def getDefaultConfigObj(taskname, configObj, input_dict={}, loadOnly=True):
""" Return default configObj instance for task updated
with user-specified values from input_dict.
Parameters
----------
taskname : string
Name of task to load into TEAL
configObj : string
The valid values for 'configObj' would be::
None - loads last saved user .cfg file
'defaults' - loads task default .cfg file
name of .cfg file (string)- loads user-specified .cfg file
input_dict : dict
Set of parameters and values specified by user to be different from
what gets loaded in from the .cfg file for the task
loadOnly : bool
Setting 'loadOnly' to False causes the TEAL GUI to start allowing the
user to edit the values further and then run the task if desired.
"""
if configObj is None:
# Start by grabbing the default values without using the GUI
# This insures that all subsequent use of the configObj includes
# all parameters and their last saved values
configObj = teal.load(taskname)
elif isinstance(configObj, str):
if configObj.lower().strip() == 'defaults':
# Load task default .cfg file with all default values
configObj = teal.load(taskname, defaults=True)
# define default filename for configObj
configObj.filename = taskname.lower() + '.cfg'
else:
# Load user-specified .cfg file with its special default values
# we need to call 'fileutil.osfn()' to insure all environment
# variables specified by the user in the configObj filename are
# expanded to the full path
configObj = teal.load(fileutil.osfn(configObj))
# merge in the user values for this run
# this, though, does not save the results for use later
if input_dict not in [None, {}]: # and configObj not in [None, {}]:
# check to see whether any input parameters are unexpected.
# Any unexpected parameters provided on input should be reported and
# the code should stop
validateUserPars(configObj, input_dict)
# If everything looks good, merge user inputs with configObj and continue
cfgpars.mergeConfigObj(configObj, input_dict)
# Update the input .cfg file with the updated parameter values
#configObj.filename = os.path.join(cfgpars.getAppDir(),os.path.basename(configObj.filename))
#configObj.write()
if not loadOnly:
# We want to run the GUI AFTER merging in any parameters
# specified by the user on the command-line and provided in
# input_dict
configObj = teal.teal(configObj, loadOnly=False)
return configObj
def setCommonInput(configObj, createOutwcs=True):
"""
The common interface interpreter for MultiDrizzle tasks which not only runs
'process_input()' but 'createImageObject()' and 'defineOutput()' as well to
fully setup all inputs for use with the rest of the MultiDrizzle steps either
as stand-alone tasks or internally to MultiDrizzle itself.
Parameters
----------
configObj : object
configObj instance or simple dictionary of input parameters
imageObjectList : list of imageObject objects
list of imageObject instances, 1 for each input exposure
outwcs : object
imageObject instance defining the final output frame
Notes
-----
At a minimum, the configObj instance (dictionary) should contain:
configObj = {'input':None,'output':None }
If provided, the configObj should contain the values of all the multidrizzle parameters
as set by the user with TEAL. If no configObj is given, it will retrieve
the default values automatically. In either case, the values from the input_dict
will be merged in with the configObj before being used by the rest of the
code.
Examples
--------
You can set *createOutwcs=False* for the cases where you only want the
images processed and no output wcs information in necessary; as in:
>>> imageObjectList,outwcs = processInput.processCommonInput(configObj)
"""
# make sure 'updatewcs' is set to False when running from GUI or if missing
# from configObj:
if 'updatewcs' not in configObj:
configObj['updatewcs'] = False
if not createOutwcs or not configObj['coeffs']:
# we're probably just working on single images here
configObj['updatewcs'] = False
# maybe we can chunk this part up some more so that we can call just the
# parts we want
# Interpret input, read and convert and update input files, then return
# list of input filenames and derived output filename
asndict, ivmlist, output = process_input(
configObj['input'],
configObj['output'],
updatewcs=configObj['updatewcs'],
wcskey=configObj['wcskey'],
**configObj['STATE OF INPUT FILES'])
if not asndict:
return None, None
# convert the filenames from asndict into a list of full filenames
files = [fileutil.buildRootname(f) for f in asndict['order']]
original_files = asndict['original_file_names']
# interpret MDRIZTAB, if specified, and update configObj accordingly
# This can be done here because MDRIZTAB does not include values for
# input, output, or updatewcs.
if 'mdriztab' in configObj and configObj['mdriztab']:
print("Reading in MDRIZTAB parameters for {} files".format(len(files)))
mdriztab_dict = mdzhandler.getMdriztabParameters(files)
# Update configObj with values from mpars
cfgpars.mergeConfigObj(configObj, mdriztab_dict)
# Convert interpreted list of input files from process_input into a list
# of imageObject instances for use by the MultiDrizzle tasks.
instrpars = configObj['INSTRUMENT PARAMETERS']
# pass in 'proc_unit' to initialize unit conversions as necessary
instrpars['proc_unit'] = configObj['proc_unit']
undistort = True
if not configObj['coeffs']:
undistort = False
# determine whether parallel processing will be performed
use_parallel = False
if util.can_parallel:
# look to see whether steps which can be run using multiprocessing
# have been turned on
for stepnum in parallel_steps:
sname = util.getSectionName(configObj, stepnum[0])
if configObj[sname][stepnum[1]]:
use_parallel = True
break
# interpret all 'bits' related parameters and convert them to integers
configObj['resetbits'] = interpret_bit_flags(configObj['resetbits'])
step3name = util.getSectionName(configObj, 3)
configObj[step3name]['driz_sep_bits'] = interpret_bit_flags(
configObj[step3name]['driz_sep_bits'])
step4name = util.getSectionName(configObj, 4)
if len(files) > 5 and 'minmed' in configObj[step4name]['combine_type']:
msg = '“minmed” is highly recommended for three images, \n'+\
' and is good for four to six images, \n'+\
' but should be avoided for ten or more images.\n'
print(textutil.textbox(msg))
step7name = util.getSectionName(configObj, 7)
configObj[step7name]['final_bits'] = interpret_bit_flags(
configObj[step7name]['final_bits'])
# Verify any refimage parameters to be used
step3aname = util.getSectionName(configObj, '3a')
if not util.verifyRefimage(configObj[step3aname]['driz_sep_refimage']):
msg = 'No refimage with WCS found!\n '+\
' This could be caused by one of 2 problems:\n'+\
' * filename does not specify an extension with a valid WCS.\n'+\
' * can not find the file.\n'+\
'Please check the filename specified in the "refimage" parameter.'
print(textutil.textbox(msg))
return None, None
step7aname = util.getSectionName(configObj, '7a')
if not util.verifyRefimage(configObj[step7aname]['final_refimage']):
msg = 'No refimage with WCS found!\n '+\
' This could be caused by one of 2 problems:\n'+\
' * filename does not specify an extension with a valid WCS.\n'+\
' * can not find the file.\n'+\
'Please check the filename specified in the "refimage" parameter.'
print(textutil.textbox(msg))
return None, None
# Build imageObject list for all the valid, shift-updated input files
log.info('-Creating imageObject List as input for processing steps.')
if 'in_memory' in configObj:
virtual = configObj['in_memory']
else:
virtual = False
imageObjectList = createImageObjectList(files,
instrpars,
output=asndict['output'],
group=configObj['group'],
undistort=undistort,
inmemory=virtual)
# Add original file names as "hidden" attributes of imageObject
assert (len(original_files) == len(imageObjectList)
) #TODO: remove after extensive testing
for i in range(len(imageObjectList)):
imageObjectList[i]._original_file_name = original_files[i]
# apply context parameter
applyContextPar(imageObjectList, configObj['context'])
# reset DQ bits if requested by user
resetDQBits(imageObjectList, cr_bits_value=configObj['resetbits'])
# Add info about input IVM files at this point to the imageObjectList
addIVMInputs(imageObjectList, ivmlist)
if createOutwcs:
log.info('-Creating output WCS.')
# Build output WCS and update imageObjectList with output WCS info
outwcs = wcs_functions.make_outputwcs(imageObjectList,
output,
configObj=configObj,
perfect=True)
outwcs.final_wcs.printwcs()
else:
outwcs = None
try:
# Provide user with some information on resource usage for this run
# raises ValueError Exception in interactive mode and user quits
num_cores = configObj.get('num_cores') if use_parallel else 1
reportResourceUsage(imageObjectList, outwcs, num_cores)
except ValueError:
imageObjectList = None
return imageObjectList, outwcs
def setCommonInput(configObj, createOutwcs=True):
"""
The common interface interpreter for MultiDrizzle tasks which not only runs
'process_input()' but 'createImageObject()' and 'defineOutput()' as well to
fully setup all inputs for use with the rest of the MultiDrizzle steps either
as stand-alone tasks or internally to MultiDrizzle itself.
Parameters
----------
configObj : object
configObj instance or simple dictionary of input parameters
imageObjectList : list of imageObject objects
list of imageObject instances, 1 for each input exposure
outwcs : object
imageObject instance defining the final output frame
Notes
-----
At a minimum, the configObj instance (dictionary) should contain:
configObj = {'input':None,'output':None }
If provided, the configObj should contain the values of all the multidrizzle parameters
as set by the user with TEAL. If no configObj is given, it will retrieve
the default values automatically. In either case, the values from the input_dict
will be merged in with the configObj before being used by the rest of the
code.
Examples
--------
You can set *createOutwcs=False* for the cases where you only want the
images processed and no output wcs information in necessary; as in:
>>> imageObjectList,outwcs = processInput.processCommonInput(configObj)
"""
# make sure 'updatewcs' is set to False when running from GUI or if missing
# from configObj:
if 'updatewcs' not in configObj:
configObj['updatewcs'] = False
if not createOutwcs or not configObj['coeffs']:
# we're probably just working on single images here
configObj['updatewcs']=False
# maybe we can chunk this part up some more so that we can call just the
# parts we want
# Interpret input, read and convert and update input files, then return
# list of input filenames and derived output filename
asndict, ivmlist, output = process_input(
configObj['input'], configObj['output'],
updatewcs=configObj['updatewcs'], wcskey=configObj['wcskey'],
**configObj['STATE OF INPUT FILES'])
if not asndict:
return None, None
# convert the filenames from asndict into a list of full filenames
files = [fileutil.buildRootname(f) for f in asndict['order']]
original_files = asndict['original_file_names']
# interpret MDRIZTAB, if specified, and update configObj accordingly
# This can be done here because MDRIZTAB does not include values for
# input, output, or updatewcs.
if 'mdriztab' in configObj and configObj['mdriztab']:
print("Reading in MDRIZTAB parameters for {} files".format(len(files)))
mdriztab_dict = mdzhandler.getMdriztabParameters(files)
# Update configObj with values from mpars
cfgpars.mergeConfigObj(configObj, mdriztab_dict)
# Convert interpreted list of input files from process_input into a list
# of imageObject instances for use by the MultiDrizzle tasks.
instrpars = configObj['INSTRUMENT PARAMETERS']
# pass in 'proc_unit' to initialize unit conversions as necessary
instrpars['proc_unit'] = configObj['proc_unit']
undistort = True
if not configObj['coeffs']:
undistort = False
# determine whether parallel processing will be performed
use_parallel = False
if util.can_parallel:
# look to see whether steps which can be run using multiprocessing
# have been turned on
for stepnum in parallel_steps:
sname = util.getSectionName(configObj,stepnum[0])
if configObj[sname][stepnum[1]]:
use_parallel = True
break
# interpret all 'bits' related parameters and convert them to integers
configObj['resetbits'] = interpret_bit_flags(configObj['resetbits'])
step3name = util.getSectionName(configObj,3)
configObj[step3name]['driz_sep_bits'] = interpret_bit_flags(
configObj[step3name]['driz_sep_bits']
)
step7name = util.getSectionName(configObj,7)
configObj[step7name]['final_bits'] = interpret_bit_flags(
configObj[step7name]['final_bits']
)
# Verify any refimage parameters to be used
step3aname = util.getSectionName(configObj,'3a')
if not util.verifyRefimage(configObj[step3aname]['driz_sep_refimage']):
msg = 'No refimage with WCS found!\n '+\
' This could be caused by one of 2 problems:\n'+\
' * filename does not specify an extension with a valid WCS.\n'+\
' * can not find the file.\n'+\
'Please check the filename specified in the "refimage" parameter.'
print(textutil.textbox(msg))
return None,None
step7aname = util.getSectionName(configObj,'7a')
if not util.verifyRefimage(configObj[step7aname]['final_refimage']):
msg = 'No refimage with WCS found!\n '+\
' This could be caused by one of 2 problems:\n'+\
' * filename does not specify an extension with a valid WCS.\n'+\
' * can not find the file.\n'+\
'Please check the filename specified in the "refimage" parameter.'
print(textutil.textbox(msg))
return None,None
# Build imageObject list for all the valid, shift-updated input files
log.info('-Creating imageObject List as input for processing steps.')
if 'in_memory' in configObj:
virtual = configObj['in_memory']
else:
virtual = False
imageObjectList = createImageObjectList(files, instrpars,
group=configObj['group'],
undistort=undistort,
inmemory=virtual)
# Add original file names as "hidden" attributes of imageObject
assert(len(original_files) == len(imageObjectList)) #TODO: remove after extensive testing
for i in range(len(imageObjectList)):
imageObjectList[i]._original_file_name = original_files[i]
# apply context parameter
applyContextPar(imageObjectList, configObj['context'])
# reset DQ bits if requested by user
resetDQBits(imageObjectList, cr_bits_value=configObj['resetbits'])
# Add info about input IVM files at this point to the imageObjectList
addIVMInputs(imageObjectList, ivmlist)
if createOutwcs:
log.info('-Creating output WCS.')
# Build output WCS and update imageObjectList with output WCS info
outwcs = wcs_functions.make_outputwcs(imageObjectList, output,
configObj=configObj, perfect=True)
outwcs.final_wcs.printwcs()
else:
outwcs = None
try:
# Provide user with some information on resource usage for this run
# raises ValueError Exception in interactive mode and user quits
num_cores = configObj.get('num_cores') if use_parallel else 1
reportResourceUsage(imageObjectList, outwcs, num_cores)
except ValueError:
imageObjectList = None
return imageObjectList, outwcs
def getDefaultConfigObj(taskname,configObj,input_dict={},loadOnly=True):
""" Return default configObj instance for task updated
with user-specified values from input_dict.
Parameters
----------
taskname : string
Name of task to load into TEAL
configObj : string
The valid values for 'configObj' would be::
None - loads last saved user .cfg file
'defaults' - loads task default .cfg file
name of .cfg file (string)- loads user-specified .cfg file
input_dict : dict
Set of parameters and values specified by user to be different from
what gets loaded in from the .cfg file for the task
loadOnly : bool
Setting 'loadOnly' to False causes the TEAL GUI to start allowing the
user to edit the values further and then run the task if desired.
"""
if configObj is None:
# Start by grabbing the default values without using the GUI
# This insures that all subsequent use of the configObj includes
# all parameters and their last saved values
configObj = teal.load(taskname)
elif isinstance(configObj,str):
if configObj.lower().strip() == 'defaults':
# Load task default .cfg file with all default values
configObj = teal.load(taskname,defaults=True)
# define default filename for configObj
configObj.filename = taskname.lower()+'.cfg'
else:
# Load user-specified .cfg file with its special default values
# we need to call 'fileutil.osfn()' to insure all environment
# variables specified by the user in the configObj filename are
# expanded to the full path
configObj = teal.load(fileutil.osfn(configObj))
# merge in the user values for this run
# this, though, does not save the results for use later
if input_dict not in [None,{}]:# and configObj not in [None, {}]:
# check to see whether any input parameters are unexpected.
# Any unexpected parameters provided on input should be reported and
# the code should stop
validateUserPars(configObj,input_dict)
# If everything looks good, merge user inputs with configObj and continue
cfgpars.mergeConfigObj(configObj, input_dict)
# Update the input .cfg file with the updated parameter values
#configObj.filename = os.path.join(cfgpars.getAppDir(),os.path.basename(configObj.filename))
#configObj.write()
if not loadOnly:
# We want to run the GUI AFTER merging in any parameters
# specified by the user on the command-line and provided in
# input_dict
configObj = teal.teal(configObj,loadOnly=False)
return configObj
