def __call__(
self,
vis=None,
outputvis=None,
timerange=None,
spw=None,
subtime1=None,
subtime2=None,
splitsel=None,
overwrite=None,
):
"""Vector-subtraction in UV using selected time ranges and spectral channels as background
Detailed Description:
Split is the general purpose program to make a new data set that is a
subset or averaged form of an existing data set. General selection
parameters are included, and one or all of the various data columns
(DATA, LAG_DATA and/or FLOAT_DATA, and possibly MODEL_DATA and/or
CORRECTED_DATA) can be selected.
Split is often used after the initial calibration of the data to make a
smaller measurement set with only the data that will be used in
further flagging, imaging and/or self-calibration. split can
average over frequency (channels) and time (integrations).
Arguments :
vis: Name of input measurement set
Default Value:
outputvis: Name of output measurement set
Default Value:
timerange: Select the time range of the input visbility to be subtracted from
Default Value:
spw: Select the spectral channels of the input visibility to be subtracted from
Default Value:
subtime1: Select time range 1 as the background to be subtracted
Default Value:
subtime2: Select time range 2 as the background to be subtracted
Default Value:
splitsel: Split the selected timerange and spectral channels as outputvis
Default Value: True
overwrite: Overwrite the already existing output measurement set
Default Value: False
Example :
Subvs is a task to do UV vector-subtraction, by selecting time ranges
in the data as background. Subvs can be used to subtract the background
continuum emission to separate the time-dependent emission, e.g. solar
coherent radio bursts.
Keyword arguments:
vis -- Name of input visibility file
default: none; example: vis='sun_type3.ms'
outputvis -- Name of output visibility file
default: none; example: outputvis='sun_type3.sub.ms'
timerange -- Select the time range in the data to be subtracted from.
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
subtime1 -- Select the time range 1 of data as the background.
Visibilities will be vector-averaged in time1 before subtraction.
default = '' (will raise an exception); examples,
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
subtime2 -- Select the time range 2 of data as the background.
Visibilities will be vector-averaged in time2 before subtraction.
if specified, then linear-interpolated values based on time1 and
time2 will be applied to the times specified by "subtime" for
subtraction.
if not specified, then only "time1" is used as the background
default = '' (none); examples,
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
splitsel -- True of False. default = False. If splitsel = False, then the entire input
measurement set is copied as the output measurement set (outputvis), with
background subtracted at selected timerange and spectral channels.
If splitsel = True,then only the selected timerange and spectral channels
are copied into the output measurement set (outputvis).
overwrite -- True or False. default = False. If overwrite = True and outputvis
already exists, the selected subtime and spw in the already existing
output measurement set will be replaced with subtracted visibilities
"""
if not hasattr(self, "__globals__") or self.__globals__ == None:
self.__globals__ = sys._getframe(len(inspect.stack()) -
1).f_globals
#casac = self.__globals__['casac']
casalog = self.__globals__['casalog']
casa = self.__globals__['casa']
#casalog = casac.casac.logsink()
self.__globals__['__last_task'] = 'subvs'
self.__globals__['taskname'] = 'subvs'
###
self.__globals__['update_params'](func=self.__globals__['taskname'],
printtext=False,
ipython_globals=self.__globals__)
###
###
#Handle globals or user over-ride of arguments
#
if type(self.__call__.func_defaults) is NoneType:
function_signature_defaults = {}
else:
function_signature_defaults = dict(
zip(self.__call__.func_code.co_varnames[1:],
self.__call__.func_defaults))
useLocalDefaults = False
for item in function_signature_defaults.iteritems():
key, val = item
keyVal = eval(key)
if (keyVal == None):
#user hasn't set it - use global/default
pass
else:
#user has set it - use over-ride
if (key != 'self'):
useLocalDefaults = True
myparams = {}
if useLocalDefaults:
for item in function_signature_defaults.iteritems():
key, val = item
keyVal = eval(key)
exec('myparams[key] = keyVal')
self.parameters[key] = keyVal
if (keyVal == None):
exec('myparams[key] = ' + key + ' = self.itsdefault(key)')
keyVal = eval(key)
if (type(keyVal) == dict):
if len(keyVal) > 0:
exec('myparams[key] = ' + key +
' = keyVal[len(keyVal)-1][\'value\']')
else:
exec('myparams[key] = ' + key + ' = {}')
else:
print ''
myparams['vis'] = vis = self.parameters['vis']
myparams['outputvis'] = outputvis = self.parameters['outputvis']
myparams['timerange'] = timerange = self.parameters['timerange']
myparams['spw'] = spw = self.parameters['spw']
myparams['subtime1'] = subtime1 = self.parameters['subtime1']
myparams['subtime2'] = subtime2 = self.parameters['subtime2']
myparams['splitsel'] = splitsel = self.parameters['splitsel']
myparams['overwrite'] = overwrite = self.parameters['overwrite']
result = None
#
# The following is work around to avoid a bug with current python translation
#
mytmp = {}
mytmp['vis'] = vis
mytmp['outputvis'] = outputvis
mytmp['timerange'] = timerange
mytmp['spw'] = spw
mytmp['subtime1'] = subtime1
mytmp['subtime2'] = subtime2
mytmp['splitsel'] = splitsel
mytmp['overwrite'] = overwrite
pathname = "file:///Users/binchen/Dropbox/bc_python/casa_task/"
trec = casac.casac.utils().torecord(pathname + 'subvs.xml')
casalog.origin('subvs')
try:
#if not trec.has_key('subvs') or not casac.casac.utils().verify(mytmp, trec['subvs']) :
#return False
casac.casac.utils().verify(mytmp, trec['subvs'], True)
scriptstr = ['']
saveinputs = self.__globals__['saveinputs']
if type(self.__call__.func_defaults) is NoneType:
saveinputs = ''
else:
saveinputs('subvs',
'subvs.last',
myparams,
self.__globals__,
scriptstr=scriptstr)
tname = 'subvs'
spaces = ' ' * (18 - len(tname))
casalog.post('\n##########################################' +
'\n##### Begin Task: ' + tname + spaces + ' #####')
if type(self.__call__.func_defaults) is NoneType:
casalog.post(scriptstr[0] + '\n', 'INFO')
else:
casalog.post(scriptstr[1][1:] + '\n', 'INFO')
result = subvs(vis, outputvis, timerange, spw, subtime1, subtime2,
splitsel, overwrite)
casalog.post('##### End Task: ' + tname + ' ' + spaces +
' #####' +
'\n##########################################')
except Exception, instance:
if (self.__globals__.has_key('__rethrow_casa_exceptions')
and self.__globals__['__rethrow_casa_exceptions']):
raise
else:
#print '**** Error **** ',instance
tname = 'subvs'
casalog.post('An error occurred running task ' + tname + '.',
'ERROR')
pass
def __call__(
self,
vis=None,
outputvis=None,
timerange=None,
spw=None,
mode=None,
subtime1=None,
subtime2=None,
smoothaxis=None,
smoothtype=None,
smoothwidth=None,
splitsel=None,
reverse=None,
overwrite=None,
):
"""Vector-subtraction in UV using selected time ranges and spectral channels as background
Detailed Description:
Split is the general purpose program to make a new data set that is a
subset or averaged form of an existing data set. General selection
parameters are included, and one or all of the various data columns
(DATA, LAG_DATA and/or FLOAT_DATA, and possibly MODEL_DATA and/or
CORRECTED_DATA) can be selected.
Split is often used after the initial calibration of the data to make a
smaller measurement set with only the data that will be used in
further flagging, imaging and/or self-calibration. split can
average over frequency (channels) and time (integrations).
Arguments :
vis: Name of input measurement set
Default Value:
outputvis: Name of output measurement set
Default Value:
timerange: Select the time range of the input visbility to be subtracted from
Default Value:
spw: Select the spectral channels of the input visibility to be subtracted from
Default Value:
mode: Operation: linear, highpass
Default Value: linear
Allowed Values:
linear
lowpass
highpass
subtime1: Select the first time range as the background for uv subtraction
Default Value:
subtime2: Select the second time range as the background for uv subtraction
Default Value:
smoothaxis: Select the axis along which smooth is performed
Default Value: time
smoothtype: Select the smooth type
Default Value: flat
smoothwidth: Select the width of the smoothing window
Default Value: 5
splitsel: Split the selected timerange and spectral channels as outputvis
Default Value: True
reverse: Reverse the sign of the background-subtracted data (for absorptive structure)
Default Value: False
overwrite: Overwrite the already existing output measurement set
Default Value: False
Example :
Subvs is a task to do UV vector-subtraction, by selecting time ranges
in the data as background. Subvs can be used to subtract the background
continuum emission to separate the time-dependent emission, e.g. solar
coherent radio bursts.
Keyword arguments:
vis -- Name of input visibility file (MS)
default: none; example: vis='ngc5921.ms'
outputvis -- Name of output uv-subtracted visibility file (MS)
default: none; example: outputvis='ngc5921_src.ms'
timerange -- Time range of performing the UV subtraction:
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
mode -- operation mode
default 'linear'
mode = 'linear': use a linear fit for the background to be subtracted
mode = 'lowpass': act as a lowpass filter---smooth the data using different smooth
types and smooth window size. Can be performed along either time
or frequency axis
mode = 'highpass': act as a highpass filter---smooth the data first, and
subtract the smoothed data from the original. Can be performed along either time
or frequency axis
mode = 'linear' expandable parameters:
subtime1 -- Time range 1 of the background to be subtracted from the data
default='' means all times. format:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
subtime2 -- Time range 2 of the backgroud to be subtracted from the data
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
mode = 'lowpass' or 'highpass' expandable parameters:
smoothaxis -- axis of smooth
Default: 'time'
smoothaxis = 'time': smooth is along the time axis
smoothaxis = 'freq': smooth is along the frequency axis
smoothtype -- type of the smooth depending on the convolving kernel
Default: 'flat'
smoothtype = 'flat': convolving kernel is a flat rectangle,
equivalent to a boxcar moving smooth
smoothtype = 'hanning': Hanning smooth kernel. See numpy.hanning
smoothtype = 'hamming': Hamming smooth kernel. See numpy.hamming
smoothtype = 'bartlett': Bartlett smooth kernel. See numpy.bartlett
smoothtype = 'blackman': Blackman smooth kernel. See numpy.blackman
smoothwidth -- width of the smooth kernel
Default: 5
Examples: smoothwidth=5, meaning the width is 5 pixels
splitsel -- True or False. default = False. If splitsel = False, then the entire input
measurement set is copied as the output measurement set (outputvis), with
background subtracted at selected timerange and spectral channels.
If splitsel = True,then only the selected timerange and spectral channels
are copied into the output measurement set (outputvis).
reverse -- True or False. default = False. If reverse = False, then the times indicated
by subtime1 and/or subtime2 are treated as background and subtracted; If reverse
= True, then reverse the sign of the background-subtracted data. The option can
be used for mapping absorptive structure.
overwrite -- True or False. default = False. If overwrite = True and
outputvis already exists, the selected subtime and spw in the
output measurment set will be replaced with background subtracted
visibilities
"""
if not hasattr(self, "__globals__") or self.__globals__ == None:
self.__globals__ = sys._getframe(len(inspect.stack()) -
1).f_globals
#casac = self.__globals__['casac']
casalog = self.__globals__['casalog']
casa = self.__globals__['casa']
#casalog = casac.casac.logsink()
self.__globals__['__last_task'] = 'subvs'
self.__globals__['taskname'] = 'subvs'
###
self.__globals__['update_params'](func=self.__globals__['taskname'],
printtext=False,
ipython_globals=self.__globals__)
###
###
#Handle globals or user over-ride of arguments
#
if type(self.__call__.func_defaults) is NoneType:
function_signature_defaults = {}
else:
function_signature_defaults = dict(
zip(self.__call__.func_code.co_varnames[1:],
self.__call__.func_defaults))
useLocalDefaults = False
for item in function_signature_defaults.iteritems():
key, val = item
keyVal = eval(key)
if (keyVal == None):
#user hasn't set it - use global/default
pass
else:
#user has set it - use over-ride
if (key != 'self'):
useLocalDefaults = True
myparams = {}
if useLocalDefaults:
for item in function_signature_defaults.iteritems():
key, val = item
keyVal = eval(key)
exec('myparams[key] = keyVal')
self.parameters[key] = keyVal
if (keyVal == None):
exec('myparams[key] = ' + key + ' = self.itsdefault(key)')
keyVal = eval(key)
if (type(keyVal) == dict):
if len(keyVal) > 0:
exec('myparams[key] = ' + key +
' = keyVal[len(keyVal)-1][\'value\']')
else:
exec('myparams[key] = ' + key + ' = {}')
else:
print ''
myparams['vis'] = vis = self.parameters['vis']
myparams['outputvis'] = outputvis = self.parameters['outputvis']
myparams['timerange'] = timerange = self.parameters['timerange']
myparams['spw'] = spw = self.parameters['spw']
myparams['mode'] = mode = self.parameters['mode']
myparams['subtime1'] = subtime1 = self.parameters['subtime1']
myparams['subtime2'] = subtime2 = self.parameters['subtime2']
myparams['smoothaxis'] = smoothaxis = self.parameters['smoothaxis']
myparams['smoothtype'] = smoothtype = self.parameters['smoothtype']
myparams['smoothwidth'] = smoothwidth = self.parameters[
'smoothwidth']
myparams['splitsel'] = splitsel = self.parameters['splitsel']
myparams['reverse'] = reverse = self.parameters['reverse']
myparams['overwrite'] = overwrite = self.parameters['overwrite']
result = None
#
# The following is work around to avoid a bug with current python translation
#
mytmp = {}
mytmp['vis'] = vis
mytmp['outputvis'] = outputvis
mytmp['timerange'] = timerange
mytmp['spw'] = spw
mytmp['mode'] = mode
mytmp['subtime1'] = subtime1
mytmp['subtime2'] = subtime2
mytmp['smoothaxis'] = smoothaxis
mytmp['smoothtype'] = smoothtype
mytmp['smoothwidth'] = smoothwidth
mytmp['splitsel'] = splitsel
mytmp['reverse'] = reverse
mytmp['overwrite'] = overwrite
pathname = "file:///Users/binchen/Dropbox/bc_python/casa_task/"
trec = casac.casac.utils().torecord(pathname + 'subvs.xml')
casalog.origin('subvs')
try:
#if not trec.has_key('subvs') or not casac.casac.utils().verify(mytmp, trec['subvs']) :
#return False
casac.casac.utils().verify(mytmp, trec['subvs'], True)
scriptstr = ['']
saveinputs = self.__globals__['saveinputs']
if type(self.__call__.func_defaults) is NoneType:
saveinputs = ''
else:
saveinputs('subvs',
'subvs.last',
myparams,
self.__globals__,
scriptstr=scriptstr)
tname = 'subvs'
spaces = ' ' * (18 - len(tname))
casalog.post('\n##########################################' +
'\n##### Begin Task: ' + tname + spaces + ' #####')
if type(self.__call__.func_defaults) is NoneType:
casalog.post(scriptstr[0] + '\n', 'INFO')
else:
casalog.post(scriptstr[1][1:] + '\n', 'INFO')
result = subvs(vis, outputvis, timerange, spw, mode, subtime1,
subtime2, smoothaxis, smoothtype, smoothwidth,
splitsel, reverse, overwrite)
casalog.post('##### End Task: ' + tname + ' ' + spaces +
' #####' +
'\n##########################################')
except Exception, instance:
if (self.__globals__.has_key('__rethrow_casa_exceptions')
and self.__globals__['__rethrow_casa_exceptions']):
raise
else:
#print '**** Error **** ',instance
tname = 'subvs'
casalog.post('An error occurred running task ' + tname + '.',
'ERROR')
pass
def subvs(vis='',
outputvis='',
timerange='',
spw='',
mode='linear',
subtime1='',
subtime2='',
smoothaxis='time',
smoothtype='flat',
smoothwidth=5,
splitsel=True,
reverse=False,
overwrite=False):
"""Vector-subtraction in UV using selected time ranges and spectral channels as background
Subvs is a task to do UV vector-subtraction, by selecting time ranges
in the data as background. Subvs can be used to subtract the background
continuum emission to separate the time-dependent emission, e.g. solar
coherent radio bursts.
Keyword arguments:
vis -- Name of input visibility file (MS)
default: none; example: vis='ngc5921.ms'
outputvis -- Name of output uv-subtracted visibility file (MS)
default: none; example: outputvis='ngc5921_src.ms'
timerange -- Time range of performing the UV subtraction:
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
mode -- operation mode
default 'linear'
mode = 'linear': use a linear fit for the background to be subtracted
mode = 'lowpass': act as a lowpass filter---smooth the data using different smooth
types and smooth window size. Can be performed along either time
or frequency axis
mode = 'highpass': act as a highpass filter---smooth the data first, and
subtract the smoothed data from the original. Can be performed along either time
or frequency axis
mode = 'linear' expandable parameters:
subtime1 -- Time range 1 of the background to be subtracted from the data
default='' means all times. format:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
subtime2 -- Time range 2 of the backgroud to be subtracted from the data
default='' means all times. examples:
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
timerange = 'hh:mm:ss~hh:mm:ss'
mode = 'lowpass' or 'highpass' expandable parameters:
smoothaxis -- axis of smooth
Default: 'time'
smoothaxis = 'time': smooth is along the time axis
smoothaxis = 'freq': smooth is along the frequency axis
smoothtype -- type of the smooth depending on the convolving kernel
Default: 'flat'
smoothtype = 'flat': convolving kernel is a flat rectangle,
equivalent to a boxcar moving smooth
smoothtype = 'hanning': Hanning smooth kernel. See numpy.hanning
smoothtype = 'hamming': Hamming smooth kernel. See numpy.hamming
smoothtype = 'bartlett': Bartlett smooth kernel. See numpy.bartlett
smoothtype = 'blackman': Blackman smooth kernel. See numpy.blackman
smoothwidth -- width of the smooth kernel
Default: 5
Examples: smoothwidth=5, meaning the width is 5 pixels
splitsel -- True or False. default = False. If splitsel = False, then the entire input
measurement set is copied as the output measurement set (outputvis), with
background subtracted at selected timerange and spectral channels.
If splitsel = True,then only the selected timerange and spectral channels
are copied into the output measurement set (outputvis).
reverse -- True or False. default = False. If reverse = False, then the times indicated
by subtime1 and/or subtime2 are treated as background and subtracted; If reverse
= True, then reverse the sign of the background-subtracted data. The option can
be used for mapping absorptive structure.
overwrite -- True or False. default = False. If overwrite = True and
outputvis already exists, the selected subtime and spw in the
output measurment set will be replaced with background subtracted
visibilities
"""
#
# The following is work around to avoid a bug with current python translation
#
mytmp = {}
mytmp['vis'] = vis
mytmp['outputvis'] = outputvis
mytmp['timerange'] = timerange
mytmp['spw'] = spw
mytmp['mode'] = mode
mytmp['subtime1'] = subtime1
mytmp['subtime2'] = subtime2
mytmp['smoothaxis'] = smoothaxis
mytmp['smoothtype'] = smoothtype
mytmp['smoothwidth'] = smoothwidth
mytmp['splitsel'] = splitsel
mytmp['reverse'] = reverse
mytmp['overwrite'] = overwrite
pathname = "file:///Users/fisher/Dropbox/PycharmProjects/suncasa/tasks/"
trec = casac.utils().torecord(pathname + 'subvs.xml')
casalog.origin('subvs')
if trec.has_key('subvs') and casac.utils().verify(mytmp, trec['subvs']):
result = task_subvs.subvs(vis, outputvis, timerange, spw, mode,
subtime1, subtime2, smoothaxis, smoothtype,
smoothwidth, splitsel, reverse, overwrite)
else:
result = False
return result
def subvs(vis='', outputvis='', timerange='', spw='', subtime1='', subtime2='', splitsel=True, reverse=False, overwrite=False):
"""Vector-subtraction in UV using selected time ranges and spectral channels as background
Subvs is a task to do UV vector-subtraction, by selecting time ranges
in the data as background. Subvs can be used to subtract the background
continuum emission to separate the time-dependent emission, e.g. solar
coherent radio bursts.
Keyword arguments:
vis -- Name of input visibility file
default: none; example: vis='sun_type3.ms'
outputvis -- Name of output visibility file
default: none; example: outputvis='sun_type3.sub.ms'
timerange -- Select the time range in the data to be subtracted from.
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
spw -- Select spectral window/channel.
default = '' all the spectral channels. Example: spw='0:1~20'
subtime1 -- Select the time range 1 of data as the background.
Visibilities will be vector-averaged in time1 before subtraction.
default = '' (will raise an exception); examples,
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
subtime2 -- Select the time range 2 of data as the background.
Visibilities will be vector-averaged in time2 before subtraction.
if specified, then linear-interpolated values based on time1 and
time2 will be applied to the times specified by "subtime" for
subtraction.
if not specified, then only "time1" is used as the background
default = '' (none); examples,
timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
Note: if YYYY/MM/DD is missing date, timerange defaults to the
first day in the dataset
timerange='09:14:0~09:54:0' picks 40 min on first day
timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min
on next day
splitsel -- True of False. default = False. If splitsel = False, then the entire input
measurement set is copied as the output measurement set (outputvis), with
background subtracted at selected timerange and spectral channels.
If splitsel = True,then only the selected timerange and spectral channels
are copied into the output measurement set (outputvis).
reverse -- True or False. default = False. If reverse = False, then the times indicated
by subtime1 and/or subtime2 are treated as background and subtracted; If reverse
= True, then reverse the sign of the background-subtracted data. The option can
be used for mapping absorptive structure.
overwrite -- True or False. default = False. If overwrite = True and outputvis
already exists, the selected subtime and spw in the already existing
output measurement set will be replaced with subtracted visibilities
"""
#
# The following is work around to avoid a bug with current python translation
#
mytmp = {}
mytmp['vis'] = vis
mytmp['outputvis'] = outputvis
mytmp['timerange'] = timerange
mytmp['spw'] = spw
mytmp['subtime1'] = subtime1
mytmp['subtime2'] = subtime2
mytmp['splitsel'] = splitsel
mytmp['reverse'] = reverse
mytmp['overwrite'] = overwrite
pathname="file:///Users/binchen/Dropbox/bc_python/casa_task/"
trec = casac.utils().torecord(pathname+'subvs.xml')
casalog.origin('subvs')
if trec.has_key('subvs') and casac.utils().verify(mytmp, trec['subvs']) :
result = task_subvs.subvs(vis, outputvis, timerange, spw, subtime1, subtime2, splitsel, reverse, overwrite)
else :
result = False
return result