def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'registration',
'tensorfsl', 'hardidipy', 'tractquerier', 'qa')
self.setCleanupBeforeImplement(False)
self.absInDir = os.path.join(self.workingDir, 'input')
self.relativeOutDir = 'output/subject/outlier_cleaned_tracts'
self.absOutDir = os.path.join(self.workingDir, 'output')
def __init__(self, subject):
GenericTask.__init__(
self, subject, 'upsampling', 'registration', 'masking', 'qa'
)
self.__dwiData = None
self.__csdModel = None
self.__csdPeaks = None
def __init__(self, subject):
GenericTask.__init__(
self, subject, "preparation", "registration", "tensorfsl", "hardidipy", "tractquerier", "qa"
)
self.setCleanupBeforeImplement(False)
self.relativeOutDir = "raw/outlier_cleaned_tracts"
self.absOutDir = os.path.join(self.workingDir, "raw", "outlier_cleaned_tracts")
def __init__(self, subject):
GenericTask.__init__(self, subject,
'preparation', 'registration', 'tensorfsl',
'hardidipy', 'tractquerier', 'qa')
self.setCleanupBeforeImplement(False)
self.absInDir = os.path.join(self.workingDir, 'input')
self.relativeOutDir = 'output/subject/outlier_cleaned_tracts'
self.absOutDir = os.path.join(self.workingDir, 'output')
def __init__(self, subject):
GenericTask.__init__(
self, subject, 'preparation', 'tensorfsl', 'tensormrtrix',
'tensordipy', 'hardimrtrix', 'hardidipy', 'tractfiltering',)
self.setCleanupBeforeImplement(False)
self.absInDir = os.path.join(self.workingDir, 'input')
self.absOutDir = os.path.join(self.workingDir, 'output')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'hardimrtrix',
'masking', 'registration', 'atlasregistration' ,'qa')
self.__tckDetRoiTrk = None
self.__tckProbRoiTrk = None
self.__tckgenRoiTrk = None
self.__tcksiftRoiTrk = None
self.__nbDirections = None
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'hardimrtrix',
'masking', 'registration', 'atlasregistration',
'qa')
self.__tckDetRoiTrk = None
self.__tckProbRoiTrk = None
self.__tckgenRoiTrk = None
self.__tcksiftRoiTrk = None
self.__nbDirections = None
def __init__(self, subject):
GenericTask.__init__(
self,
subject,
'preparation',
'tensorfsl',
'tensormrtrix',
'tensordipy',
'hardimrtrix',
'hardidipy',
'tractfiltering',
)
self.setCleanupBeforeImplement(False)
self.absInDir = os.path.join(self.workingDir, 'input')
self.absOutDir = os.path.join(self.workingDir, 'output')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'parcellation', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'registration', 'masking', 'qa')
self.__fit = None
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'parcellation', 'denoising', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, "preparation", "correction", "denoising", "masking", "qa")
def __init__(self, subject):
GenericTask.__init__(
self, subject,
'preparation', 'upsampling', 'registration', 'atlasregistration',
'tractographymrtrix', 'qa')
self.setCleanupBeforeImplement(False)
def __init__(self, subject):
"""Fits a diffusion tensor model at each voxel
"""
GenericTask.__init__(self, subject, 'upsampling', 'registration',
'masking', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'parcellation', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'registration', 'tensormrtrix', 'tensordipy', 'tensorfsl',
'hardidipy', 'hardimrtrix', 'tractographymrtrix', 'tractquerier', 'tractfiltering', 'tractometry')
self.__finished = False
def __init__(self, subject):
GenericTask.__init__(self, subject, "masking", "registration",
"hardidipy")
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'correction',
'denoising', 'masking', 'qa')
def __init__(self, subject):
self.subjectDir = subject.getDir()
GenericTask.__init__(self, subject)
self.setCleanupBeforeImplement(False)
def __init__(self, subject):
GenericTask.__init__(self, subject, "upsampling", "registration", "masking", "qa")
self.__dwiData = None
self.__csdModel = None
self.__csdPeaks = None
def __init__(self, subject):
GenericTask.__init__(self, subject,'preparation', 'parcellation', 'qa')
self.matlabWarning = False
self.sigmaVector = None
self.algorithm = None
def __init__(self, subject):
GenericTask.__init__(self, subject, 'atlas', 'upsampling', 'registration')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'backup', 'qa')
def __init__(self, subject):
"""initialisation methods. Please leave as is"""
GenericTask.__init__(self, subject, 'parcellation', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject,'preparation', 'parcellation', 'qa')
self.matlabWarning = False
self.sigmaVector = None
self.algorithm = None
def __init__(self, subject):
GenericTask.__init__(self, subject, 'backup')
self.setCleanupBeforeImplement(False)
self.subjectName = subject.getName()
def __init__(self, subject):
GenericTask.__init__(self, subject, 'backup')
self.setCleanupBeforeImplement(False)
self.subjectName = subject.getName()
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'upsampling',
'registration', 'atlasregistration',
'tractographymrtrix', 'qa')
self.setCleanupBeforeImplement(False)
def __init__(self, subject):
GenericTask.__init__(self, subject, "masking", "registration", "hardidipy")
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'registration', 'tensormrtrix', 'tensordipy', 'tensorfsl', 'hardidipy', 'hardimrtrix')
self.__finished = False
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'correction', 'denoising', 'masking', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'registration',
'tensormrtrix', 'tensordipy', 'tensorfsl',
'hardidipy', 'hardimrtrix', 'tractographymrtrix',
'tractquerier', 'tractfiltering', 'tractometry')
self.__finished = False
def __init__(self, subject):
GenericTask.__init__(self, subject, 'registration', 'upsampling', 'qa')
def __init__(self, subject):
self.subjectDir = subject.getDir()
GenericTask.__init__(self, subject)
self.setCleanupBeforeImplement(False)
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'parcellation',
'denoising', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'qa')
self.id = self.get('id')
def __init__(self, subject):
"""Fits a diffusion tensor model at each voxel
"""
GenericTask.__init__(self, subject, 'upsampling', 'registration', 'masking', 'qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'hardimrtrix', 'masking', 'registration','qa')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'backup', 'qa')
def __init__(self, subject):
"""initialisation methods. Please leave as is"""
GenericTask.__init__(self, subject, 'parcellation', 'qa')
def __init__(self, subject):
GenericTask.__init__(
self, subject, 'preparation', 'tensorfsl', 'tensormrtrix',
'tensordipy', 'hardimrtrix', 'hardidipy', 'tractfiltering',)
self.setCleanupBeforeImplement(False)
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'parcellation', 'denoising', 'qa')
self.__topupCorrection = False
self.__fieldmapCorrection = False
def __init__(self, subject):
GenericTask.__init__(self, subject, 'preparation', 'qa')
self.id = self.get('id')
def __init__(self, subject):
GenericTask.__init__(self, subject, 'upsampling', 'registration',
'masking', 'qa')
self.__dwiData = None
self.__csdModel = None
self.__csdPeaks = None
