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

Description

This task determines a baseline by baseline gain (time) or bandpass (freq) for all baseline pairs in the data set. For the usual antenna-based calibration of interferometric data, this task gaincal is recommended, even with only one to three baselines. For arrays with closure errors, use blcal.

Parameters

Title
Parameter	Default	Description
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 by baseline length.
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'`	Type of solution” ('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 parameters for each gaintable, as a list
spwmap	`numpy.array( [ ] )`	Spectral windows combinations to form for gaintables(s)
parang	`False`	Apply parallactic angle correction

Parameter Explanations

vis

''

Name of input visibility file: Default: none

Example: vis=’ngc5921.ms’

caltable

''

Name of output gain calibration table: Default: none

Example: caltable=’ngc5921.gcal’

field

''

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

Default: ‘’ (all fields)

Use ‘go listobs’ to obtain the list id’s or names. If field string is a non-negative integer, it is assumed a field index, otherwise, it is assumed a field name.

Examples: field=’0~2’; field ids 0,1,2 field=’0,4,5~7’; field ids 0,4,5,6,7 field=’3C286,3C295’; field named 3C286 and 3C295 field = ‘3,4C*’; field id 3, all names starting with 4C

spw

''

Select spectral window/channels: Default: ‘’ (all spectral windows and channels)

Examples: spw=’0~2,4’; spectral windows 0,1,2,4 (all channels) spw=’<2’; spectral windows less than 2 (i.e. 0,1) spw=’0:5~61’; spw 0, channels 5 to 61, INCLUSIVE spw=’*:5~61’; all spw with channels 5 to 61 spw=’0,10,3:3~45’; spw 0,10 all channels, spw 3, channels 3 to 45. spw=’0~2:2~6’; spw 0,1,2 with channels 2 through 6 in each. spw=’0:0~10;15~60’; spectral window 0 with channels 0-10,15-60. (NOTE ‘;’ to separate channel selections) spw=’0:0~10^2,1:20~30^5’; spw 0, channels 0,2,4,6,8,10, spw 1, channels 20,25,30

intent

''

Select observing intent: Default: ‘’ (no selection by intent)

Example: intent=’BANDPASS’ (selects data labelled with BANDPASS intent)

selectdata

True

Other data selection parameters: Default: True Options: True|False

timerange

''

Select data based on time range: Subparameter of selectdata=True Default = ‘’ (all)

Examples: timerange = ‘YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss’ (Note: if YYYY/MM/DD is missing date defaults to first day in data set.) timerange=’09:14:0~09:54:0’ picks 40 min on first day timerange= ‘25:00:00~27:30:00’ picks 1 hr to 3 hr 30min on NEXT day timerange=’09:44:00’ pick data within one integration of time timerange=’>10:24:00’ data after this time

uvrange

''

Select data by baseline length.: Default = ‘’ (all)

Examples: uvrange=’0~1000klambda’; uvrange from 0-1000 kilo-lambda uvrange=’>4klambda’;uvranges greater than 4 kilo-lambda uvrange=’0~1000km’; uvrange in kilometers

antenna

''

Select data based on antenna/baseline

Subparameter of selectdata=True Default: ‘’ (all)

If antenna string is a non-negative integer, it is assumed an antenna index, otherwise, it is assumed as an antenna name

Examples: antenna=’5&6’; baseline between antenna index 5 and index 6. antenna=’VA05&VA06’; baseline between VLA antenna 5 and 6. antenna=’5&6;7&8’; baselines with indices 5-6 and 7-8 antenna=’5’; all baselines with antenna index 5 antenna=’05’; all baselines with antenna number 05 (VLA old name) antenna=’5,6,10’; all baselines with antennas 5,6,10 index numbers

scan

''

Scan number range: Subparameter of selectdata=True Default: ‘’ = all

observation

''

Select by observation ID(s): Subparameter of selectdata=True Default: ‘’ = all

Example: observation=’0~2,4’

msselect

''

Optional complex data selection (ignore for now)

solint

'inf'

Solution interval: Default: ‘inf’ (infinite, up to boundaries controlled by combine); Options: ‘inf’ (~infinite), ‘int’ (per integration), any float or integer value with or without units

Examples: solint=’1min’; solint=’60s’, solint=60 (i.e., 1 minute); solint=’0s’; solint=0; solint=’int’ (i.e., per integration); solint-‘-1s’; solint=’inf’ (i.e., ~infinite, up to boundaries enforced by combine)

combine

'scan'

Data axes which to combine for solve: Default: ‘scan’ (solutions will break at obs, field, and spw boundaries, but may extend over multiple scans [per obs, field, and spw] up to solint.) Options: ‘’,’obs’,’scan’,’spw’,field’, or any comma-separated combination in a single string

Example: combine=’scan,spw’ - Extend solutions over scan boundaries (up to the solint), and combine spws for solving

freqdep

False

Solve for frequency dependent solutions: Default: False (gain; True=bandpass) Options: False|True

calmode

'ap'

Type of solution” (‘ap’, ‘p’, ‘a’): Default: ‘ap’ (amp and phase) Options: ‘p’ (phase) ,’a’ (amplitude), ‘ap’ (amplitude and phase)

Example: calmode=’p’

solnorm

False

Normalize average solution amplitudes to 1.0

Default: False (no normalization)

For freqdep=False, this is a global (per-spw) normalization of amplitudes (only). For freqdep=True, each baseline solution spectrum is separately normalized by its (complex) mean.

gaintable

numpy.array( [ ] )

Gain calibration table(s) to apply on the fly: Default: ‘’ (none)

Examples: gaintable=’ngc5921.gcal’ gaintable=[‘ngc5921.ampcal’,’ngc5921.phcal’]

gainfield

numpy.array( [ ] )

Select a subset of calibrators from gaintable(s)

Default: ‘’ (all sources on the sky)

‘nearest’ ==> nearest (on sky) available field in table otherwise, same syntax as field

Examples: gainfield=’0~3’ gainfield=[‘0~3’,’4~6’]

interp

numpy.array( [ ] )

Interpolation parmameters (in time[,freq]) for each gaintable, as a list of strings.

Default: ‘’ –> ‘linear,linear’ for all gaintable(s) Options: Time: ‘nearest’, ‘linear’

Freq: ‘nearest’, ‘linear’, ‘cubic’, ‘spline’

Specify a list of strings, aligned with the list of caltable specified in gaintable, that contain the required interpolation parameters for each caltable. * When frequency interpolation is relevant (B, Df,

Xf), separate time-dependent and freq-dependent interp types with a comma (freq_after_ the comma).

Specifications for frequency are ignored when the calibration table has no channel-dependence.
Time-dependent interp options ending in ‘PD’ enable a “phase delay” correction per spw for non-channel-dependent calibration types.
For multi-obsId datasets, ‘perobs’ can be appended to the time-dependent interpolation specification to enforce obsId boundaries when interpolating in time.
Freq-dependent interp options can have ‘flag’ appended to enforce channel-dependent flagging, and/or ‘rel’ appended to invoke relative frequency interpolation

Examples: interp=’nearest’ (in time, freq-dep will be linear, if relevant) interp=’linear,cubic’ (linear in time, cubic in freq) interp=’linearperobs,splineflag’ (linear in time per obsId, spline in freq with channelized flagging) interp=’nearest,linearflagrel’ (nearest in time, linear in freq with with channelized flagging and relative-frequency interpolation) interp=’,spline’ (spline in freq; linear in time by default) interp=[‘nearest,spline’,’linear’] (for multiple gaintables)

spwmap

numpy.array( [ ] )

Spectral windows combinations to form for gaintables(s): Subparameter of callib=False default: [] (apply solutions from each spw to that spw only)

Examples: spwmap=[0,0,1,1] means apply the caltable solutions from spw = 0 to the spw 0,1 and spw 1 to spw 2,3. spwmap=[[0,0,1,1],[0,1,0,1]] (for multiple gaintables)

parang

False

Apply parallactic angle correction

Default: False

If True, apply the parallactic angle correction (required for polarization calibration)