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Basic Information on blcal
Task: blcal
Purpose: Compute and apply baseline calibration.
Categories: uv analysis
BLCAL computes and applies baseline-based calibration to a visibility
dataset.
This reads two datasets. It uses the first dataset to determine
baseline-based calibration, and applies these calibration corrections
to the second dataset.
Key: vis
Normally, this gives the name of two visibility datasets, being
the "reference" and the "source" datasets respectively. The
reference dataset is used to determine the baseline calibration,
whereas the source contains the data that is corrected and written
out. If only a single dataset is given, then this is self-calibrated.
Baseline-based self-calibration is a very dubious operation, and
generally should not be performed.
Note: Both the reference and source datasets should be in time order.
Key: select
The normal uv selection commands -- see the help on select for
more information. This selection is applied to both the reference
and source input datasets.
Key: line
The normal uv linetype in the form:
line,nchan,start,width,step
See the help on line for more information.
The default is all channels (or all wide channels if there are no
spectral channels). The output will consist of only spectral or
wideband data (but not both).
Key: stokes
Normal Stokes/polarisation processing. See the help on stokes
for more information. The default is to use the Stokes/polarisations
present in the dataset.
Key: interval
Solution time interval, in minutes. The default is a single solution.
Key: out
The name of the output uv data set. No default.
Key: options
Extra processing options. Possible values are:
nopassol Determine a solution which is independent of channel number.
nopolsol Solve for parallel-hand polarisations only. When
applying corrections, cross-hand correlations get corrected
with a parallel-hand gain. In particular XY and YX are
corrected with the mean of the XX and YY gains; RL and LR
are corrected with the mean of RR and LL gains; Q,U, and V
are corrected with the I gain.
replace Rather than writing the corrected dataset, write out a
dataset where the data are replaced with the model of a
unit point source with baseline errors.
Generated by miriad@atnf.csiro.au on 02 Jun 2021