##################### generated by xml-casa (v2) from hif_mstransform.xml ###########
##################### 252461e8e4304dd31cdc3fe294239fdf ##############################
from __future__ import absolute_import
from casashell.private.stack_manip import find_local as __sf__
from casashell.private.stack_manip import find_frame as _find_frame
from casatools.typecheck import validator as _pc
from casatools.coercetype import coerce as _coerce
from pipeline.hif.cli import hif_mstransform as _hif_mstransform_t
from collections import OrderedDict
import numpy
import sys
import os
import shutil
[docs]def static_var(varname, value):
def decorate(func):
setattr(func, varname, value)
return func
return decorate
class _hif_mstransform:
"""
hif_mstransform ---- Create new MeasurementSets for science target imaging
Create new MeasurementSets for imaging from the corrected column of the input
MeasurementSet. By default all science target data is copied to the new MS. The
new MeasurementSet is not re-indexed to the selected data and the new MS will
have the same source, field, and spw names and ids as it does in the parent MS.
Output
results -- If pipeline mode is 'getinputs' then None is returned. Otherwise
the results object for the pipeline task is returned.
--------- parameter descriptions ---------------------------------------------
vis The list of input MeasurementSets. Defaults to the list of
MeasurementSets specified in the h_init or hif_importdata task.
'': use all MeasurementSets in the context
Examples: 'ngc5921.ms', ['ngc5921a.ms', ngc5921b.ms', 'ngc5921c.ms']
outputvis The list of output transformed MeasurementSets to be used for
imaging. The output list must be the same length as the input
list. The default output name defaults to
<msrootname>_target.ms
Examples: 'ngc5921.ms',
['ngc5921a.ms', ngc5921b.ms', 'ngc5921c.ms']
field Select fields name(s) or id(s) to transform. Only fields with
data matching the intent will be selected.
Examples: '3C279', 'Centaurus*', '3C279,J1427-421'
intent Select intents for which associated fields will be imaged.
By default only TARGET data is selected.
Examples: 'PHASE,BANDPASS'
spw Select spectral window/channels to image. By default all
science spws for which the specified intent is valid are
selected .
chanbin Width (bin) of input channels to average to form an output
channel. If chanbin > 1 then chanaverage is automatically
switched to True.
timebin Bin width for time averaging. If timebin > 0s then
timeaverage is automatically switched to True.
pipelinemode The pipeline operating modeThe 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.
dryrun Run the task (False) or just display the command (True)
acceptresults Add the results of the task to the pipeline context (True) or
reject them (False).
--------- examples -----------------------------------------------------------
1. Create a science target MS from the corrected column in the input MS.
hif_mstransform()
2. Make a phase and bandpass calibrator targets MS from the corrected
column in the input MS.
hif_mstransform(intent='PHASE,BANDPASS')
"""
_info_group_ = """pipeline"""
_info_desc_ = """Create new MeasurementSets for science target imaging"""
__schema = {'vis': {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}, 'outputvis': {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}, 'field': {'type': 'cStr', 'coerce': _coerce.to_str}, 'intent': {'type': 'cStr', 'coerce': _coerce.to_str}, 'spw': {'type': 'cStr', 'coerce': _coerce.to_str}, 'chanbin': {'type': 'cInt'}, 'timebin': {'type': 'cStr', 'coerce': _coerce.to_str}, 'pipelinemode': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'automatic', 'interactive', 'getinputs' ]}, 'dryrun': {'type': 'cBool'}, 'acceptresults': {'type': 'cBool'}}
def __init__(self):
self.__stdout = None
self.__stderr = None
self.__root_frame_ = None
def __globals_(self):
if self.__root_frame_ is None:
self.__root_frame_ = _find_frame( )
assert self.__root_frame_ is not None, "could not find CASAshell global frame"
return self.__root_frame_
def __to_string_(self,value):
if type(value) is str:
return "'%s'" % value
else:
return str(value)
def __validate_(self,doc,schema):
return _pc.validate(doc,schema)
def __do_inp_output(self,param_prefix,description_str,formatting_chars):
out = self.__stdout or sys.stdout
description = description_str.split( )
prefix_width = 23 + 16 + 4
output = [ ]
addon = ''
first_addon = True
while len(description) > 0:
## starting a new line.....................................................................
if len(output) == 0:
## for first line add parameter information............................................
if len(param_prefix)-formatting_chars > prefix_width - 1:
output.append(param_prefix)
continue
addon = param_prefix + ' #'
first_addon = True
addon_formatting = formatting_chars
else:
## for subsequent lines space over prefix width........................................
addon = (' ' * prefix_width) + '#'
first_addon = False
addon_formatting = 0
## if first word of description puts us over the screen width, bail........................
if len(addon + description[0]) - addon_formatting + 1 > self.term_width:
## if we're doing the first line make sure it's output.................................
if first_addon: output.append(addon)
break
while len(description) > 0:
## if the next description word puts us over break for the next line...................
if len(addon + description[0]) - addon_formatting + 1 > self.term_width: break
addon = addon + ' ' + description[0]
description.pop(0)
output.append(addon)
out.write('\n'.join(output) + '\n')
#--------- return nonsubparam values ----------------------------------------------
def __timebin_dflt( self, glb ):
return '0s'
def __timebin( self, glb ):
if 'timebin' in glb: return glb['timebin']
return '0s'
def __pipelinemode_dflt( self, glb ):
return 'automatic'
def __pipelinemode( self, glb ):
if 'pipelinemode' in glb: return glb['pipelinemode']
return 'automatic'
def __chanbin_dflt( self, glb ):
return int(1)
def __chanbin( self, glb ):
if 'chanbin' in glb: return glb['chanbin']
return int(1)
#--------- return inp/go default --------------------------------------------------
def __dryrun_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return bool(False)
return None
def __field_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return ""
if self.__pipelinemode( glb ) == "getinputs": return ""
return None
def __outputvis_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return []
if self.__pipelinemode( glb ) == "getinputs": return []
return None
def __intent_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return ""
if self.__pipelinemode( glb ) == "getinputs": return ""
return None
def __vis_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return []
if self.__pipelinemode( glb ) == "getinputs": return []
return None
def __acceptresults_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return bool(True)
return None
def __spw_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return ""
if self.__pipelinemode( glb ) == "getinputs": return ""
return None
#--------- return subparam values -------------------------------------------------
def __vis( self, glb ):
if 'vis' in glb: return glb['vis']
dflt = self.__vis_dflt( glb )
if dflt is not None: return dflt
return [ ]
def __outputvis( self, glb ):
if 'outputvis' in glb: return glb['outputvis']
dflt = self.__outputvis_dflt( glb )
if dflt is not None: return dflt
return [ ]
def __field( self, glb ):
if 'field' in glb: return glb['field']
dflt = self.__field_dflt( glb )
if dflt is not None: return dflt
return ''
def __intent( self, glb ):
if 'intent' in glb: return glb['intent']
dflt = self.__intent_dflt( glb )
if dflt is not None: return dflt
return ''
def __spw( self, glb ):
if 'spw' in glb: return glb['spw']
dflt = self.__spw_dflt( glb )
if dflt is not None: return dflt
return ''
def __dryrun( self, glb ):
if 'dryrun' in glb: return glb['dryrun']
dflt = self.__dryrun_dflt( glb )
if dflt is not None: return dflt
return False
def __acceptresults( self, glb ):
if 'acceptresults' in glb: return glb['acceptresults']
dflt = self.__acceptresults_dflt( glb )
if dflt is not None: return dflt
return True
#--------- subparam inp output ----------------------------------------------------
def __vis_inp(self):
if self.__vis_dflt( self.__globals_( ) ) is not None:
description = 'The list of input MeasurementSets'
value = self.__vis( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'vis': value},{'vis': self.__schema['vis']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('vis',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __outputvis_inp(self):
if self.__outputvis_dflt( self.__globals_( ) ) is not None:
description = 'The list of transformed MeasurementSets to be used for imaging'
value = self.__outputvis( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'outputvis': value},{'outputvis': self.__schema['outputvis']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('outputvis',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __field_inp(self):
if self.__field_dflt( self.__globals_( ) ) is not None:
description = 'Set of data selection field names or ids, \'\' for all'
value = self.__field( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'field': value},{'field': self.__schema['field']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('field',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __intent_inp(self):
if self.__intent_dflt( self.__globals_( ) ) is not None:
description = 'Set of data selection intents'
value = self.__intent( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'intent': value},{'intent': self.__schema['intent']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('intent',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __spw_inp(self):
if self.__spw_dflt( self.__globals_( ) ) is not None:
description = 'Set of data selection spectral window ids \'\' for all'
value = self.__spw( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'spw': value},{'spw': self.__schema['spw']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('spw',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __chanbin_inp(self):
description = 'Width (bin) of input channels to average to form an output channel.'
value = self.__chanbin( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'chanbin': value},{'chanbin': self.__schema['chanbin']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output('%-16.16s = %s%-23s%s' % ('chanbin',pre,self.__to_string_(value),post),description,0+len(pre)+len(post))
def __timebin_inp(self):
description = 'Bin width for time averaging.'
value = self.__timebin( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'timebin': value},{'timebin': self.__schema['timebin']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output('%-16.16s = %s%-23s%s' % ('timebin',pre,self.__to_string_(value),post),description,0+len(pre)+len(post))
def __pipelinemode_inp(self):
description = 'The pipeline operating mode'
value = self.__pipelinemode( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'pipelinemode': value},{'pipelinemode': self.__schema['pipelinemode']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output('\x1B[1m\x1B[47m%-16.16s =\x1B[0m %s%-23s%s' % ('pipelinemode',pre,self.__to_string_(value),post),description,13+len(pre)+len(post))
def __dryrun_inp(self):
if self.__dryrun_dflt( self.__globals_( ) ) is not None:
description = 'Run the task (False) or just display the command (True)'
value = self.__dryrun( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'dryrun': value},{'dryrun': self.__schema['dryrun']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('dryrun',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __acceptresults_inp(self):
if self.__acceptresults_dflt( self.__globals_( ) ) is not None:
description = 'Add the results to the pipeline context'
value = self.__acceptresults( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'acceptresults': value},{'acceptresults': self.__schema['acceptresults']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('acceptresults',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
#--------- global default implementation-------------------------------------------
@static_var('state', __sf__('casa_inp_go_state'))
def set_global_defaults(self):
self.set_global_defaults.state['last'] = self
glb = self.__globals_( )
if 'dryrun' in glb: del glb['dryrun']
if 'field' in glb: del glb['field']
if 'pipelinemode' in glb: del glb['pipelinemode']
if 'outputvis' in glb: del glb['outputvis']
if 'intent' in glb: del glb['intent']
if 'vis' in glb: del glb['vis']
if 'acceptresults' in glb: del glb['acceptresults']
if 'timebin' in glb: del glb['timebin']
if 'chanbin' in glb: del glb['chanbin']
if 'spw' in glb: del glb['spw']
#--------- inp function -----------------------------------------------------------
def inp(self):
print("# hif_mstransform -- %s" % self._info_desc_)
self.term_width, self.term_height = shutil.get_terminal_size(fallback=(80, 24))
self.__vis_inp( )
self.__outputvis_inp( )
self.__field_inp( )
self.__intent_inp( )
self.__spw_inp( )
self.__chanbin_inp( )
self.__timebin_inp( )
self.__pipelinemode_inp( )
self.__dryrun_inp( )
self.__acceptresults_inp( )
#--------- tget function ----------------------------------------------------------
@static_var('state', __sf__('casa_inp_go_state'))
def tget(self,file=None):
from casashell.private.stack_manip import find_frame
from runpy import run_path
filename = None
if file is None:
if os.path.isfile("hif_mstransform.last"):
filename = "hif_mstransform.last"
elif isinstance(file, str):
if os.path.isfile(file):
filename = file
if filename is not None:
glob = find_frame( )
newglob = run_path( filename, init_globals={ } )
for i in newglob:
glob[i] = newglob[i]
self.tget.state['last'] = self
else:
print("could not find last file, setting defaults instead...")
self.set_global_defaults( )
def __call__( self, vis=None, outputvis=None, field=None, intent=None, spw=None, chanbin=None, timebin=None, pipelinemode=None, dryrun=None, acceptresults=None ):
def noobj(s):
if s.startswith('<') and s.endswith('>'):
return "None"
else:
return s
_prefile = os.path.realpath('hif_mstransform.pre')
_postfile = os.path.realpath('hif_mstransform.last')
_return_result_ = None
_arguments = [vis,outputvis,field,intent,spw,chanbin,timebin,pipelinemode,dryrun,acceptresults]
_invocation_parameters = OrderedDict( )
if any(map(lambda x: x is not None,_arguments)):
# invoke python style
# set the non sub-parameters that are not None
local_global = { }
if chanbin is not None: local_global['chanbin'] = chanbin
if timebin is not None: local_global['timebin'] = timebin
if pipelinemode is not None: local_global['pipelinemode'] = pipelinemode
# the invocation parameters for the non-subparameters can now be set - this picks up those defaults
_invocation_parameters['chanbin'] = self.__chanbin( local_global )
_invocation_parameters['timebin'] = self.__timebin( local_global )
_invocation_parameters['pipelinemode'] = self.__pipelinemode( local_global )
# the sub-parameters can then be set. Use the supplied value if not None, else the function, which gets the appropriate default
_invocation_parameters['vis'] = self.__vis( _invocation_parameters ) if vis is None else vis
_invocation_parameters['outputvis'] = self.__outputvis( _invocation_parameters ) if outputvis is None else outputvis
_invocation_parameters['field'] = self.__field( _invocation_parameters ) if field is None else field
_invocation_parameters['intent'] = self.__intent( _invocation_parameters ) if intent is None else intent
_invocation_parameters['spw'] = self.__spw( _invocation_parameters ) if spw is None else spw
_invocation_parameters['dryrun'] = self.__dryrun( _invocation_parameters ) if dryrun is None else dryrun
_invocation_parameters['acceptresults'] = self.__acceptresults( _invocation_parameters ) if acceptresults is None else acceptresults
else:
# invoke with inp/go semantics
_invocation_parameters['vis'] = self.__vis( self.__globals_( ) )
_invocation_parameters['outputvis'] = self.__outputvis( self.__globals_( ) )
_invocation_parameters['field'] = self.__field( self.__globals_( ) )
_invocation_parameters['intent'] = self.__intent( self.__globals_( ) )
_invocation_parameters['spw'] = self.__spw( self.__globals_( ) )
_invocation_parameters['chanbin'] = self.__chanbin( self.__globals_( ) )
_invocation_parameters['timebin'] = self.__timebin( self.__globals_( ) )
_invocation_parameters['pipelinemode'] = self.__pipelinemode( self.__globals_( ) )
_invocation_parameters['dryrun'] = self.__dryrun( self.__globals_( ) )
_invocation_parameters['acceptresults'] = self.__acceptresults( self.__globals_( ) )
try:
with open(_prefile,'w') as _f:
for _i in _invocation_parameters:
_f.write("%-13s = %s\n" % (_i,noobj(repr(_invocation_parameters[_i]))))
_f.write("#hif_mstransform( ")
count = 0
for _i in _invocation_parameters:
_f.write("%s=%s" % (_i,noobj(repr(_invocation_parameters[_i]))))
count += 1
if count < len(_invocation_parameters): _f.write(",")
_f.write(" )\n")
except: pass
try:
_return_result_ = _hif_mstransform_t( _invocation_parameters['vis'],_invocation_parameters['outputvis'],_invocation_parameters['field'],_invocation_parameters['intent'],_invocation_parameters['spw'],_invocation_parameters['chanbin'],_invocation_parameters['timebin'],_invocation_parameters['pipelinemode'],_invocation_parameters['dryrun'],_invocation_parameters['acceptresults'] )
except Exception as e:
from traceback import format_exc
from casatasks import casalog
casalog.origin('hif_mstransform')
casalog.post("Exception Reported: Error in hif_mstransform: %s" % str(e),'SEVERE')
casalog.post(format_exc( ))
_return_result_ = False
try:
os.rename(_prefile,_postfile)
except: pass
return _return_result_
hif_mstransform = _hif_mstransform( )