blcal – Calculate a baseline-based calibration solution (gain or bandpass) – calibration task

Description

Parameters

Title
Parameter	Default	Description
vis	`''`
caltable	`''`
field	`''`
spw	`''`
intent	`''`
selectdata	`True`
timerange	`''`
uvrange	`''`
antenna	`''`
scan	`''`
observation	`''`
msselect	`''`
solint	`'inf'`
combine	`'scan'`
freqdep	`False`
calmode	`'ap'`	Amp/phase calibration solving mode
solnorm	`False`
gaintable	`numpy.array( [ ] )`
gainfield	`numpy.array( [ ] )`
interp	`numpy.array( [ ] )`
spwmap	`numpy.array( [ ] )`
parang	`False`

Parameter Explanations

vis

''

Name of input visibility file

caltable

''

Name of output gain calibration table

field

''

Select field using field id(s) or field name(s)

spw

''

Select spectral window/channels

intent

''

Select observing intent

selectdata

True

Other data selection parameters

timerange

''

Select data based on time range

uvrange

''

Select data within uvrange (default units meters)

antenna

''

Select data based on antenna/baseline

scan

''

Scan number range

observation

''

Select by observation ID(s)

msselect

''

Optional complex data selection (ignore for now)

solint

'inf'

Solution interval

combine

'scan'

Data axes which to combine for solve (obs, scan, spw, and/or field)

freqdep

False

Solve for frequency dependent solutions

calmode

'ap'

Amp/phase calibration solving mode: (‘ap’, ‘p’, ‘a’)

solnorm

False

Normalize average solution amplitudes to 1.0

gaintable

numpy.array( [ ] )

Gain calibration table(s) to apply on the fly

gainfield

numpy.array( [ ] )

Select a subset of calibrators from gaintable(s)

interp

numpy.array( [ ] )

Interpolation mode (in time) to use for each gaintable

spwmap

numpy.array( [ ] )

Spectral windows combinations to form for gaintables(s)

parang

False

Apply parallactic angle correction