##################### generated by xml-casa (v2) from hsd_blflag.xml ################
##################### f151a976ee2dbb445bded36b19ebbec6 ##############################
from __future__ import absolute_import
import numpy
from casatools.typecheck import CasaValidator as _val_ctor
_pc = _val_ctor( )
from casatools.coercetype import coerce as _coerce
from .private.task_hsd_blflag import hsd_blflag as _hsd_blflag_t
from casatasks.private.task_logging import start_log as _start_log
from casatasks.private.task_logging import end_log as _end_log
class _hsd_blflag:
"""
hsd_blflag ---- Flag spectra based on predefined criteria of single dish pipeline
Data are flagged based on several flagging rules. Available rules are:
expected rms, calculated rms, and running mean of both pre-fit and
post-fit spectra. Tsys flagging is also available.
In addition, the heuristics script creates many plots for each stage.
Those plots are included in the weblog.
Output:
results -- If pipeline mode is 'getinputs' then None is returned. Otherwise
the results object for the pipeline task is returned.
--------- parameter descriptions ---------------------------------------------
iteration Number of iterations to perform sigma clipping to
calculate threshold value of flagging.
edge Number of channels to be dropped from the edge.
The value must be a list of integer with length of one or
two. If list length is one, same number will be applied
both side of the band.
example: [10,20], [10]
flag_tsys Activate (True) or deactivate (False) Tsys flag.
tsys_thresh Threshold value for Tsys flag.
flag_weath Activate (True) or deactivate (False) weather flag.
Since weather flagging is not implemented yet,
setting True has no effect at the moment.
weath_thresh Threshold value for weather flag.
flag_prfre Activate (True) or deactivate (False) flag by expected
rms of pre-fit spectra.
prfre_thresh Threshold value for flag by expected rms of pre-fit
spectra.
flag_pofre Activate (True) or deactivate (False) flag by expected
rms of post-fit spectra.
pofre_thresh Threshold value for flag by expected rms of post-fit
spectra.
flag_prfr Activate (True) or deactivate (False) flag by rms of
pre-fit spectra.
prfr_thresh Threshold value for flag by rms of pre-fit spectra.
flag_pofr Activate (True) or deactivate (False) flag by rms of
post-fit spectra.
pofr_thresh Threshold value for flag by rms of post-fit spectra.
flag_prfrm Activate (True) or deactivate (False) flag by running
mean of pre-fit spectra.
prfrm_thresh Threshold value for flag by running mean of pre-fit
spectra.
prfrm_nmean Number of channels for running mean of pre-fit spectra.
flag_pofrm Activate (True) or deactivate (False) flag by running
mean of post-fit spectra.
pofrm_thresh Threshold value for flag by running mean of post-fit
spectra.
pofrm_nmean Number of channels for running mean of post-fit spectra.
flag_user Activate (True) or deactivate (False) user-defined flag.
Since user flagging is not implemented yet, setting True
has no effect at the moment.
user_thresh Threshold value for flag by user-defined rule.
plotflag True to plot result of data flagging.
pipelinemode The pipeline operating mode. In 'automatic' mode the
pipeline determines the values of all context defined
pipeline inputs automatically. In interactive mode
the user can set the pipeline context defined parameters
manually. In 'getinputs' mode the user can check the
settings of all pipeline parameters without running
the task.
infiles ASDM or MS files to be processed. This parameter behaves
as data selection parameter. The name specified by
infiles must be registered to context before you run
hsd_blflag.
antenna Data selection by antenna names or ids.
example: 'PM03,PM04'
'' (all antennas)
field Data selection by field names or ids.
example: '*Sgr*,M100'
'' (all fields)
spw Data selection by spw ids.
example: '3,4' (spw 3 and 4)
'' (all spws)
pol Data selection by polarizations.
example: 'XX,YY' (correlation XX and YY)
'' (all polarizations)
dryrun Run the commands (True) or generate the commands to be
run but do not execute (False).
acceptresults Add the results of the task to the pipeline context (True)
or reject them (False).
parallel Execute using CASA HPC functionality, if available.
--------- examples -----------------------------------------------------------
"""
_info_group_ = """pipeline"""
_info_desc_ = """Flag spectra based on predefined criteria of single dish pipeline"""
def __call__( self, iteration=int(5), edge=[ int(0),int(0) ], flag_tsys=True, tsys_thresh=float(3.0), flag_weath=False, weath_thresh=float(3.0), flag_prfre=True, prfre_thresh=float(3.0), flag_pofre=True, pofre_thresh=float(1.3333), flag_prfr=True, prfr_thresh=float(4.5), flag_pofr=True, pofr_thresh=float(4.0), flag_prfrm=True, prfrm_thresh=float(5.5), prfrm_nmean=int(5), flag_pofrm=True, pofrm_thresh=float(5.0), pofrm_nmean=int(5), flag_user=False, user_thresh=float(5.0), plotflag=True, pipelinemode='automatic', infiles=[ ], antenna='', field='', spw='', pol='', dryrun=False, acceptresults=True, parallel='automatic' ):
schema = {'iteration': {'type': 'cInt'}, 'edge': {'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}, 'flag_tsys': {'type': 'cBool'}, 'tsys_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'flag_weath': {'type': 'cBool'}, 'weath_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'flag_prfre': {'type': 'cBool'}, 'prfre_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'flag_pofre': {'type': 'cBool'}, 'pofre_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'flag_prfr': {'type': 'cBool'}, 'prfr_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'flag_pofr': {'type': 'cBool'}, 'pofr_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'flag_prfrm': {'type': 'cBool'}, 'prfrm_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'prfrm_nmean': {'type': 'cInt'}, 'flag_pofrm': {'type': 'cBool'}, 'pofrm_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'pofrm_nmean': {'type': 'cInt'}, 'flag_user': {'type': 'cBool'}, 'user_thresh': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'plotflag': {'type': 'cBool'}, 'pipelinemode': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'automatic', 'interactive', 'getinputs' ]}, 'infiles': {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}, 'antenna': {'type': 'cStr', 'coerce': _coerce.to_str}, 'field': {'type': 'cStr', 'coerce': _coerce.to_str}, 'spw': {'type': 'cStr', 'coerce': _coerce.to_str}, 'pol': {'type': 'cStr', 'coerce': _coerce.to_str}, 'dryrun': {'type': 'cBool'}, 'acceptresults': {'type': 'cBool'}, 'parallel': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'automatic', 'true', 'false' ]}}
doc = {'iteration': iteration, 'edge': edge, 'flag_tsys': flag_tsys, 'tsys_thresh': tsys_thresh, 'flag_weath': flag_weath, 'weath_thresh': weath_thresh, 'flag_prfre': flag_prfre, 'prfre_thresh': prfre_thresh, 'flag_pofre': flag_pofre, 'pofre_thresh': pofre_thresh, 'flag_prfr': flag_prfr, 'prfr_thresh': prfr_thresh, 'flag_pofr': flag_pofr, 'pofr_thresh': pofr_thresh, 'flag_prfrm': flag_prfrm, 'prfrm_thresh': prfrm_thresh, 'prfrm_nmean': prfrm_nmean, 'flag_pofrm': flag_pofrm, 'pofrm_thresh': pofrm_thresh, 'pofrm_nmean': pofrm_nmean, 'flag_user': flag_user, 'user_thresh': user_thresh, 'plotflag': plotflag, 'pipelinemode': pipelinemode, 'infiles': infiles, 'antenna': antenna, 'field': field, 'spw': spw, 'pol': pol, 'dryrun': dryrun, 'acceptresults': acceptresults, 'parallel': parallel}
assert _pc.validate(doc,schema), str(_pc.errors)
_logging_state_ = _start_log( 'hsd_blflag', [ 'iteration=' + repr(_pc.document['iteration']), 'edge=' + repr(_pc.document['edge']), 'flag_tsys=' + repr(_pc.document['flag_tsys']), 'tsys_thresh=' + repr(_pc.document['tsys_thresh']), 'flag_weath=' + repr(_pc.document['flag_weath']), 'weath_thresh=' + repr(_pc.document['weath_thresh']), 'flag_prfre=' + repr(_pc.document['flag_prfre']), 'prfre_thresh=' + repr(_pc.document['prfre_thresh']), 'flag_pofre=' + repr(_pc.document['flag_pofre']), 'pofre_thresh=' + repr(_pc.document['pofre_thresh']), 'flag_prfr=' + repr(_pc.document['flag_prfr']), 'prfr_thresh=' + repr(_pc.document['prfr_thresh']), 'flag_pofr=' + repr(_pc.document['flag_pofr']), 'pofr_thresh=' + repr(_pc.document['pofr_thresh']), 'flag_prfrm=' + repr(_pc.document['flag_prfrm']), 'prfrm_thresh=' + repr(_pc.document['prfrm_thresh']), 'prfrm_nmean=' + repr(_pc.document['prfrm_nmean']), 'flag_pofrm=' + repr(_pc.document['flag_pofrm']), 'pofrm_thresh=' + repr(_pc.document['pofrm_thresh']), 'pofrm_nmean=' + repr(_pc.document['pofrm_nmean']), 'flag_user=' + repr(_pc.document['flag_user']), 'user_thresh=' + repr(_pc.document['user_thresh']), 'plotflag=' + repr(_pc.document['plotflag']), 'pipelinemode=' + repr(_pc.document['pipelinemode']), 'infiles=' + repr(_pc.document['infiles']), 'antenna=' + repr(_pc.document['antenna']), 'field=' + repr(_pc.document['field']), 'spw=' + repr(_pc.document['spw']), 'pol=' + repr(_pc.document['pol']), 'dryrun=' + repr(_pc.document['dryrun']), 'acceptresults=' + repr(_pc.document['acceptresults']), 'parallel=' + repr(_pc.document['parallel']) ] )
return _end_log( _logging_state_, 'hsd_blflag', _hsd_blflag_t( _pc.document['iteration'], _pc.document['edge'], _pc.document['flag_tsys'], _pc.document['tsys_thresh'], _pc.document['flag_weath'], _pc.document['weath_thresh'], _pc.document['flag_prfre'], _pc.document['prfre_thresh'], _pc.document['flag_pofre'], _pc.document['pofre_thresh'], _pc.document['flag_prfr'], _pc.document['prfr_thresh'], _pc.document['flag_pofr'], _pc.document['pofr_thresh'], _pc.document['flag_prfrm'], _pc.document['prfrm_thresh'], _pc.document['prfrm_nmean'], _pc.document['flag_pofrm'], _pc.document['pofrm_thresh'], _pc.document['pofrm_nmean'], _pc.document['flag_user'], _pc.document['user_thresh'], _pc.document['plotflag'], _pc.document['pipelinemode'], _pc.document['infiles'], _pc.document['antenna'], _pc.document['field'], _pc.document['spw'], _pc.document['pol'], _pc.document['dryrun'], _pc.document['acceptresults'], _pc.document['parallel'] ) )
hsd_blflag = _hsd_blflag( )