def calskymodel_fit_gaintable(evis,
calskymodel,
gain=0.1,
niter=3,
tol=1e-3,
**kwargs):
"""Fit a gaintable to a visibility
This is the update to the gain part of the window
:param evis: Expected vis for this ssm
:param calskymodel: csm element being fit
:param gain: Gain in step
:param niter: Number of iterations
:param kwargs: Gaintable
"""
previous_gt = copy_gaintable(calskymodel[1])
gt = copy_gaintable(calskymodel[1])
model_vis = copy_visibility(evis, zero=True)
model_vis = predict_skymodel_visibility(model_vis, calskymodel[0])
gt = solve_gaintable(evis,
model_vis,
gt=gt,
niter=niter,
phase_only=True,
gain=0.5,
tol=1e-4,
**kwargs)
gt.data['gain'][...] = gain * gt.data['gain'][...] + (
1 - gain) * previous_gt.data['gain'][...]
gt.data['gain'][...] /= numpy.abs(previous_gt.data['gain'][...])
return gt
def create_modelpartition(vis: BlockVisibility, skymodels, **kwargs):
"""Create a set of associations between skymodel and gaintable
:param vis: BlockVisibility to process
:param skymodels: List of skyModels
:param kwargs:
:return:
"""
gt = create_gaintable_from_blockvisibility(vis, **kwargs)
return [(copy_skymodel(sm), copy_gaintable(gt)) for sm in skymodels]
def solve_modelpartition(vis,
skymodels,
niter=10,
tol=1e-8,
gain=0.25,
**kwargs):
""" Solve for model partitions
Solve by iterating, performing E step and M step.
:param vis: Initial visibility
:param components: Initial components to be used
:param gaintables: Initial gain tables to be used
:param kwargs:
:return: The individual data models and the residual visibility
"""
model_partition = create_modelpartition(vis, skymodels=skymodels, **kwargs)
for iter in range(niter):
new_modelpartitions = list()
evis_all = modelpartition_expectation_all(vis, model_partition)
log.debug("solve_modelpartition: Iteration %d" % (iter))
for window_index, csm in enumerate(model_partition):
evis = modelpartition_expectation_step(vis,
evis_all,
csm,
gain=gain,
**kwargs)
new_csm = modelpartition_maximisation_step(evis, csm, **kwargs)
new_modelpartitions.append((new_csm[0], new_csm[1]))
flux = new_csm[0].components[0].flux[0, 0]
qa = qa_gaintable(new_csm[1])
residual = qa.data['residual']
rms_phase = qa.data['rms-phase']
log.debug(
"solve_modelpartition:\t Window %d, flux %s, residual %.3f, rms phase %.3f"
% (window_index, str(flux), residual, rms_phase))
model_partition = [(copy_skymodel(csm[0]), copy_gaintable(csm[1]))
for csm in new_modelpartitions]
residual_vis = copy_visibility(vis)
final_vis = modelpartition_expectation_all(vis, model_partition)
residual_vis.data['vis'][
...] = vis.data['vis'][...] - final_vis.data['vis'][...]
return model_partition, residual_vis
def create_calskymodel(vis, skymodel):
gt = create_gaintable_from_blockvisibility(vis, **kwargs)
return (copy_skymodel(skymodel), copy_gaintable(gt))
