def main2():
funcSpecs = {'Orient': '', 'Dimensions': '', 'Thickness': 0, 'Reps': 0, 'TR': 0, 'Origin': 0, 'Slices': 0}
subjDict = {'sub{:003d}'.format(s): {'Run{:d}'.format(i): dict(funcSpecs) for i in [4]} for s in [15]}
#-------------------#
# Ready, Begin #
#-------------------#
subj = 'sub015'
scan = 'Run4'
print '\n', subj, scan
#---------------------------------#
# Directory Pointers #
#---------------------------------#
ICEWORD = '/Volumes/Data/IcewordNEW'
FUNC = os.path.join(ICEWORD, subj, 'Func')
RD = os.path.join(FUNC, scan, 'RealignDetails')
#---------------------------------#
# Functional Images #
#---------------------------------#
img = '-'.join([subj, scan.lower() + '.nii.gz'])
imgFile = os.path.join(FUNC, scan, img)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing getFuncSpec():
# ++
# This will extract the specs of the imageFIle and update
# the subjDict to reflect the information extracted.
# Supplied variables are the image file in question, the
# subject Dictionary, and the reference to subj and scan,
# this is done as a control check to make sure the program is
# outputting the correct information.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
print '\n\tpopulating header'
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing volumeTrim():
# ++
# This will trim the first X volumes from the image. If the
# image has 214 TRs, then only 1 volume is removed, otherwise
# 5 volumes will be removed.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
if subjDict[subj][scan]['Reps'] == '214':
trim = '1'
else:
trim = '5'
imgFile = volumeTrim(imgFile, trim)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing writeReport():
# ++
# sub4dImg -- input file
# subStatsImg -- output file name
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
writeReport(subjDict)
def main2():
funcSpecs = {
'Orient': '',
'Dimensions': '',
'Thickness': 0,
'Reps': 0,
'TR': 0,
'Origin': 0,
'Slices': 0
}
subjDict = {
'sub{:003d}'.format(s):
{'Run{:d}'.format(i): dict(funcSpecs)
for i in [4]}
for s in [15]
}
#-------------------#
# Ready, Begin #
#-------------------#
subj = 'sub015'
scan = 'Run4'
print '\n', subj, scan
#---------------------------------#
# Directory Pointers #
#---------------------------------#
ICEWORD = '/Volumes/Data/IcewordNEW'
FUNC = os.path.join(ICEWORD, subj, 'Func')
RD = os.path.join(FUNC, scan, 'RealignDetails')
#---------------------------------#
# Functional Images #
#---------------------------------#
img = '-'.join([subj, scan.lower() + '.nii.gz'])
imgFile = os.path.join(FUNC, scan, img)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing getFuncSpec():
# ++
# This will extract the specs of the imageFIle and update
# the subjDict to reflect the information extracted.
# Supplied variables are the image file in question, the
# subject Dictionary, and the reference to subj and scan,
# this is done as a control check to make sure the program is
# outputting the correct information.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
print '\n\tpopulating header'
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing volumeTrim():
# ++
# This will trim the first X volumes from the image. If the
# image has 214 TRs, then only 1 volume is removed, otherwise
# 5 volumes will be removed.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
if subjDict[subj][scan]['Reps'] == '214':
trim = '1'
else:
trim = '5'
imgFile = volumeTrim(imgFile, trim)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing writeReport():
# ++
# sub4dImg -- input file
# subStatsImg -- output file name
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
writeReport(subjDict)
def main():
funcSpecs = {'Orient': '', 'Dimensions': '', 'Thickness': 0, 'Reps': 0, 'TR': 0, 'Origin': 0, 'Slices': 0}
subjDict = {'sub{:003d}'.format(s): {'Run{:d}'.format(i): dict(funcSpecs) for i in [1, 2, 3, 4]} for s in range(1, 20)}
#-------------------#
# Ready, Begin #
#-------------------#
for subscan in [(sub, scan) for sub in subjDict.keys() for scan in subjDict[sub].keys()]:
subj, scan = subscan
print '\n', subj, scan
#---------------------------------#
# Directory Pointers #
#---------------------------------#
ICEWORD = '/Volumes/Data/IcewordNEW'
FUNC = os.path.join(ICEWORD, subj, 'Func')
RD = os.path.join(FUNC, scan, 'RealignDetails')
#---------------------------------#
# Functional Images #
#---------------------------------#
img = '_'.join([subj, scan.lower(), 'RAW.nii'])
imgFile = os.path.join(FUNC, scan, img)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing getFuncSpec():
# ++
# This will extract the specs of the imageFIle and update
# the subjDict to reflect the information extracted.
# Supplied variables are the image file in question, the
# subject Dictionary, and the reference to subj and scan,
# this is done as a control check to make sure the program is
# outputting the correct information.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
print '\n\tpopulating header'
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing makeImageCorrections():
# ++
# This will make corrections to each of the images via resample.
# It returns a pointer to the new image file created.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
print '\n\tmaking Image corrections'
imgFile = makeImageCorrections(imgFile)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing volumeTrim():
# ++
# This will trim the first X volumes from the image. If the
# image has 214 TRs, then only 1 volume is removed, otherwise
# 5 volumes will be removed.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
if subjDict[subj][scan]['Reps'] == '214':
trim = '1'
else:
trim = '5'
imgFile = volumeTrim(imgFile, trim)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing sliceTiming():
# ++
# This will trim the first X volumes from the image. If the
# image has 214 TRs, then only 1 volume is removed, otherwise
# 5 volumes will be removed.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
imgFile = sliceTiming(imgFile)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing volumeReg():
# ++
# After a base volume is identified, volumeReg is performed.
# It will correct for motion related errors.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
base = baseVolume(imgFile)
imgFile = volumeReg(imgFile, base)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing despikeVolume():
# ++
# After a base volume is identified, volumeReg is performed.
# It will correct for motion related errors.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
imgFile = despikeVolume(imgFile)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing smoothVolume():
# ++
# After a base volume is identified, volumeReg is performed.
# It will correct for motion related errors.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
imgFile = smoothVolume(imgFile)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing writeReport():
# ++
# sub4dImg -- input file
# subStatsImg -- output file name
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
writeReport(subjDict)
def main():
funcSpecs = {
'Orient': '',
'Dimensions': '',
'Thickness': 0,
'Reps': 0,
'TR': 0,
'Origin': 0,
'Slices': 0
}
subjDict = {
'sub{:003d}'.format(s):
{'Run{:d}'.format(i): dict(funcSpecs)
for i in [1, 2, 3, 4]}
for s in range(1, 20)
}
#-------------------#
# Ready, Begin #
#-------------------#
for subscan in [(sub, scan) for sub in subjDict.keys()
for scan in subjDict[sub].keys()]:
subj, scan = subscan
print '\n', subj, scan
#---------------------------------#
# Directory Pointers #
#---------------------------------#
ICEWORD = '/Volumes/Data/IcewordNEW'
FUNC = os.path.join(ICEWORD, subj, 'Func')
RD = os.path.join(FUNC, scan, 'RealignDetails')
#---------------------------------#
# Functional Images #
#---------------------------------#
img = '_'.join([subj, scan.lower(), 'RAW.nii'])
imgFile = os.path.join(FUNC, scan, img)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing getFuncSpec():
# ++
# This will extract the specs of the imageFIle and update
# the subjDict to reflect the information extracted.
# Supplied variables are the image file in question, the
# subject Dictionary, and the reference to subj and scan,
# this is done as a control check to make sure the program is
# outputting the correct information.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
print '\n\tpopulating header'
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing makeImageCorrections():
# ++
# This will make corrections to each of the images via resample.
# It returns a pointer to the new image file created.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
print '\n\tmaking Image corrections'
imgFile = makeImageCorrections(imgFile)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing volumeTrim():
# ++
# This will trim the first X volumes from the image. If the
# image has 214 TRs, then only 1 volume is removed, otherwise
# 5 volumes will be removed.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
if subjDict[subj][scan]['Reps'] == '214':
trim = '1'
else:
trim = '5'
imgFile = volumeTrim(imgFile, trim)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing sliceTiming():
# ++
# This will trim the first X volumes from the image. If the
# image has 214 TRs, then only 1 volume is removed, otherwise
# 5 volumes will be removed.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
imgFile = sliceTiming(imgFile)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing volumeReg():
# ++
# After a base volume is identified, volumeReg is performed.
# It will correct for motion related errors.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
base = baseVolume(imgFile)
imgFile = volumeReg(imgFile, base)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing despikeVolume():
# ++
# After a base volume is identified, volumeReg is performed.
# It will correct for motion related errors.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
imgFile = despikeVolume(imgFile)
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing smoothVolume():
# ++
# After a base volume is identified, volumeReg is performed.
# It will correct for motion related errors.
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
imgFile = smoothVolume(imgFile)
getFuncSpec(imgFile, subjDict[subj][scan])
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Executing writeReport():
# ++
# sub4dImg -- input file
# subStatsImg -- output file name
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
writeReport(subjDict)
