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casa
$Rev:20696$
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casa
$Rev:20696$
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Public Member Functions | |
| def | __init__ |
| def | __call__ |
Private Attributes | |
| __bases__ | |
| __doc__ | |
Static Private Attributes | |
| string | __name__ |
Definition at line 18 of file split_pg.py.
| def split_pg.split_pg_.__init__ | ( | self | ) |
Definition at line 21 of file split_pg.py.
| def split_pg.split_pg_.__call__ | ( | self, | |
vis = None, |
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outputvis = None, |
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datacolumn = None, |
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field = None, |
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spw = None, |
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width = None, |
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antenna = None, |
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timebin = None, |
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timerange = None, |
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scan = None, |
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intent = None, |
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array = None, |
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uvrange = None, |
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correlation = None, |
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observation = None, |
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combine = None, |
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keepflags = None, |
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keepmms = None, |
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async = None |
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| ) |
Create a visibility subset from an existing visibility set
Split is the general purpose program to make a new data set that is a
subset or averaged form of an existing data set. General selection
parameters are included, and one or all of the various data columns
(DATA, LAG_DATA and/or FLOAT_DATA, and possibly MODEL_DATA and/or
CORRECTED_DATA) can be selected.
Split 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. split can
average over frequency (channels) and time (integrations).
With the keepmms parameter, split can be run parallelized on multi-MS
input.
Keyword arguments:
vis -- Name of input visibility file
default: none; example: vis='ngc5921.ms'
outputvis -- Name of output visibility file
default: none; example: outputvis='ngc5921_src.ms'
datacolumn -- Which data column to split out
default='corrected'; example: datacolumn='data'
Options: 'data', 'model', 'corrected', 'all',
'float_data', 'lag_data', 'float_data,data', and
'lag_data,data'.
N.B.: '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!
--- Data Selection (see help par.selectdata for more detailed
information)
field -- Select field using field id(s) or field name(s).
[run listobs to obtain the list id's or 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
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
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.
split 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 -- Defines the number of channel to average to form the one
output channel.
default: '1' => no channel averaging
example: width=[2,3] => average 2 channels of 1st
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 -- Interval width for time averaging.
default: '0s' or '-1s' (no averaging)
example: timebin='30s'
'10' means '10s'
timerange -- Select data based on time range:
default = '' (all); examples,
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
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 -- (Sub)array number range
default: ''=all
uvrange -- Select data within uvrange (default units meters)
default: ''=all; example:
uvrange='0~1000klambda'; uvrange from 0-1000 kilo-lambda
uvrange='>4klambda';uvranges greater than 4 kilo-lambda
uvrange='0~1000km'; uvrange in kilometers
scan -- Scan number range
default: ''=all
intent -- Select by scan intent (state). Case sensitive.
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, e.g. 'rr, ll' or ['XY', 'YX'].
default '' (all).
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)
combine = 'scan': Can be useful when the scan number
goes up with each integration,
as in many WSRT MSes.
combine = ['scan', 'state']: disregard scan and state
numbers when time averaging.
combine = 'state,scan': Same as above.
keepflags -- 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 -- If true and the input is a multi-MS, make the output one, too.
Otherwise, the output will be a normal MS without partitioning.
(experimental)
Default: FalseDefinition at line 26 of file split_pg.py.
References vla_uvfits_line_sf.verify.
split_pg.split_pg_.__bases__ [private] |
Definition at line 22 of file split_pg.py.
split_pg.split_pg_.__doc__ [private] |
Definition at line 23 of file split_pg.py.
string split_pg.split_pg_.__name__ [static, private] |
Definition at line 19 of file split_pg.py.
1.8.0