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NRAO Home > CASA > CASA Task Reference Manual |
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0.1.1 accum
Requires:
Synopsis
Accumulate incremental calibration solutions into a calibration table
Description
Accum will interpolate and extrapolate a calibration table onto a new table
that has a regularly-space time grid.
The first run of accum defines the time grid and fills this table with the results from the input table.
Subsequent use of accum will combine additional calibration tables onto the same grid of the initial accum table to obtain an output accum table. See below for concrete examples.
Accum tables are similar to CL tables in AIPS Incremental tables are similar to SN tables in AIPS
Arguments
Inputs |
| ||
vis |
| Name of input visibility file
| |
| allowed: | string |
|
| Default: |
| |
tablein |
| Input cumulative calibration table; use ” on first run
| |
| allowed: | string |
|
| Default: |
| |
incrtable |
| Input incremental calibration table to add
| |
| allowed: | string |
|
| Default: |
|
|
caltable |
| Output (cumulative) calibration table
| |
| allowed: | string |
|
| Default: |
| |
field |
| List of field names to process from tablein
| |
| allowed: | stringArray |
|
| Default: |
|
|
calfield |
| List of field names to use from incrtable.
| |
| allowed: | stringArray |
|
| Default: |
|
|
interp |
| Interpolation mode to use for resampling incrtable
solutions
| |
| allowed: | string |
|
| Default: | linear |
|
accumtime |
| Time-interval when create cumulative table
| |
| allowed: | any |
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| Default: | variant 1.0 |
|
spwmap |
| Spectral window combinations to apply
| |
| allowed: | intArray |
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| Default: | -1 |
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void
Example
Accum will interpolate and extrapolate a temporal calibration
table onto a new table that has a regularly-space time grid.
The first run of accum defines the time grid and fills this
table with the results from the input table.
Subsequent use of accum will combine additional calibration
tables onto the same grid of the initial accum table to obtain
an output accum table. See below for a concrete example.
Keyword arguments:
vis -- Name of input visibility file
default: none. example: vis=’ngc5921.ms’
tablein -- Input cumulative calibration table.
default: ’’ means none
On first execution of accum, tablein=’’
and accumtime is used to generate tablein with
the specified time gridding.
accumtime -- The time separation when making tablein.
default: 1.0 (1 second). This time should not be
less than the visibiility sampling time, but should
be less than about 30% of a typical scan length.
incrtable -- The calibration data to be interpolated onto the
tablein file.
default: ’’. Must be specified
caltable -- The output cumulated calibration file.
default: ’’ means use tablein as the output file
field -- Select field(s) from tablein to process.
[’go 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’; field named 3C286 and 3C295
field = ’3,4C*’; field id 3, all names starting with 4C
calfield -- Select field(s) from incrtable to process.
default: ’’ = all fields
interp -- Interpolation type (in time[,freq]) to use for each gaintable.
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.
default: ’’ --> ’linear,linear’ for all gaintable(s)
example: interp=’nearest’ (in time, freq-dep will be
linear, if relevant)
interp=’linear,cubic’ (linear in time, cubic
in freq)
interp=’linearperobs,spline’ (linear in time
per obsId,
spline in freq)
interp=’,spline’ (spline in freq; linear in
time by default)
interp=[’nearest,spline’,’linear’] (for multiple gaintables)
Options: Time: ’nearest’, ’linear’
Freq: ’nearest’, ’linear’, ’cubic’, ’spline’
spwmap -- Spectral windows combinations to form for gaintable(s)
default: [] (apply solutions from each spw to that spw only)
Example: 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)
async -- Run task in a separate process
default: False; example: async=True
Examples:
Create an accum table with 10-sec sampling, filling it with the calibration
in ’first_cal’ with the desired interpolation.
taskname = ’accum’
default()
vis = ’mydata.ms’
tablein = ’’
accumtime = 10
incrtable = ’first_cal’
caltable = ’accum1_cal’
accum()
If you plot ’accum1_cal’ with plotcal, you can see how the incrtable was
interpolated.
Continue accumulating calibrations in accum1_cal from ’second_cal’
taskname = ’accum’
default()
vis = ’mydata.ms’
tablein = ’accum1_cal’
incrtable = ’second_cal’
caltable = ’accum1_cal’
accum()
More information about CASA may be found at the
CASA web page
Copyright © 2016 Associated Universities Inc., Washington, D.C.
This code is available under the terms of the GNU General Public Lincense
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