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NRAO Home > CASA > CASA Task Reference Manual |
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0.1.29 flagdata
Requires:
Synopsis
All-purpose flagging task based on data-selections and flagging
modes/algorithms.
Description
This task can flag a Measurement Set or a calibration table. It has two main
types of operation. One type will read the parameters from the interface and
flag using any of the various available modes. The other type will read the
commands from a text file, a list of files or a Python list of strings, containing
a list of flag commands (each line containing data selection parameters and
any parameter specific for the mode being requested). Please see examples at
the end of this help.
It is also possible to only save the parameters set in the interface without flagging. The parameters can be saved in the FLAG_CMD sub-table or in a text file. Note that when saving to an external file, the parameters will be appended to the given file.
The available flagging modes are: manual, clip, shadow, quack, elevation, tfcrop, rflag, extend, unflag and summary. For automatic flagging, it is recommended to combine auto-flag modes with extend, via the list mode.
The current flags can be automatically backed up before applying new flags if the parameter flagbackup is set. Previous flag versions can be recovered using the flagmanager task.
NOTE on flagging calibration tables. ———————————–
Flagdata can flag many types of calibration tables using mode=’manual’. It can only flag using the auto-flagging algorithms (clip, tfcrop or rflag), the cal tables that have the following data columns: CPARAM, FPARAM or SNR. The solution elements of the data columns are given in the correlation parameter using the names ’Sol1’, ’Sol2’, ’Sol3’, or ’Sol4’. See examples at the end of this help on how to flag different cal tables.
When the input is a calibration table, the modes ’elevation’ and ’shadow’ will be disabled. Data selection for calibration tables is limited to field, scan, time, antenna, spw and observation. It is only possible to save the parameters to an external file. If the calibration table was created before CASA 4.1, this task will create a dummy OBSERVATION column and OBSERVATION sub-table in the input calibration table to adapt it to the new cal table format.
Selecting antennas in some calibration tables have a different meaning compared to selecting the MS. Some calibration tables such as the antenna-based ones, created with some modes of gencal or polcal, have the ANTENNA2 column set to -1. This means that when selecting antenna=’ANT’, will select the whole ANT and not the cross-correlations between ANT and the other antennas. Similarly, the baseline syntax do not apply to this type of calibration tables. Those values with ampersand do not have any meaning when selecting antenna/baselines in antenna-based cal tables.
The task will flag a subset of data based on the following modes of operation:
list = list of flagging commands to apply to MS/cal table manual = flagging based on specific selection parameters clip = clip data according to values quack = remove/keep specific time range at scan beginning/end shadow = remove antenna-shadowed data elevation = remove data below/above given elevations tfcrop = automatic identification of outliers on the time-freq plane rflag = automatic detection of outliers based on sliding-window RMS filters antint = flag integrations if all baselines to a specified antenna are flagged extend = extend and/or grow flags beyond what the basic algorithms detect summary = report the amount of flagged data unflag = unflag the specified data
Arguments
Inputs |
| ||
vis |
| Name of MS file or calibration table to flag
| |
| allowed: | string |
|
| Default: |
| |
mode |
| Flagging mode
| |
| allowed: | string |
|
| Default: | manual | |
autocorr |
| Flag only the auto-correlations
| |
| allowed: | bool | |
| Default: | False |
|
inpfile |
| Input ASCII file, list of files or Python list of strings
with flag commands.
| |
| allowed: | any |
|
| Default: | variant
|
|
reason |
| Select by REASON types
| |
| allowed: | any |
|
| Default: | variant any |
|
tbuff |
| List of time buffers (sec) to pad timerange in flag
commands | |
| allowed: | any |
|
| Default: | variant 0.0 |
|
spw |
| Spectral-window/frequency/channel: ” ==> all,
spw=”0:17~19”
| |
| allowed: | any |
|
| Default: | variant
|
|
field |
| Field names or field index numbers: ” ==> all,
field=”0~2,3C286”
| |
| allowed: | any |
|
| Default: | variant
|
|
antenna |
| Antenna/baselines: ” ==> all, antenna =”3,VA04”
| |
| allowed: | any |
|
| Default: | variant
|
|
uvrange |
| UV range: ” ==> all; uvrange =”0~100klambda”,
default units=meters | |
| allowed: | any |
|
| Default: | variant
|
|
timerange |
| Time range: ” ==> all,timerange=”09:14:0~09:54:0”
| |
| allowed: | any |
|
| Default: | variant
|
|
correlation |
| Correlation: ” ==> all, correlation=”XX,YY”
| |
| allowed: | any |
|
| Default: | variant
|
|
scan |
| Scan numbers: ” ==> all
| |
| allowed: | any |
|
| Default: | variant
|
|
intent |
| Scan intent: ” ==> all, intent=”CAL*POINT*”
| |
| allowed: | any |
|
| Default: | variant
|
|
array |
| (Sub)array numbers: ” ==> all
| |
| allowed: | any |
|
| Default: | variant
|
|
observation |
| Observation ID: ” ==> all
| |
| allowed: | any |
|
| Default: | variant
|
|
feed |
| Multi-feed numbers: Not yet implemented
| |
| allowed: | any |
|
| Default: | variant
|
|
clipminmax |
| Range to use for clipping
| |
| allowed: | any |
|
| Default: | variant
|
|
datacolumn |
| Data column on which to operate
(data,corrected,model,weight,etc.)
| |
| allowed: | any |
|
| Default: | variant DATA | |
clipoutside |
| Clip outside the range, or within it
| |
| allowed: | any |
|
| Default: | variant True | |
channelavg |
| Pre-average data across channels before analyzing
visibilities for flagging
| |
| allowed: | any |
|
| Default: | variant False | |
chanbin |
| Bin width for channel average in number of input
channels | |
| allowed: | any |
|
| Default: | variant 1 | |
timeavg |
| Pre-average data across time before analyzing visibilities
for flagging.
| |
| allowed: | any |
|
| Default: | variant False | |
timebin |
| Bin width for time average in seconds
| |
| allowed: | string |
|
| Default: | 0s | |
clipzeros |
| Clip zero-value data
| |
| allowed: | bool | |
| Default: | False |
|
quackinterval |
| Quack n seconds from scan beginning or end
| |
| allowed: | any |
|
| Default: | variant 1.0 | |
quackmode |
| Quack mode. beg: first n seconds of scan; endb: last n
seconds of scan; end: all but first n seconds of scan; tail:
all but last n seconds of scan. | |
| allowed: | any |
|
| Default: | variant beg |
|
quackincrement |
| Flag incrementally in time?
| |
| allowed: | any |
|
| Default: | variant False |
|
tolerance |
| Amount of shadow allowed (in meters)
| |
| allowed: | double | |
| Default: | 0.0 |
|
addantenna |
| File name or dictionary with additional antenna names,
positions and diameters
| |
| allowed: | any |
|
| Default: | variant
|
|
lowerlimit |
| Lower limiting elevation (in degrees)
| |
| allowed: | double | |
| Default: | 0.0 |
|
upperlimit |
| Upper limiting elevation (in degrees)
| |
| allowed: | double | |
| Default: | 90.0 |
|
ntime |
| Time-range to use for each chunk (in seconds or minutes)
| |
| allowed: | any |
|
| Default: | variant scan | |
combinescans |
| Accumulate data across scans depending on the value of
ntime. | |
| allowed: | bool |
|
| Default: | False | |
timecutoff |
| Flagging thresholds in units of deviation from the fit
| |
| allowed: | double | |
| Default: | 4.0 |
|
freqcutoff |
| Flagging thresholds in units of deviation from the fit
| |
| allowed: | double | |
| Default: | 3.0 |
|
timefit |
| Fitting function for the time direction (poly/line)
| |
| allowed: | string |
|
| Default: | line |
|
freqfit |
| Fitting function for the frequency direction (poly/line)
| |
| allowed: | string |
|
| Default: | poly |
|
maxnpieces |
| Number of pieces in the polynomial-fits (for ”freqfit” or
”timefit” = ”poly”)
| |
| allowed: | int |
|
| Default: | 7 |
|
flagdimension |
| Dimensions along which to calculate fits
(freq/time/freqtime/timefreq)
| |
| allowed: | string |
|
| Default: | freqtime |
|
usewindowstats |
| Calculate additional flags using sliding window statistics
(none,sum,std,both)
| |
| allowed: | string |
|
| Default: | none |
|
halfwin |
| Half-width of sliding window to use with
”usewindowstats” (1,2,3).
| |
| allowed: | int |
|
| Default: | 1 |
|
extendflags |
| Extend flags along time, frequency and correlation.
| |
| allowed: | bool |
|
| Default: | True |
|
winsize |
| Number of timesteps in the sliding time window
[aips:fparm(1)]
| |
| allowed: | int |
|
| Default: | 3 |
|
timedev |
| Time-series noise estimate [aips:noise]
| |
| allowed: | any |
|
| Default: | variant
|
|
freqdev |
| Spectral noise estimate [aips:scutoff]
| |
| allowed: | any |
|
| Default: | variant
|
|
timedevscale |
| Threshold scaling for timedev [aips:fparm(9)]
| |
| allowed: | double |
|
| Default: | 5.0 |
|
freqdevscale |
| Threshold scaling for freqdev [aips:fparm(10)]
| |
| allowed: | double |
|
| Default: | 5.0 |
|
spectralmax |
| Flag whole spectrum if freqdev is greater than
spectralmax [aips:fparm(6)]
| |
| allowed: | double |
|
| Default: | 1E6 |
|
spectralmin |
| Flag whole spectrum if freqdev is less than spectralmin
[aips:fparm(5)]
| |
| allowed: | double |
|
| Default: | 0.0 |
|
antint_ref_antenna |
| Antenna of interest. Baselines with this antenna will be
checked for flagged channels.
| |
| allowed: | string |
|
| Default: |
|
|
minchanfrac |
| Minimum fraction of flagged channels required for a
baseline to be deemed as flagged
| |
| allowed: | double |
|
| Default: | 0.6 |
|
verbose |
| Print timestamps of flagged integrations to the log
| |
| allowed: | bool |
|
| Default: | False |
|
extendpols |
| If any correlation is flagged, flag all correlations
| |
| allowed: | any |
|
| Default: | True |
|
growtime |
| Flag all ”ntime” integrations if more than X% of the
timerange is flagged (0-100)
| |
| allowed: | double |
|
| Default: | 50.0 |
|
growfreq |
| Flag all selected channels if more than X% of the
frequency range is flagged(0-100)
| |
| allowed: | double |
|
| Default: | 50.0 |
|
growaround |
| Flag data based on surrounding flags
| |
| allowed: | bool |
|
| Default: | False |
|
flagneartime |
| Flag one timestep before and after a flagged one
(True/False)
| |
| allowed: | bool |
|
| Default: | False |
|
flagnearfreq |
| Flag one channel before and after a flagged one
(True/False)
| |
| allowed: | bool |
|
| Default: | False |
|
minrel |
| minimum number of flags (relative)
| |
| allowed: | double |
|
| Default: | 0.0 |
|
maxrel |
| maximum number of flags (relative)
| |
| allowed: | double |
|
| Default: | 1.0 |
|
minabs |
| minimum number of flags (absolute)
| |
| allowed: | int |
|
| Default: | 0 |
|
maxabs |
| maximum number of flags (absolute). Use a negative
value to indicate infinity.
| |
| allowed: | int |
|
| Default: | -1 |
|
spwchan |
| Print summary of channels per spw
| |
| allowed: | bool |
|
| Default: | False |
|
spwcorr |
| Print summary of correlation per spw
| |
| allowed: | bool |
|
| Default: | False |
|
basecnt |
| Print summary counts per baseline
| |
| allowed: | bool |
|
| Default: | False |
|
fieldcnt |
| Produce a separated breakdown for each field
| |
| allowed: | bool |
|
| Default: | False |
|
name |
| Name of this summary report (key in summary
dictionary)
| |
| allowed: | string |
|
| Default: | Summary |
|
action |
| Action to perform in MS and/or in inpfile
(none/apply/calculate)
| |
| allowed: | string |
|
| Default: | apply |
|
display |
| Display data and/or end-of-MS reports at runtime
(data/report/both).
| |
| allowed: | string |
|
| Default: |
|
|
flagbackup |
| Back up the state of flags before the run
| |
| allowed: | bool |
|
| Default: | True |
|
savepars |
| Save the current parameters to the FLAG_CMD table
or to a file
| |
| allowed: | bool |
|
| Default: | False |
|
cmdreason |
| Reason to save to output file or to FLAG_CMD table.
| |
| allowed: | string |
|
| Default: |
|
|
outfile |
| Name of output file to save current parameters. If empty,
save to FLAG_CMD
| |
| allowed: | string |
|
| Default: |
|
|
overwrite |
| Overwrite an existing file to save the flag commands
| |
| allowed: | bool |
|
| Default: | True |
|
writeflags |
| Internal hidden parameter. Do not modify.
| |
| allowed: | bool |
|
| Default: | True |
|
void
Example
----- Detailed description of keyword arguments -----
vis -- Name of input visibility file or calibration table.
default: ’’ (none)
example1: vis=’uid___A002_X2a5c2f_X54.ms’ or
example2: vis=’cal-X54.B1’
Any flagging will only be applied to the specified selections.
antenna -- Select data based on baseline
default: ’’ (all); example: antenna=’DV04&DV06’ baseline DV04-DV06
antenna=’DV04&DV06;DV07&DV10’ #baselines DV04-DV06 and DV07-DV10
antenna=’DV06’ # all cross-correlation baselines between antenna DV06 and
all other available antennas
antenna=’DV04,DV06’ # all baselines with antennas DV04 and DV06
antenna=’DV06&&DV06’ # only the auto-correlation baselines for antenna DV06
antenna=’DV04&&*’ # cross and auto-correlation baselines between antenna DV04
and all other available antennas
antenna=’0~2&&&’ # only the auto-correlation baselines for antennas
in range 0~2
Note that for some antenna-based calibration tables, selecting baselines with
the & syntax do not apply.
spw -- Select data based on spectral window and channels
default: ’’ (all); example: spw=’1’
spw=’<2’ #spectral windows less than 2
spw=’>1’ #spectral windows greater than 1
spw=’1:0~10’ # first 10 channels from spw 1
spw=’1:0~5;120~128’ # multiple separated channel chunks.
Note : For modes clip, tfcrop and rflag, channel-ranges can be excluded
from flagging by leaving them out of the selection range. This is a way to
protect known spectral-lines from being flagged by the autoflag algorithms.
Example: if spectral-lines fall in channels 6~9, set the selection range to
spw=’0:0~5;10~63’.
correlation -- Correlation types or expression.
default: ’’ (all correlations)
For modes clip, tfcrop or rflag, the default means ABS_ALL. If
the input is cal table that does not contain a complex data column,
the default will fall back to REAL_ALL.
example: correlation=’XX,YY’ or
options: Any of ’ABS’, ’ARG’, ’REAL’, ’IMAG’, ’NORM’ followed by
any of ’ALL’, ’I’, ’XX’, ’YY’, ’RR’, ’LL’, ’WVR’
’WVR’ refers to the water vapour radiometer of ALMA data.
For calibration tables, the solutions are: ’Sol1’, ’Sol2’, Sol3, Sol4.
example: correlation=’REAL_XX,XY’
-->correlation selection is not supported for modes other than clip, tfcrop or
rflag in cal tables.
Note that the operators ABS,ARG,REAL, etc. are written only once as the first value.
if more than one correlation is given, the operator will be applied to all of them.
The expression is used only in modes clip, tfcrop and rflag.
field -- Select data based on field id(s) or name(s)
default: ’’ (all); example: field=’1’
field=’0~2’ # field ids inclusive from 0 to 2
field=’3C*’ # all field names starting with 3C
uvrange -- Select data within uvrange (default units meters)
default: ’’ (all); example:
uvrange=’0~1000klambda’; uvrange from 0-1000 kilo-lambda
uvrange=’>4klamda’;uvranges greater than 4 kilo-lambda
uvrange=’0~1000km’; uvrange in kilometers
-->uvrange selection is not supported for cal tables.
timerange -- Select data based on time range:
default = ’’ (all); example,
timerange = ’YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss’
Note: YYYY/MM/DD can be dropped as needed:
timerange=’09:14:0~09:54:0’ # this time range
timerange=’09:44:00’ # data within one integration of time
timerange=’>10:24:00’ # data after this time
timerange=’09:44:00+00:13:00’ #data 13 minutes after time
scan -- Select data based on scan number
default: ’’ (all); example: scan=’>3’
intent -- Select data based on scan intent
default: ’’ (all); example: intent=’*CAL*,*BAND*’
-->intent selection is not supported for cal tables.
array -- Selection based on the antenna array
default: ’’ (all);
-->array selection is not supported for cal tables.
observation -- Selection based on the observation ID
default: ’’ (all); example: observation=’1’ or observation=1
feed -- Selection based on the feed - NOT IMPLEMENTED YET
mode -- Mode of operation.
options: ’list’, ’manual’,’clip’,’quack’,’shadow’,’elevation’, ’tfcrop’, ’antint’,
’extend’, ’unflag’, ’summary’
default: ’manual’
------------------------------------- LIST MODE -----------------------------------------------
list -- Flag according to the data selection and flag commands specified in the input list.
The input list may come from a text file, a list of text files or from a Python list
of strings. Each input line may contain data selection parameters and any parameter
specific to the mode given in the line. Default values will be used for
the parameters that are not present in the line. Each line will be taken
as a command to the task. If data is pre-selected using any of the selection
parameters, then flagging will apply only to that subset of the MS.
For optimization and whenever possible, the task will create a union of the data selection
parameters present in the list and select only that portion of the MS.
NOTE: the flag commands will be applied only when action=’apply’. If
action=’calculate’ the flags will be calculated, but not applied.
This is useful if display is set to something other than ’none’. If
action=’’ or ’none’, the flag commands will not be applied either.
An empty action is useful only to save the parameters of the list
to a file or to the FLAG_CMD sub-table.
inpfile -- Input ASCII file, list of files or a Python list of command strings.
default: ’’
options: [] with flag commands or
[] with filenames or
’’ with a filename.
IMPORTANT: From CASA 4.3 onwards, the parser will be strict and accept only
valid flagdata parameters in the list. It will check each parameter
name and type and exit with an error if any of them is wrong.
String values must contain quotes around them or the parser
will not work. The parser evaluates the commands in the list
and considers only existing Python types.
NOTE: There should be no whitespace between KEY=VALUE since the parser
first breaks command lines on whitespace, then on "=". Use only one whitespace
to separate the parameters (no commas). Scroll down to the bottom to see
a detailed description of the input list syntax.
Example1: the following commands can be saved to a file or group of files
and given to the task (e.g. save it to flags.txt).
scan=’1~3’ mode=’manual’
mode=’clip’ clipminmax=[0,2] correlation=’ABS_XX’ clipoutside=False
spw=’9’ mode=’tfcrop’ correlation=’ABS_YY’ ntime=51.0
mode=’extend’ extendpols=True
flagdata(vis, mode=’list’, inpfile=’flags.txt’) or
flagdata(vis, mode=’list’, inpfile=[’onlineflags.txt’,’otherflags.txt’])
Example2: the same commands can be given in a Python list on the command line
to the task.
cmd=["scan=’1~3’ mode=’manual’",
"mode=’clip’ clipminmax=[0,2] correlation=’ABS_XX’ clipoutside=False",
"spw=’9’ mode=’tfcrop’ correlation=’ABS_YY’ ntime=51.0",
"mode=’extend’ extendpols=True"]
flagdata(vis,mode=’list’,inpfile=cmd)
reason -- select flag commands based on REASON(s) .
default: ’any’ (all flags regardless of reason)
can be a string, or list of strings
example: reason=’FOCUS_ERROR’
reason=[’FOCUS_ERROR’,’SUBREFLECTOR_ERROR’]
If inpfile is a list of files, the reasons given in this
parameter will apply to all the files.
NOTE: what is within the string is literally
matched, e.g. reason=’’ matches only blank reasons,
and reason = ’FOCUS_ERROR,SUBREFLECTOR_ERROR’
matches this compound reason string only.
See the syntax for writing flag commands at the end of this help.
tbuff -- A time buffer or list of time buffers to pad the timerange parameters
in flag commands. When a list of 2 time buffers is given, it will
subtract the first value from the lower time and the second value will be
added to the upper time in the range. The 2 time buffer values can be different,
allowing to have an irregular time buffer padding to time ranges.
If the list contains only one time buffer, it will use it to subtract
from t0 and add to t1. If more than one list of input files is given,
tbuff will apply to all of the flag commands that have timerange parameters in the files.
Each tbuff value should be a Float number given in seconds.
default: 0.0 (it will not apply any time padding)
example: tbuff=[0.5, 0.8]
inpfile=[’online.txt’,’userflags.txt’]
The timeranges in the online.txt file are first converted to seconds.
Then, 0.5 is subtracted from t0 and 0.8 is added to t1,
where t0 and t1 are the two intervals given in timerange. Similarly,
tbuff will be applied to any timerange in userflags.txt.
IMPORTANT: This parameter assumes that timerange = t0 ~ t1, therefore it will
not work if only t0 or t1 is given.
NOTE: The most common use-case for tbuff is to apply the online flags
that are created by importasdm when savecmds=True. The value of
a regular time buffer should be tbuff=0.5*max(integration time).
------------------------------------- MANUAL MODE -----------------------------------------------
manual -- Flag according to the data selection specified.
This is the default mode (used when the mode is not specified).
autocorr -- Flag only the auto-correlations. Note that this parameter is only
active when set to True. If set to False it does NOT mean "do not
flag auto-correlations". When set to True, it will only flag
data from a processor of type CORRELATOR.
default: False
options: True,False
------------------------------------- CLIP MODE -----------------------------------------------
clip -- Clip data according to values of the following subparameters. The polarization
expression is given by the correlation parameter. For calibration tables, the
solutions are also given by the correlation parameter.
datacolumn -- Column to use for clipping.
default: ’DATA’
options: MS columns: ’DATA’, ’CORRECTED’,’MODEL’, ’RESIDUAL’, ’RESIDUAL_DATA’,
’WEIGHT_SPECTRUM’, ’WEIGHT’, ’FLOAT_DATA’.
Cal table columns: ’FPARAM’, ’CPARAM’, ’SNR’,’WEIGHT’.
NOTE1: RESIDUAL = CORRECTED - MODEL
RESIDUAL_DATA = DATA - MODEL
NOTE2: when datacolumn is WEIGHT, the task will internally use WEIGHT_SPECTRUM.
If WEIGHT_SPECTRUM does not exist, it will create one on-the-fly
based on the values of WEIGHT.
clipminmax -- Range of data (Jy) that will NOT be flagged.
default: []; it will flag only NaN and Infs.
example: [0.0,1.5]
It will always flag the NaN/Inf data, even when a range is specified.
clipoutside -- Clip OUTSIDE the range?
default: True
example: False; flag data WITHIN the clipminmax range.
channelavg -- Pre-average data across channels before analyzing visibilities for flagging.
Partially flagged data is not be included in the average unless all data
contributing to a given output channel is flagged. If present, WEIGHT_SPECTRUM /
SIGMA_SPECTRUM are used to compute a weighted average (WEIGHT_SPECTRUM for
CORRECTED_DATA and SIGMA_SPECTRUM for DATA).
default: False
options: True/False
NOTE1: Pre-average across channels is not supported in list mode.
NOTE2: Pre-average across channels is not supported for calibration tables
chanbin -- Bin width for channel average in number of input channels.
If a list is given, each bin applies to one of the selected SPWs.
When chanbin is set to 1 all input channels are used considered for the
average to produce a single output channel, this behaviour aims to be preserve
backwards compatibility with the previous pre-averaging feature of clip mode.
default: 1
timeavg -- Pre-average data across time before analyzing visibilities for flagging.
Partially flagged data is not be included in the average unless all data
contributing to a given output channel is flagged. If present, WEIGHT_SPECTRUM /
SIGMA_SPECTRUM are used to compute a weighted average (WEIGHT_SPECTRUM for
CORRECTED_DATA and SIGMA_SPECTRUM for DATA). Otherwise WEIGHT/SIGMA are used to
average together data from different integrations.
default: False
options: True/False
NOTE1: Pre-average across time is not supported in list mode.
NOTE2: Pre-average across time is not supported for calibration tables
timebin -- Bin width for time average in seconds.
default: ’0s’
clipzeros -- Clip zero-value data.
default: False
------------------------------------- QUACK MODE -----------------------------------------------
quack -- Option to remove specified part of scan beginning/end.
quackinterval -- Time in seconds from scan beginning or end to flag. Make time slightly
smaller than the desired time.
default: 0.0
type: int or float
quackmode -- Quack mode
default: ’beg’
options: ’beg’ ==> flag an interval at the beginning of scan
’endb’ ==> flag an interval at the end of scan
’tail’ ==> flag all but an interval at the beginning of scan
’end’ ==> flag all but an interval at end of scan
Visual representation of quack mode flagging one scan with 1s duration.
The following diagram shows what is flagged for each quack mode when
quackinterval is set to 0.25s. The flagged part is represented by crosses (+++++++++)
scan with 1s duration
--------------------------------------------
beg
+++++++++++---------------------------------
endb
---------------------------------+++++++++++
tail
-----------+++++++++++++++++++++++++++++++++
end
+++++++++++++++++++++++++++++++++-----------
quackincrement -- Quack incrementally in time?
default: False
type: bool
False ==> the quack interval is counted from the
beginning of the scan
True ==> the quack interval is counted from the
first unflagged data in the scan
shadow -- Option to flag data of shadowed antennas. This mode is not available
for cal tables.
All antennas in the antenna-subtable of the MS (and the corresponding
diameters) will be considered for shadow-flag calculations.
For a given timestep, an antenna is flagged if any of its baselines
(projected onto the uv-plane) is shorter than radius_1 + radius_2 - tolerance.
The value of ’w’ is used to determine which antenna is behind the other.
The phase-reference center is used for antenna-pointing direction.
tolerance -- Amount of shadowing allowed (or tolerated), in meters.
A positive number allows antennas to overlap in projection
A negative number forces antennas apart in projection
Zero implies a distance of radius_1+radius_2 between antenna centers.
default: 0.0
addantenna -- It can be either a file name with additional antenna names, positions
and diameters, or a Python dictionary with the same information.
You can use the flaghelper functions to create the dictionary from a file.
default: ’’
type: string or {}
To create a dictionary inside casapy.
> import flaghelper as fh
> antdic = fh.readAntennaList(antfile)
Where antfile is a text file in disk that contains information such as:
name=VLA01
diameter=25.0
position=[-1601144.96146691, -5041998.01971858, 3554864.76811967]
name=VLA02
diameter=25.0
position=[-1601105.7664601889, -5042022.3917835914, 3554847.245159178]
------------------------------------- ELEVATION MODE -----------------------------------------------
elevation -- Option to flag based on antenna elevation. This mode is not available
for cal tables.
lowerlimit -- Lower limiting elevation in degrees. Data coming from a baseline
where one or both antennas were pointing at a strictly lower elevation
(as function of time), will be flagged.
default: 0.0
upperlimit -- Upper limiting elevation in degrees. Data coming from a baseline
where one or both antennas were pointing at a strictly higher elevation
(as function of time), will be flagged.
default: 90.0
------------------------------------- TFCROP MODE -----------------------------------------------
tfcrop -- Flag using the TFCrop autoflag algorithm.
For each field, spw, timerange (specified by ntime), and baseline,
(1) Average visibility amplitudes along time dimension to
form an average spectrum
(2) Calculate a robust piece-wise polynomial fit for the band-shape
at the base of RFI spikes. Calculate ’stddev’ of (data - fit).
(3) Flag points deviating from the fit by more than N-stddev
(4) Repeat (1-3) along the other dimension.
This algorithm is designed to operate on un-calibrated data (step (2)),
as well as calibrated data. It is recommended to extend the flags
after running this algorithm. See the sub-parameter extendflags below.
ntime -- Timerange (in seconds or minutes) over which to buffer data before
running the algorithm.
options: ’scan’ or any other float value or string containing the units.
default: ’scan’
example: ’1.5min’
: 1.2 (taken in seconds)
The dataset will be iterated through in time-chunks defined here.
WARNING: if ntime=’scan’ and combinescans=True, all the scans will
be loaded at once, thus requesting a lot of memory depending on the
available spws.
combinescans -- Accumulate data across scans depending on the value of ntime.
default: False
This parameter should be set to True only when ntime is specified as a
time-interval (not ’scan’). When set to True, it will remove SCAN from the
sorting columns, therefore it will only accumulate across scans if
ntime is not set to ’scan’.
datacolumn -- Column to use for flagging. (See also the datacolumn explanation in clip)
default: ’DATA’
options: MS columns: ’DATA’, ’CORRECTED’,’MODEL’, ’RESIDUAL’, ’RESIDUAL_DATA’,
’WEIGHT_SPECTRUM’, ’WEIGHT’, ’FLOAT_DATA’.
Cal table columns: ’FPARAM’, ’CPARAM’, ’SNR’,’WEIGHT’.
timecutoff -- Flag threshold in time. Flag all data-points further than N-stddev
from the fit. This threshold catches time-varying RFI spikes (
narrow and broad-band), but will not catch RFI that is persistent in time.
default: 4.0
Flagging is done in upto 5 iterations. The stddev calculation is adaptive and
converges to a value that reflects only the data and no RFI. At each iteration,
the same relative threshold is applied to detect flags. (Step (3) of the algorithm).
freqcutoff -- Flag threshold in frequency. Flag all data-points further than N-stddev
from the fit.
default: 3.0
Same as timecutoff, but along the frequency-dimension. This threshold catches
narrow-band RFI that may or may not be persistent in time.
timefit -- Fitting function for the time direction
default: ’line’
options: ’line’, ’poly’
A ’line’ fit is a robust straight-line fit across the entire timerange (defined
by ’ntime’).
A ’poly’ fit is a robust piece-wise polynomial fit across the timerange.
Note: A robust fit is computed in upto 5 iterations. At each iteration, the stddev
between the data and the fit is computed, values beyond N-stddev are flagged,
and the fit and stddev are re-calculated with the remaining points.
This stddev calculation is adaptive, and converges to a value that reflects
only the data and no RFI. It also provides a varying set of flagging thresholds,
that allows deep flagging only when the fit best represents the true data.
Choose ’poly’ only if the visibilities are expected to vary significantly over the
timerange selected by ’ntime’, or if there is a lot of strong but intermittent RFI.
freqfit -- Fitting function for the frequency direction
default: ’poly’
options: ’line’,’poly’
Same as for the ’timefit’ parameter.
Choose ’line’ only if you are operating on bandpass-corrected data, or residuals,
and expect that the bandshape is linear. The ’poly’ option works better on
uncalibrated bandpasses with narrow-band RFI spikes.
maxnpieces -- Maxinum number of pieces to allow in the piecewise-polynomial fits
default: 7
options: 1 - 9
This parameter is used only if ’timefit’ or ’freqfit’ are chosen as ’poly’.
If there is significant broad-band RFI, reduce this number. Using too many
pieces could result in the RFI being fitted in the ’clean’ bandpass.
In later stages of the fit, a third-order polynomial is fit per piece, so
for best results, please ensure that nchan/maxnpieces is at-least 10.
flagdimension -- Choose the directions along which to perform flagging
default: ’freqtime’; first flag along frequency, and then along time
options: ’time’, ’freq’, ’timefreq’, ’freqtime’
For most cases, ’freqtime’ or ’timefreq’ are appropriate, and differences
between these choices are apparant only if RFI in one dimension is
significantly stronger than the other. The goal is to flag the dominant RFI first.
If there are very few (less than 5) channels of data, then choose ’time’.
Similarly for ’freq’.
usewindowstats -- Use sliding-window statistics to find additional flags.
default: ’none’
options: ’none’, ’sum’, ’std’, ’both’
Note: This is experimental !
The ’sum’ option chooses to flag a point, if the mean-value in a
window centered on that point deviates from the fit by more than
N-stddev/2.0.
Note: stddev is calculated between the data and fit as explained in Step (2).
This option is an attempt to catch broad-band or
time-persistent RFI that the above polynomial fits will mistakenly fit
as the clean band. It is an approximation to the sumThreshold
method found to be effective by Offringa et.al (2010) for LOFAR data.
The ’std’ option chooses to flag a point, if the ’local’ stddev calculated
in a window centered on that point is larger than N-stddev/2.0.
This option is an attempt to catch noisy RFI that is not excluded in the
polynomial fits, and which increases the global stddev, and results in
fewer flags (based on the N-stddev threshold).
halfwin -- Half width of sliding window to use with ’usewindowstats’
default: 1 (a 3-point window size)
options: 1,2,3
Note: This is experimental !
extendflags -- Extend flags along time, frequency and correlation.
default: True
NOTE: It is usually helpful to extend the flags along time, frequency,
and correlation using this parameter, which will run the "extend"
mode after "tfcrop" and extend the flags if more than 50% of the
timeranges are already flagged, and if more than 80% of the channels
are already flagged. It will also extend the flags to the other
polarizations. The user may also set extendflags to False and run
the "extend" mode in a second step within the same flagging run. See
the example below:
example :
cmd=["mode=’tfcrop’ freqcutoff=3.0 usewindowstats=’sum’ extendflags=False",
"mode=’extend’ extendpols=True growtime=50.0 growaround=True"]
flagdata(vis, mode=’list’, inpfile=cmd)
channelavg -- Pre-average data across channels before analyzing visibilities for flagging.
Partially flagged data is not be included in the average unless all data
contributing to a given output channel is flagged. If present, WEIGHT_SPECTRUM /
SIGMA_SPECTRUM are used to compute a weighted average (WEIGHT_SPECTRUM for
CORRECTED_DATA and SIGMA_SPECTRUM for DATA).
default: False
options: True/False
NOTE1: Pre-average across channels is not supported in list mode.
NOTE2: Pre-average across channels is not supported for calibration tables
chanbin -- Bin width for channel average in number of input channels.
If a list is given, each bin applies to one of the selected SPWs.
When chanbin is set to 1 all input channels are used considered for the
average to produce a single output channel.
default: 1
timeavg -- Pre-average data across time before analyzing visibilities for flagging.
Partially flagged data is not be included in the average unless all data
contributing to a given output channel is flagged. If present, WEIGHT_SPECTRUM /
SIGMA_SPECTRUM are used to compute a weighted average (WEIGHT_SPECTRUM for
CORRECTED_DATA and SIGMA_SPECTRUM for DATA). Otherwise WEIGHT/SIGMA are used to
average together data from different integrations.
default: False
options: True/False
NOTE1: Pre-average across time is not supported in list mode.
NOTE2: Pre-average across time is not supported for calibration tables
timebin -- Bin width for time average in seconds.
default: ’0s’
------------------------------------- RFLAG MODE -----------------------------------------------
rflag -- Detect outliers based on the RFlag algorithm (ref. E.Greisen, AIPS, 2011).
The polarization expression is given by the correlation parameter.
Iterate through the data in chunks of time. For each chunk, calculate local
statistics, and apply flags based on user supplied (or auto-calculated) thresholds.
Step 1 : Time analysis (for each channel)
-- calculate local rms of real and imag visibilities, within a sliding time window
-- calculate the median rms across time windows, deviations of local rms from
this median, and the median deviation
-- flag if local rms is larger than timedevscale x (medianRMS + medianDev)
Step 2 : Spectral analysis (for each time)
-- calculate avg of real and imag visibilities and their rms across channels
-- calculate the deviation of each channel from this avg, and the median-deviation
-- flag if deviation is larger than freqdevscale x medianDev
It is recommended to extend the flags after running this algorithm.
See the sub-parameter extendflags below.
Notice that by default the flag implementation in CASA is able to calculate the
thresholds and apply them on-the-fly (OTF). There is a significant performance
gain with this approach, as the visibilities don’t have to be read twice,
and therefore is highly recommended (see example 1). Otherwise it is possible to
reproduce the AIPS usage pattern by doing a first run with ’calculate’ mode and
a second run with ’apply’ mode. The advantage of this approach is that the thresholds
are calculated using the data from all scans, instead of calculating them for
one scan only (see example 3)
Example usage :
(1) Calculate thresholds automatically per scan, and use them to find flags.
Specify scale-factor for time-analysis thresholds, use default for frequency.
flagdata(’my.ms’, mode=’rflag’,spw=’9’,timedevscale=4.0)
(2) Supply noise-estimates to be used with default scale-factors.
flagdata(vis=’my.ms’, mode=’rflag’, spw=’9’, timedev=0.1, freqdev=0.5, action=’calculate’)
(3) Two-passes. This replicates the usage pattern in AIPS.
-- The first pass saves commands in an output text files, with auto-calculated
thresholds. Thresholds are returned from rflag only when action=’calculate’.
The user can edit this file before doing the second pass,
but the python-dictionary structure must be preserved.
-- The second pass applies these commands (action=’apply’).
flagdata(vis=’my.ms’, mode=’rflag’, spw=’9,10’, timedev=’tdevfile.txt’,
freqdev=’fdevfile.txt’, action=’calculate’)
flagdata(vis=’my.ms’, mode=’rflag’, spw=’9,10’, timedev=’tdevfile.txt’,
freqdev=’fdevfile.txt’, action=’apply’)
With action=’calculate’, display=’report’ will produce diagnostic plots
showing data-statistics and thresholds (the same thresholds as those
written out to ’tdevfile.txt’ and ’fdevfile.txt’).
Note : The RFlag algorithm was originally developed by Eric Greisen in
AIPS (31DEC11).
AIPS documentation : Section E.5 of the AIPS cookbook
(Appendix E : Special Considerations for EVLA data calibration and imaging in AIPS,
http://www.aips.nrao.edu/cook.html#CEE )
Note1 : Since this algorithm operates with two passes through each
chunk of data (time and freq axes), some data points get flagged
twice. This can affect the flag-percentage estimate printed in the
logger at runtime. An accurate estimate can be obtained via the
summary mode.
Note2: RFlag calculates statistics across all selected correlations.
Therefore, if there is a significant amplitude difference between
parallel-hand and cross-hand correlations, or between different
solutions in a gain table, it is advisable to pre-select subsets of
correlations (or sols) on which to run one instance of RFlag.
For example, correlation=’RR,LL’ or correlation=’ABS sol1,sol2’.
ntime -- Timerange (in seconds or minutes) over which to buffer data before running
the algorithm.
options: ’scan’ or any other float value or string containing the units.
default: ’scan’
example: ’1.5min’
: 1.2 (taken in seconds)
The dataset will be iterated through in time-chunks defined here.
WARNING: if ntime=’scan’ and combinescans=True, all the scans will
be loaded at once, thus requesting a lot of memory depending on the
available spws.
combinescans -- Accumulate data across scans depending on the value of ntime.
default: False
This parameter should be set to True only when ntime is specified as a
time-interval (not ’scan’). When set to True, it will remove SCAN from the
sorting columns, therefore it will only accumulate across scans if
ntime is not set to ’scan’.
datacolumn -- Column to use for flagging. (See also the datacolumn explanation in clip)
default: ’DATA’
options: MS columns: ’DATA’, ’CORRECTED’,’MODEL’, ’RESIDUAL’, ’RESIDUAL_DATA’,
’WEIGHT_SPECTRUM’, ’WEIGHT’, ’FLOAT_DATA’.
Cal table columns: ’FPARAM’, ’CPARAM’, ’SNR’,’WEIGHT’.
winsize -- number of timesteps in the sliding time window ( fparm(1) in AIPS ).
default: 3
timedev -- time-series noise estimate ( noise in AIPS ).
default: []
Examples :
timedev = 0.5 : Use this noise-estimate to calculate flags. Do not recalculate.
timedev = [ [1,9,0.2], [1,10,0.5] ] : Use noise-estimate of 0.2 for field 1,
spw 9, and noise-estimate of 0.5 for field 1, spw 10.
timedev = [] : Auto-calculate noise estimates.
freqdev -- spectral noise estimate ( scutoff in AIPS ).
This step depends on having a relatively-flat bandshape.
Same parameter-options as ’timedev’.
default: []
timedevscale -- For Step 1 (time analysis), flag a point if local rms around it
is larger than ’timedevscale’ x ’timedev’ ( fparm(0) in AIPS )
default: 5.0
freqdevscale -- For Step 2 (spectral analysis), flag a point if local rms around it
is larger than ’freqdevscale’ x ’freqdev’ ( fparm(10) in AIPS )
default: 5.0
spectralmax -- Flag whole spectrum if ’freqdev’ is greater than spectralmax ( fparm(6) in AIPS )
default: 1E6
spectralmin -- Flag whole spectrum if ’freqdev’ is less than spectralmin ( fparm(5) in AIPS )
default: 0.0
extendflags -- Extend flags along time, frequency and correlation.
default: True
NOTE: It is usually helpful to extend the flags along time, frequency,
and correlation using this parameter, which will run the "extend"
mode after "rflag" and extend the flags if more than 50% of the
timeranges are already flagged, and if more than 80% of the channels
are already flagged. It will also extend the flags to the other
polarizations. The user may also set extendflags to False and run
the "extend" mode in a second step within the same flagging run. See
the example below:
example :
cmd=["mode=’rflag’ freqdevscale=3.0 extendflags=False",
"mode=’extend’ extendpols=True growtime=50.0 growaround=True"]
flagdata(vis, mode=’list’, inpfile=cmd)
channelavg -- Pre-average data across channels before analyzing visibilities for flagging.
Partially flagged data is not be included in the average unless all data
contributing to a given output channel is flagged. If present, WEIGHT_SPECTRUM /
SIGMA_SPECTRUM are used to compute a weighted average (WEIGHT_SPECTRUM for
CORRECTED_DATA and SIGMA_SPECTRUM for DATA).
default: False
options: True/False
NOTE1: Pre-average across channels is not supported in list mode.
NOTE2: Pre-average across channels is not supported for calibration tables
chanbin -- Bin width for channel average in number of input channels.
If a list is given, each bin applies to one of the selected SPWs.
When chanbin is set to 1 all input channels are used considered for the
average to produce a single output channel.
default: 1
timeavg -- Pre-average data across time before analyzing visibilities for flagging.
Partially flagged data is not be included in the average unless all data
contributing to a given output channel is flagged. If present, WEIGHT_SPECTRUM /
SIGMA_SPECTRUM are used to compute a weighted average (WEIGHT_SPECTRUM for
CORRECTED_DATA and SIGMA_SPECTRUM for DATA). Otherwise WEIGHT/SIGMA are used to
average together data from different integrations.
default: False
options: True/False
NOTE1: Pre-average across time is not supported in list mode.
NOTE2: Pre-average across time is not supported for calibration tables
timebin -- Bin width for time average in seconds.
default: ’0s’
------------------------------------- ANTINT MODE -----------------------------------------------
antint -- Flag integrations if all baselines to a specified antenna are flagged
This mode flag all integrations in which a specified antenna is flagged.
This mode operates for an spectral window. It flags any integration in
which all baselines to a specified antenna are flagged, but only if this
condition is satisfied in a fraction of channels within the spectral
window of interest greater than a nominated fraction. For simplicity, it
assumes that all polarization products must be unflagged for a baseline to
be deemed unflagged. The antint mode implements the flagging approach
introduced in ’antintflag’ (https://doi.org/10.5281/zenodo.163546)
The motivating application for introducing this mode is removal of data
that will otherwise lead to changes in reference antenna during gain
calibration, which will in turn lead to corrupted polarization
calibration.
antint_ref_antenna -- Check the baselines to this antenna. Note that this is
not the same as the general ’antenna’ parameter of flagdata.
The parameter antint_ref_antenna is mandatory with the
’antint’ mode and chooses the antenna for which the
fraction of channels flagged will be checked.
minchanfrac -- Minimum fraction of flagged channels required for a baseline
to be deemed as flagged. Takes values between 0-1 (float).
In this mode flagdata does the following for every point in
time. It checks the fraction of channels flagged for any of
the polarization products and for every baseline to the antenna
of interest. If the fraction is higher than this ’minchanfrac’
threshold then the data are flagged for this pont in time
(this includes all the rows selected with the flagdata command
that have that timestamp).
This parameter will be ignored if spw specifies a channel.
verbose -- Print timestamps of flagged integrations to the log
Example1:
flagdata(vis, ..., spw=’9’, antint_ref_antenna=’ea01’)
Example2:
Here we reduce the fraction of channels that are required to be
flagged, and print information for every integratino that is
flagged.
flagdata(vis, ..., spw=’9’, antint_ref_antenna=’ea01’, minchanfrac=0.3, verbose=True)
------------------------------------- EXTEND MODE -----------------------------------------------
extend -- Extend and/or grow flags beyond what the basic algorithms detect.
This mode will extend the accumulated flags available in the MS,
regardless of which algorithm created them.
It is recommended that any autoflag (tfcrop, rflag) algorithm be followed
up by a flag extension.
Extensions will apply only within the selected data, according to the settings
of extendpols,growtime,growfreq,growaround, flagneartime,flagnearfreq.
Note : Runtime summary counts in the logger can sometimes report larger
flag percentages than what is actually flagged. This is because
extensions onto already-flagged data-points are counted as new flags.
An accurate flag count can be obtained via the summary mode.
ntime -- Timerange (in seconds or minutes) over which to buffer data before running
the algorithm.
options: ’scan’ or any other float value or string containing the units.
default: ’scan’
example: ’1.5min’
: 1.2 (taken in seconds)
The dataset will be iterated through in time-chunks defined here.
WARNING: if ntime=’scan’ and combinescans=True, all the scans will
be loaded at once, thus requesting a lot of memory depending on the
available spws.
combinescans -- Accumulate data across scans depending on the value of ntime.
default: False
This parameter should be set to True only when ntime is specified as a
time-interval (not ’scan’). When set to True, it will remove SCAN from the
sorting columns, therefore it will only accumulate across scans if
ntime is not set to ’scan’.
extendpols -- Extend flags to all selected correlations
default: True
options: True/False
For example, to extend flags from RR to only RL and LR, a data-selection
of correlation=’RR,LR,RL’ is required along with extendpols=True.
growtime -- For any channel, flag the entire timerange in the current 2D chunk (
set by ’ntime’) if more than X% of the timerange is already flagged.
default: 50.0
options: 0.0 - 100.0
This option catches the low-intensity parts of time-persistent RFI.
growfreq -- For any timestep, flag all channels in the current 2D chunk (set by
data-selection) if more than X% of the channels are already flagged.
default: 50.0
options: 0.0 - 100.0
This option catches broad-band RFI that is partially identified by earlier steps.
growaround -- Flag a point based on the number of flagged points around it.
default: False
options: True/False
For every un-flagged point on the 2D time/freq plane, if more than four
surrounding points are already flagged, flag that point.
This option catches some wings of strong RFI spikes.
flagneartime -- Flag points before and after every flagged one, in the time-direction.
default: False
options: True/False
Note: This can result in excessive flagging.
flagnearfreq -- Flag points before and after every flagged one, in the frequency-direction
default: False
options: True/False
This option allows flagging of wings in the spectral response of strong RFI.
Note: This can result in excessive flagging
------------------------------------- UNFLAG MODE -----------------------------------------------
unflag -- Unflag according to the data selection specified.
------------------------------------- SUMMARY MODE -----------------------------------------------
summary -- List the number of rows and flagged data points for the MS’s meta-data.
The resulting summary will be returned as a Python dictionary.
minrel -- Minimum number of flags (relative) to include in histogram
default: 0.0
maxrel -- Maximum number of flags (relative) to include in histogram
default: 1.0
minabs -- Minimum number of flags (absolute, inclusive) to include in histogram
default: 0
maxabs -- Maximum number of flags (absolute, inclusive) to include in histogram
To indicate infinity, use any negative number.
default: -1
spwchan -- list the number of flags per spw and per channel.
default: False
spwcorr -- list the number of flags per spw and per correlation.
default: False
basecnt -- list the number of flags per baseline
default: False
fieldcnt -- produce a separated breakdown per field
default: False
name -- Name for this summary, to be used as a key in the returned
Python dictionary. It is possible to call the summary mode
multiple times in list mode. When calling the summary mode as a
command in a list, one can give different names to each one of
them so that they can be easily pulled out of the summary’s dictionary.
default: ’Summary’
In summary mode, the task returns a dictionary of flagging statistics.
Example1:
s = flagdata(..., mode=’summary’)
Then s will be a dictionary which contains
s[’total’] : total number of data
s[’flagged’] : amount of flagged data
Exmaple2: two summary commands in list mode, intercalating a manual flagging command.
s = flagdata(..., mode=’list’, inpfile=["mode=’summary’ name=’InitFlags’",
"mode=’manual’ autocorr=True",
"mode=’summary’ name=’Autocorr’"])
The dictionary returned in ’s’ will contain two dictionaries, one for each of the
two summary modes.
s[’report0’][’name’] : ’InitFlags’
s[’report1’][’name’] : ’Autocorr’
------------------------------------- ACTIONS -----------------------------------------------
action -- Action to perform in MS/cal table or in the input list of parameters.
options: ’none’, ’apply’,’calculate’
default: ’apply’
’apply’ -- Apply the flags to the MS.
display -- Display data and/or end-of-MS reports at run-time. It needs to read
a datacolumn for the plotting. The default for an MS is DATA, but the task
will use FLOAT_DATA for a Sindle-dish MS.
default: ’none’
options: ’none’, ’data’, ’report’, ’both’
’none’ --> It will not display anything.
’data’ --> display data and flags per-chunk at run-time, within an interactive GUI.
This option opens a GUI to show the 2D time-freq planes of
the data with old and new flags, for all correlations per baseline.
-- The GUI allows stepping through all baselines (prev/next) in
the current chunk (set by ’ntime’), and stepping to the next-chunk.
-- The ’flagdata’ task can be quit from the GUI, in case it becomes
obvious that the current set of parameters is just wrong.
-- There is an option to stop the display but continue flagging.
’report’ --> displays end-of-MS reports on the screen.
’both’ --> displays data per chunk and end-of-MS reports on the screen
flagbackup -- Automatically backup flags before running the tool.
Flagversion names are chosen automatically, and are based on the
mode being used.
default: True
options: True/False
’calculate’ -- Only calculate the flags but do not write them to the MS. This is
useful if used together with the display to analyse the results before
writing to the MS.
display -- Display data and/or end-of-MS reports at run-time. See extended description
above.
default: ’none’
options: ’none’, ’data’, ’report’, ’both’
’ ’ -- When set to empty, the underlying tool will not be executed and no flags
will be produced. No data selection will be done either. This is useful
when used together with the parameter savepars to only save the current
parameters (or list of parameters) to the FLAG_CMD sub-table or to an
external file.
savepars -- Save the current parameters to the FLAG_CMD table of the MS or to an output text file.
Note that when display is set to anything other than ’none’, savepars
will be disabled. This is done because in an interactive mode, the user
may skip data which may invalidate the initial input parameters and there
is no way to save the interactive commands. When the input is a calibration
table it is only possible to save the parameters to a file.
default: False
options: True/False
cmdreason -- A string containing a reason to save to the FLAG_CMD table or to an
output text file given by the outfile sub-parameter. If the input
contains any reason, they will be replaced with this one. At the
moment it is not possible to add more than one reason.
default: ’ ’; no reason will be added to output.
example: cmdreason=’CLIP_ZEROS’
outfile -- Name of output file to save the current parameters.
default: ’ ’; it will save the parameters to the FLAG_CMD table of the MS.
example: outfile=’flags.txt’ will save the parameters in a text file.
overwrite -- Overwrite the existing file given in ’outfile’.
options: True/False
default: True; it will remove the existing file given in ’outfile’ and save the current flag
commands to a new file with the same name. When set to False, the task will exit with
an error message if the file exist.
---- EXAMPLES ----
NOTE: The vector mode of the flagdata task (pre-dating CASA 3.4) can be achieved with this task
by using it with mode=’list’ and the commands given in a list in inpmode=[]. Example:
flagdata(’my.ms’, inpmode=’list’, inpfile=["mode=’clip’ clipzeros=True","mode=’shadow’])
1) Manually flag scans 1~3 and save the parameters to the FLAG_CMD sub-table.
flagdata(’my.ms’, scan=’1~3, mode=’manual’, savepars=True)
2) Save the parameters to a file that is open in append mode.
flagdata(’my.ms’, scan=’1~3, mode=’manual’, savepars=True, outfile=’flags.txt’)
3a) Flag all the commands given in the Python list of strings.
cmd = ["scan=’1~3’ mode=’manual’",
"spw=’9’ mode=’tfcrop’ correlation=’ABS_RR,LL’ ntime=51.0",
"mode=’extend’ extendpols=True"]
flagdata(’my.ms’, mode=’list’, inpfile=cmd)
3b) Flag all the commands given in the file called flags.txt.
> cat flags.txt
scan=’1~3’ mode=’manual’
spw=’9’ mode=’tfcrop’ correlation=’ABS_RR,LL’ ntime=51.0
mode=’extend’ extendpols=True
flagdata(’my.ms’, mode=’list’, inpfile=’flags.txt’)
4) Display the data and flags per-chunk and do not write flags to the MS.
flagdata(’my.ms’, mode=’list’, inpfile=’flags.txt’, action=’calculate’, display=’data’)
5) Flag all the antennas except antenna=5.
flagdata(vis=’my.ms’, antenna=’!5’, mode=’manual)
6) Clip the NaN in the data. An empty clipminmax will flag only NaN.
flagdata(’my.ms’, mode=’clip’)
7) Clip only the water vapour radiometer data.
flagdata(’my.ms’,mode=’clip’,clipminmax=[0,50], correlation=’ABS_WVR’)
8) Clip only zero-value data.
flagdata(’my.ms’,mode=’clip’,clipzeros=True)
9a) Flag only auto-correlations of non-radiometer data using the autocorr parameter.
flagdata(’my.ms’, autocorr=True)
9b) Flag only auto-correlations using the antenna selection.
flagdata(’my.ms’, mode=’manual’, antenna=’*&&&’)
10a) Flag based on selected reasons from a file.
> cat flags.txt
scan=’1~3’ mode=’manual’ reason=’MYREASON’
spw=’9’ mode=’clip’ clipzeros=True reason=’CLIPZEROS’
mode=’manual’ scan=’4’ reason=’MYREASON’
flagdata(’my.ms’, mode=’list’, inpfile=’flags.txt’, reason=’MYREASON’)
10b) The same as above but using task flagcmd.
flagcmd(’my.ms’, inpmode=’file’, inpfile=’flags.txt’, action=’apply’, reason=’MYREASON’)
11) Automatic flagging using ’rflag’, using auto-thresholds, and specifying
a threshold scale-factor to use for flagging.
flagdata(’my.ms’, mode=’rflag’,spw=’9’,timedevscale=4.0,action=’apply’)
12) Save the interface parameters to the FLAG_CMD sub-table of the MS. Add a reason
to the flag command. This cmdreason will be added to the REASON column of the
FLAG_CMD sub-table. Apply flags in flagcmd.
flagdata(’my.ms’, mode=’clip’,channelavg=False, clipminmax=[30., 60.], spw=’0:0~10’,
correlation=’ABS_XX,XY’, action=’’, savepars=True, cmdreason=’CLIPXX_XY’)
> Select based on the reason.
flagcmd(’my.ms’, action=’apply’, reason=’CLIPXX_XY’)
13) Flag antennas that are shadowed by antennas not present in the MS.
> Create a text file with information about the antennas.
> cat ant.txt
name=VLA01
diameter=25.0
position=[-1601144.96146691, -5041998.01971858, 3554864.76811967]
name=VLA02
diameter=25.0
position=[-1601105.7664601889, -5042022.3917835914, 3554847.245159178]
name=VLA09
diameter=25.0
position=[-1601197.2182404203, -5041974.3604805721, 3554875.1995636248]
name=VLA10
diameter=25.0
position=[-1601227.3367843349,-5041975.7011900628,3554859.1642644769]
flagdata(’my.vis’, mode=’shadow’, tolerance=10.0, addantenna=’ant.txt’)
The antenna information can also be given as a Python dictionary. To create the
dictionary using the flaghelper functions, do the following inside casapy:
> import flaghelper as fh
> antdic = fh.readAntennaList(antfile)
flagdata(’my.vis’, mode=’shadow’, tolerance=10.0, addantenna=antdic)
14) Apply the online flags that come from importasdm.
> In importasdm, save the online flags to a file.
importasdm(’myasdm’, ’asdm.ms’, process_flags=True, savecmds=True, outfile=’online_flags.txt’)
> You can edit the online_flags.txt to add other flagging commands or apply it directly.
flagdata(’asdm.ms’, mode=’list’, inpfile=’online_flags.txt’)
> The same result can be achieved using the task flagcmd.
flagcmd(’asdm.ms’, inpmode=’file’, inpfile=’online_flags.txt’, action=’apply’)
15) Clip mode pre-averaging data across channels and across time
flagdata(vis=’Four_ants_3C286.ms’, flagbackup=False, mode=’clip’, datacolumn=’DATA’,
timeavg=True, timebin=’2s’, channelavg=True, chanbin=2)
------ EXAMPLES on FLAGGING CALIBRATION TABLES ------
16) Clip zero data from a bandpass calibration table.
flagdata(’cal-X54.B1’, mode=’clip’, clipzeros=True, datacolumn=’CPARAM’)
17) Clip data from a cal table with SNR <4.0.
flagdata(’cal-X54.B1’, mode=’clip’, clipminmax=[0.0,4.0], clipoutside=False, datacolumn=’SNR’)
18) Clip the g values of a switched power caltable created using the gencal task. The g values are
usually < 1.0.
flagdata(’cal.12A.syspower’,mode=’clip’,clipminmax=[0.1,0.3],correlation=’Sol1,Sol3’,datacolumn=’FPARAM’)
19) Now, clip the Tsys values of the same table from above. The Tsys solutions have values between
10 -- 100s.
flagdata(’cal.12A.syspower’,mode=’clip’,clipminmax=[10.0,95.0],correlation=’Sol2,Sol4’,datacolumn=’FPARAM’)
---- SYNTAX FOR COMMANDS GIVEN IN A FILE or LIST OF STRINGS ----
Basic Syntax Rules
Commands are strings (which may contain internal "strings") consisting of
KEY=VALUE pairs separated by one whitespace only.
NOTE: There should be no whitespace between KEY=VALUE.The parser first breaks
command lines on whitespace, then on "=".
Use only ONE white space to separate the parameters (no commas).
Each key should only appear once on a given command line/string.
There is an implicit "mode" for each command, with the default
being ’manual’ if not given.
Comment lines can start with ’#’ and will be ignored.
The parser used in flagdata will check each parameter name and type and
exit with an error if the parameter is not a valid flagdata parameter or
of a wrong type.
Example:
scan=’1~3’ mode=’manual’
# this line will be ignored
spw=’9’ mode=’tfcrop’ correlation=’ABS_XX,YY’ ntime=51.0
mode=’extend’ extendpols=True
scan=’1~3,10~12’ mode=’quack’ quackinterval=1.0
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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