
maxabs, fluxthreshold)
def test_zero_list(self):
self.actualSetUp()
centre = self.freqwin // 2
vis_list = zero_list_serial_workflow(self.vis_list)
assert numpy.max(numpy.abs(vis_list[centre].vis)) < 1e-15, numpy.max(
numpy.abs(vis_list[centre].vis))
predicted_vis_list = [
predict_skycomponent_visibility(vis_list[freqwin],
self.components_list[freqwin])
for freqwin, _ in enumerate(self.frequency)
]
assert numpy.max(numpy.abs(predicted_vis_list[centre].vis)) > 0.0, \
numpy.max(numpy.abs(predicted_vis_list[centre].vis))
diff_vis_list = subtract_list_serial_workflow(self.vis_list,
predicted_vis_list)
assert numpy.max(numpy.abs(
diff_vis_list[centre].vis)) < 1e-15, numpy.max(
numpy.abs(diff_vis_list[centre].vis))