##################### generated by xml-casa (v2) from hif_transformimagedata.xml ####
##################### 4223a2feef5b7b814e4076af9eea922a ##############################
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_transformimagedata as _hif_transformimagedata_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_transformimagedata:
"""
hif_transformimagedata ---- Base transformimagedata task
The hif_transformimagedata task.
Output:
results -- If pipeline mode is 'getinputs' then None is returned. Otherwise
the results object for the pipeline task is returned.
--------- parameter descriptions ---------------------------------------------
vis List of visibility data files. These may be ASDMs, tar files of ASDMs,
MSs, or tar files of MSs, If ASDM files are specified, they will be
converted to MS format.
example: vis=['X227.ms', 'asdms.tar.gz']
outputvis The output MeasurementSet.
field Set of data selection field names or ids, \'\' for all.
intent Set of data selection intents, \'\' for all.
spw Set of data selection spectral window ids \'\' for all.
datacolumn Select spectral windows to split. The standard CASA options are
supported
example: 'data', 'model'
chanbin
timebin Bin width for time averaging.
replace If a split was performed delete the parent MS and remove it from the context.
example: True or False
clear_pointing Clear the pointing table.
modify_weights Re-initialize the weights.
wtmode optional weight initialization mode when modify_weights=True
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.
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).
--------- examples -----------------------------------------------------------
1. Basic transformimagedata task
hif_transformimagedata()
"""
_info_group_ = """pipeline"""
_info_desc_ = """Base transformimagedata task"""
__schema = {'vis': {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}, 'outputvis': {'type': 'cStr', 'coerce': _coerce.to_str}, 'field': {'type': 'cStr', 'coerce': _coerce.to_str}, 'intent': {'type': 'cStr', 'coerce': _coerce.to_str}, 'spw': {'type': 'cStr', 'coerce': _coerce.to_str}, 'datacolumn': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'DATA', 'model', 'corrected', 'LAG_DATA', 'lag_data', 'FLOAT_DATA,DATA', 'FLOAT_DATA', 'CORRECTED', 'lag_data,data', 'float_data', 'float_data,data', 'DATA,MODEL,CORRECTED', 'ALL', 'MODEL', 'all', 'data,model,corrected', 'LAG_DATA,DATA', 'data' ]}, 'chanbin': {'type': 'cInt', 'allowed': [ 1, 2, 4, 8, 16 ]}, 'timebin': {'type': 'cStr', 'coerce': _coerce.to_str}, 'replace': {'type': 'cBool'}, 'clear_pointing': {'type': 'cBool'}, 'modify_weights': {'type': 'cBool'}, 'wtmode': {'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 __replace_dflt( self, glb ):
return False
def __replace( self, glb ):
if 'replace' in glb: return glb['replace']
return False
def __clear_pointing_dflt( self, glb ):
return True
def __clear_pointing( self, glb ):
if 'clear_pointing' in glb: return glb['clear_pointing']
return True
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)
def __modify_weights_dflt( self, glb ):
return False
def __modify_weights( self, glb ):
if 'modify_weights' in glb: return glb['modify_weights']
return False
#--------- 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 __datacolumn_dflt( self, glb ):
if self.__pipelinemode( glb ) == "interactive": return "corrected"
if self.__pipelinemode( glb ) == "getinputs": return "corrected"
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 __wtmode_dflt( self, glb ):
if self.__modify_weights( glb ) == bool(True): return ""
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 __datacolumn( self, glb ):
if 'datacolumn' in glb: return glb['datacolumn']
dflt = self.__datacolumn_dflt( glb )
if dflt is not None: return dflt
return 'corrected'
def __wtmode( self, glb ):
if 'wtmode' in glb: return glb['wtmode']
dflt = self.__wtmode_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 output MeasurementSet'
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, \'\' for all'
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 __datacolumn_inp(self):
if self.__datacolumn_dflt( self.__globals_( ) ) is not None:
description = 'The data columns to process'
value = self.__datacolumn( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'datacolumn': value},{'datacolumn': self.__schema['datacolumn']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('datacolumn',pre,self.__to_string_(value),post),description,9+len(pre)+len(post))
def __chanbin_inp(self):
description = 'Channel bin width for spectral averaging'
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 __replace_inp(self):
description = 'Remove the parent MS and replace with the split MS'
value = self.__replace( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'replace': value},{'replace': self.__schema['replace']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output('%-16.16s = %s%-23s%s' % ('replace',pre,self.__to_string_(value),post),description,0+len(pre)+len(post))
def __clear_pointing_inp(self):
description = 'Clear the pointing table'
value = self.__clear_pointing( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'clear_pointing': value},{'clear_pointing': self.__schema['clear_pointing']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output('%-16.16s = %s%-23s%s' % ('clear_pointing',pre,self.__to_string_(value),post),description,0+len(pre)+len(post))
def __modify_weights_inp(self):
description = 'Re-initialize the weights'
value = self.__modify_weights( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'modify_weights': value},{'modify_weights': self.__schema['modify_weights']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output('\x1B[1m\x1B[47m%-16.16s =\x1B[0m %s%-23s%s' % ('modify_weights',pre,self.__to_string_(value),post),description,13+len(pre)+len(post))
def __wtmode_inp(self):
if self.__wtmode_dflt( self.__globals_( ) ) is not None:
description = 'Weight initialization mode'
value = self.__wtmode( self.__globals_( ) )
(pre,post) = ('','') if self.__validate_({'wtmode': value},{'wtmode': self.__schema['wtmode']}) else ('\x1B[91m','\x1B[0m')
self.__do_inp_output(' \x1B[92m%-13.13s =\x1B[0m %s%-23s%s' % ('wtmode',pre,self.__to_string_(value),post),description,9+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 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 'replace' in glb: del glb['replace']
if 'field' in glb: del glb['field']
if 'modify_weights' in glb: del glb['modify_weights']
if 'pipelinemode' in glb: del glb['pipelinemode']
if 'outputvis' in glb: del glb['outputvis']
if 'datacolumn' in glb: del glb['datacolumn']
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 'wtmode' in glb: del glb['wtmode']
if 'clear_pointing' in glb: del glb['clear_pointing']
if 'spw' in glb: del glb['spw']
#--------- inp function -----------------------------------------------------------
def inp(self):
print("# hif_transformimagedata -- %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.__datacolumn_inp( )
self.__chanbin_inp( )
self.__timebin_inp( )
self.__replace_inp( )
self.__clear_pointing_inp( )
self.__modify_weights_inp( )
self.__wtmode_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_transformimagedata.last"):
filename = "hif_transformimagedata.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, datacolumn=None, chanbin=None, timebin=None, replace=None, clear_pointing=None, modify_weights=None, wtmode=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_transformimagedata.pre')
_postfile = os.path.realpath('hif_transformimagedata.last')
_return_result_ = None
_arguments = [vis,outputvis,field,intent,spw,datacolumn,chanbin,timebin,replace,clear_pointing,modify_weights,wtmode,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 replace is not None: local_global['replace'] = replace
if clear_pointing is not None: local_global['clear_pointing'] = clear_pointing
if modify_weights is not None: local_global['modify_weights'] = modify_weights
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['replace'] = self.__replace( local_global )
_invocation_parameters['clear_pointing'] = self.__clear_pointing( local_global )
_invocation_parameters['modify_weights'] = self.__modify_weights( 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['datacolumn'] = self.__datacolumn( _invocation_parameters ) if datacolumn is None else datacolumn
_invocation_parameters['wtmode'] = self.__wtmode( _invocation_parameters ) if wtmode is None else wtmode
_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['datacolumn'] = self.__datacolumn( self.__globals_( ) )
_invocation_parameters['chanbin'] = self.__chanbin( self.__globals_( ) )
_invocation_parameters['timebin'] = self.__timebin( self.__globals_( ) )
_invocation_parameters['replace'] = self.__replace( self.__globals_( ) )
_invocation_parameters['clear_pointing'] = self.__clear_pointing( self.__globals_( ) )
_invocation_parameters['modify_weights'] = self.__modify_weights( self.__globals_( ) )
_invocation_parameters['wtmode'] = self.__wtmode( 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("%-14s = %s\n" % (_i,noobj(repr(_invocation_parameters[_i]))))
_f.write("#hif_transformimagedata( ")
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_transformimagedata_t( _invocation_parameters['vis'],_invocation_parameters['outputvis'],_invocation_parameters['field'],_invocation_parameters['intent'],_invocation_parameters['spw'],_invocation_parameters['datacolumn'],_invocation_parameters['chanbin'],_invocation_parameters['timebin'],_invocation_parameters['replace'],_invocation_parameters['clear_pointing'],_invocation_parameters['modify_weights'],_invocation_parameters['wtmode'],_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_transformimagedata')
casalog.post("Exception Reported: Error in hif_transformimagedata: %s" % str(e),'SEVERE')
casalog.post(format_exc( ))
_return_result_ = False
try:
os.rename(_prefile,_postfile)
except: pass
return _return_result_
hif_transformimagedata = _hif_transformimagedata( )