oldsplit – Create a visibility subset from an existing visibility set – manipulation task

Description

T H I S T A S K I S D E P R E C A T E D I T W I L L B E R E M O V E D S O O N

Oldsplit is the general purpose program to make a new data set that is a subset or averaged form of an existing data set. Oldsplit is often used after the initial calibration of the data to make a smaller measurement set with only the data that will be used in further flagging, imaging and/or self-calibration. Oldsplit includes general selection parameters and can average over frequency (channels) and time (integrations).

Parameters

Title

Parameter	Default	Description
vis	''	Name of input measurement set
outputvis	''	Name of output measurement set
datacolumn	'corrected'	Data column(s) to Oldsplit out
field	''	Select field using ID(s) or name(s)
spw	''	Select spectral window/channels
width	int(1)	Number of channels to average to form one output channel
antenna	''	Select data based on antenna/baseline
timebin	'0s'	Interval for time averaging
timerange	''	Select data by time range
array	''	Select (sub)array(s) by array ID number
uvrange	''	Select data by baseline length (default units meters)
scan	''	Select data by scan numbers
intent	''	Select data by scan intents
correlation	''	Select correlations
observation	''	Select by observation ID(s)
combine	''	Let time bins span changes in scan and/or stat
keepflags	True	If practical, keep completely flagged rows instead of dropping them.
keepmms	False	If the input is a multi-MS, make the output one,too.

Parameter Explanations

vis

''

Name of input MeasurementSet

Default: none;

Example: vis=’ngc5921.ms’

outputvis

''

Name of output measurement set

Default: none;

Example: outputvis=’ngc5921_src.ms’

datacolumn

'corrected'

Data column(s) to Oldsplit out

Default=’corrected’; Options: ‘data’, ‘model’, ‘corrected’, ‘all’, ‘float_data’, ‘lag_data’, ‘float_data,data’, and ‘lag_data,data’.

Example: datacolumn=’data’

Note: ‘all’ = whichever of the above that are present. Otherwise the selected column will go to DATA (or FLOAT_DATA) in the output. Splitting with the default datacolumn=’corrected’ before clean is normally required for self-calibration!

field

''

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

(Run listobs to obtain list of field IDs and names) Default: ‘’=all fields. If field string is a non-negative integer, it is assumed to be a field index otherwise, it is assumed to be 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’; fields 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 spw=’0,10,3:3~45’; spw 0,10 all channels, spw 3 - chans 3 to 45. spw=’0~2:2~6’; spw 0,1,2 with channels 2 through 6 in each. spw = ‘*:3~64’ channels 3 through 64 for all sp id’s spw = ‘ :3~64’ will NOT work.

Note: Oldsplit does not support multiple channel ranges per spectral window (‘;’) because it is not clear whether to keep the ranges in the original spectral window or make a new spectral window for each additional range.

width

int(1)

Number of channels to average to form one output channel

Default: ‘1’ => no channel averaging

Example: width=[2,3] => average 2 channels of 1s spectral window selected and 3 in the second one.

antenna

''

Select data based on antenna/baseline

Default: ‘’ (all) Non-negative integers are assumed to be antenna indices, and anything else is taken 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 5-6 and 7-8 antenna=’5’: all baselines with antenna 5 antenna=’5,6,10’: all baselines including antennas 5, 6, or 10 antenna=’5,6,10&’: all baselines with only antennas 5, 6, or 10. (cross-correlations only. Use && to include autocorrelations, and &&& to get only autocorrelations.) antenna=’!ea03,ea12,ea17’: all baselines except those that include EVLA antennas ea03, ea12, or ea17.

timebin

'0s'

Interval for time averaging

Default: ‘0s’ or ‘-1s’ (no averaging)

Example: timebin=’30s’ ‘10’ means ’10s’

timerange

''

Select data by time range

timerange = ‘YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss’ Note: if YYYY/MM/DD is missing date, timerange defaults to the first day in the dataset.

Default = ‘’ (all); examples,

Examples: 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’ data within one integration of time timerange=’>10:24:00’ data after this time

array

''

Select (sub)array(s) by array ID number

Default: ‘’=all

uvrange

''

Select data by baseline length (default units meters)

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

scan

''

Select data by scan numbers

Default: ‘’=all

intent

''

Select data by scan intents

Default: ‘’ = all

Examples: intent = ‘CALIBRATE_ATMOSPHERE_REFERENCE’ intent = ‘calibrate_atmosphere_reference’.upper() # same as above # Select states that include one or both of CALIBRATE_WVR.REFERENCE or OBSERVE_TARGET_ON_SOURCE. intent = ‘CALIBRATE_WVR.REFERENCE, OBSERVE_TARGET_ON_SOURCE’

correlation

''

Select correlations

Default: ‘’ = all

Examples: correlation = ‘rr, ll’ correlation = [‘XY’, ‘YX’].

observation

''

Select by observation ID(s)

Default: ‘’ = all

combine

''

Let time bins span changes in scan and/or state

Default = ‘’ (separate time bins by both of the above)

Examples: combine = ‘scan’: Can be useful when the scan number goes up with each integration, as in many WSRT MSs. combine = [‘scan’, ‘state’]: disregard scan and state numbers when time averaging. combine = ‘state,scan’: Same as above.

keepflags

True

If practical, keep completely flagged rows instead of dropping them.

This has absolutely no effect on averaging calculations, or partially flagged rows. All of the channels and correlations of a row must be flagged for it to be droppable, and a row must be well defined to be keepable. The latter condition means that this option has no effect on time averaging - in that case fully flagged rows are automatically omitted. Regardless of this parameter, flagged data is never included in averaging calculations.

The only time keepflags matters is if 1. the input MS has some completely flagged rows and 2. time averaging is not being done.

Then, if keepflags is False, the completely flagged rows will be omitted from the output MS. Otherwise, they will be included (subject to the selection parameters).

keepmms

False

If the input is a multi-MS, make the output one, too. (experimental)

Default: False => the output will be a normal MS without partitioning.