def convert_blockvisibility_to_visibility(vis: BlockVisibility) -> Visibility:
""" Convert the BlockVisibility data with no coalescence
:param vis: BlockVisibility to be converted
:return: Visibility with cindex and blockvis filled in
"""
assert isinstance(
vis, BlockVisibility), "vis is not a BlockVisibility: %r" % vis
cvis, cuvw, cwts, cimaging_wts, ctime, cfrequency, cchannel_bandwidth, ca1, ca2, cintegration_time, cindex \
= convert_blocks(vis.data['vis'], vis.data['uvw'], vis.data['weight'], vis.data['imaging_weight'],
vis.time, vis.integration_time,
vis.frequency, vis.channel_bandwidth)
converted_vis = Visibility(uvw=cuvw,
time=ctime,
frequency=cfrequency,
channel_bandwidth=cchannel_bandwidth,
phasecentre=vis.phasecentre,
antenna1=ca1,
antenna2=ca2,
vis=cvis,
weight=cwts,
imaging_weight=cimaging_wts,
configuration=vis.configuration,
integration_time=cintegration_time,
polarisation_frame=vis.polarisation_frame,
cindex=cindex,
blockvis=vis,
meta=vis.meta)
log.debug('convert_visibility: Original %s, converted %s' %
(vis_summary(vis), vis_summary(converted_vis)))
return converted_vis
def coalesce_visibility(vis: BlockVisibility, **kwargs) -> Visibility:
""" Coalesce the BlockVisibility data_models. The output format is a Visibility, as needed for imaging
Coalesce by baseline-dependent averaging (optional). The number of integrations averaged goes as the ratio of the
maximum possible baseline length to that for this baseline. This number can be scaled by coalescence_factor and
limited by max_coalescence.
When faceting, the coalescence factors should be roughly the same as the number of facets on one axis.
If coalescence_factor=0.0 then just a format conversion is done
:param vis: BlockVisibility to be coalesced
:return: Coalesced visibility with cindex and blockvis filled in
"""
assert isinstance(
vis, BlockVisibility), "vis is not a BlockVisibility: %r" % vis
time_coal = get_parameter(kwargs, 'time_coal', 0.0)
max_time_coal = get_parameter(kwargs, 'max_time_coal', 100)
frequency_coal = get_parameter(kwargs, 'frequency_coal', 0.0)
max_frequency_coal = get_parameter(kwargs, 'max_frequency_coal', 100)
if time_coal == 0.0 and frequency_coal == 0.0:
return convert_blockvisibility_to_visibility((vis))
cvis, cuvw, cwts, cimwt, ctime, cfrequency, cchannel_bandwidth, ca1, ca2, cintegration_time, cindex \
= average_in_blocks(vis.data['vis'], vis.data['uvw'], vis.data['weight'], vis.data['imaging_weight'],
vis.time, vis.integration_time,
vis.frequency, vis.channel_bandwidth, time_coal, max_time_coal,
frequency_coal, max_frequency_coal)
coalesced_vis = Visibility(uvw=cuvw,
time=ctime,
frequency=cfrequency,
channel_bandwidth=cchannel_bandwidth,
phasecentre=vis.phasecentre,
antenna1=ca1,
antenna2=ca2,
vis=cvis,
weight=cwts,
imaging_weight=cimwt,
configuration=vis.configuration,
integration_time=cintegration_time,
polarisation_frame=vis.polarisation_frame,
cindex=cindex,
blockvis=vis,
meta=vis.meta)
log.debug(
'coalesce_visibility: Created new Visibility for coalesced data_models, coalescence factors (t,f) = (%.3f,%.3f)'
% (time_coal, frequency_coal))
log.debug('coalesce_visibility: Maximum coalescence (t,f) = (%d, %d)' %
(max_time_coal, max_frequency_coal))
log.debug('coalesce_visibility: Original %s, coalesced %s' %
(vis_summary(vis), vis_summary(coalesced_vis)))
return coalesced_vis
def decoalesce_visibility(vis: Visibility, **kwargs) -> BlockVisibility:
""" Decoalesce the visibilities to the original values (opposite of coalesce_visibility)
This relies upon the block vis and the index being part of the vis. Needs the index generated by coalesce_visibility
:param vis: (Coalesced visibility)
:return: BlockVisibility with vis and weight columns overwritten
"""
assert isinstance(vis, Visibility), "vis is not a Visibility: %r" % vis
assert isinstance(vis.blockvis,
BlockVisibility), "No blockvisibility in vis %r" % vis
assert vis.cindex is not None, "No reverse index in Visibility %r" % vis
log.debug(
'decoalesce_visibility: Created new Visibility for decoalesced data_models'
)
decomp_vis = copy_visibility(vis.blockvis)
vshape = decomp_vis.data['vis'].shape
npol = vshape[-1]
dvis = numpy.zeros(vshape, dtype='complex')
assert numpy.max(vis.cindex) < dvis.size
assert numpy.max(
vis.cindex
) < vis.vis.shape[0], "Incorrect template used in decoalescing"
for i in range(dvis.size // npol):
decomp_vis.data['vis'].flat[i:i +
npol] = vis.data['vis'][vis.cindex[i]]
decomp_vis.data['flags'].flat[i:i +
npol] = vis.data['flags'][vis.cindex[i]]
decomp_vis.data['weight'].flat[i:i + npol] = vis.data['weight'][
vis.cindex[i]]
decomp_vis.data['imaging_weight'].flat[i:i + npol] = vis.data[
'imaging_weight'][vis.cindex[i]]
log.debug('decoalesce_visibility: Coalesced %s, decoalesced %s' %
(vis_summary(vis), vis_summary(decomp_vis)))
return decomp_vis