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
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|
|
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| Inputs | |
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| 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 |
| | | Default: | variant 1.0 |
| spwmap | | Spectral window combinations to apply
|
| | | allowed: | intArray |
| | | Default: | -1 |
| |
Returns
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 mode (in time) to use for each gaintable
default: ’’ --> ’linear’ for all gaintable(s)
example: interp=’nearest’
interp=[’nearest’,’linear’] (for multiple gaintables)
Options: ’nearest’, ’linear’, ’aipslin’
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()
Incorporate gaincurve, opacity, parang once and for all
taskname= ’gaincal’
vis = ’mydata.ms’
caltable = ’first_cal’
etc
gaincurve = T
opacity = 0.11
parang = T
gaincal()
taskname = ’accum’
default()
vis = ’mydata.ms’
tablein = ’’
accumtime = 10
incrtable = ’first_cal’
caltable = ’accum1_cal’
accum()
accum1_cal with contain not only the gaincal solution, but the gaincurve,
opacity and parang correction. Hence, when applying accum1_cal
on the fly for subsequent calibrations (gaincal, bandpass) or applying
the calibrations, then
gaincurve=F; opacity = 0.0; parang = F should be used
Please send any comments or questions about CASA or AIPS++
to aips2-requests@nrao.edu
Copyright © 2008 Associated Universities Inc.,
Washington, D.C.
This code is available under the terms of the GNU General Public Lincense
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Updated daily during alpha development.