def __isValidStructure(self):
"""Determine if the directory is a valid structure
Returns:
a Boolean that represent if validation is required for that directory
"""
if not self.__validateImage(self.config.get('prefix', 'anat')):
return False
if not self.__validateImage(self.config.get('prefix', 'dwi')):
return False
dwi = util.getImage(self.config, self.workingDir, 'dwi')
#@TODO fix data layout incomprehesion
#make sure that diffusion image Z scale layout is oriented correctly
#if not mriutil.isDataLayoutValid(dwiImage):
# self.error("Data layout for {} image is unexpected. "
# "Only data layout = [ +0 +1 +2 +3 ] could be process".format(dwiImage))
nbDirections = mriutil.getNbDirectionsFromDWI(dwi)
if nbDirections <= 45:
msg = "Found only {} directions into {} image. Hardi model will not be accurate with diffusion weighted image " \
"that contain less than 45 directions\n\n".format(nbDirections, self.dwi)
if self.config.getboolean('arguments', 'prompt'):
util.displayYesNoMessage(msg)
else:
self.warning(msg)
bEnc = util.getImage(self.config, self.workingDir, 'grad', None, 'b')
bVal = util.getImage(self.config, self.workingDir, 'grad', None,
'bval')
bVec = util.getImage(self.config, self.workingDir, 'grad', None,
'bvec')
if (not bEnc) and (not bVal or not bVec):
self.logger.warning("No valid .b encoding or pair of .bval, .bvec"
" file found in directory: {}".format(
self.workingDir))
return False
#@TODO uncomment and fix not all zero bvec value in the first line
"""
if bEnc and not self.__isValidEncoding(nbDirections, '.b'):
self.logger.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVal and not self.__isValidEncoding(nbDirections, '.bval'):
self.logger.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVec and not self.__isValidEncoding(nbDirections, '.bvec'):
self.logger.warning("Encoding file {} is invalid".format(bVec))
return False
"""
return True
def __isValidStructure(self):
"""Determine if the directory is a valid structure
Returns:
a Boolean that represent if validation is required for that directory
"""
if not self.__validateImage(self.config.get('prefix','anat')):
return False
if not self.__validateImage(self.config.get('prefix','dwi')):
return False
dwi = util.getImage(self.config, self.workingDir,'dwi')
#@TODO fix data layout incomprehesion
#make sure that diffusion image Z scale layout is oriented correctly
#if not mriutil.isDataLayoutValid(dwiImage):
# self.error("Data layout for {} image is unexpected. "
# "Only data layout = [ +0 +1 +2 +3 ] could be process".format(dwiImage))
nbDirections = mriutil.getNbDirectionsFromDWI(dwi)
if nbDirections <= 45:
msg = "Found only {} directions into {} image. Hardi model will not be accurate with diffusion weighted image " \
"that contain less than 45 directions\n\n".format(nbDirections, self.dwi)
if self.config.getboolean('arguments', 'prompt'):
util.displayYesNoMessage(msg)
else:
self.warning(msg)
bEnc = util.getImage(self.config, self.workingDir,'grad', None, 'b')
bVal = util.getImage(self.config, self.workingDir,'grad', None, 'bval')
bVec = util.getImage(self.config, self.workingDir,'grad', None, 'bvec')
if (not bEnc) and (not bVal or not bVec):
self.logger.warning("No valid .b encoding or pair of .bval, .bvec"
" file found in directory: {}".format(self.workingDir))
return False
#@TODO uncomment and fix not all zero bvec value in the first line
"""
if bEnc and not self.__isValidEncoding(nbDirections, '.b'):
self.logger.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVal and not self.__isValidEncoding(nbDirections, '.bval'):
self.logger.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVec and not self.__isValidEncoding(nbDirections, '.bvec'):
self.logger.warning("Encoding file {} is invalid".format(bVec))
return False
"""
return True
def __isValidEncoding(self, nbDirection, type):
"""Determine if an image with a prefix exists into the subject directory
Args:
nbDirection: number of direction into DWI image
type: type of encoding file. Valid values are: .b, .bval, .bvec
Returns:
a Boolean that represent if the encoding file is valid
"""
encoding = util.getImage(self.config, self.workingDir, 'grad', None, type)
if not encoding:
self.logger.warning("No {} encoding file found in directory: {}"
.format(type, self.workingDir))
return False
f = open(encoding,'r')
lines = f.readlines()
f.close()
if type=='.bval':
for line in lines:
nbElements = len(line.split())
if nbElements != nbDirection:
self.logger.warning("Expecting {} elements in {} file, counting {}"
.format(nbDirection, encoding, nbElements))
return False
elif type=='.bvec':
if len(lines) != 3:
self.logger.warning("Expecting 3 vectors in {} file, counting {}".format(encoding, len(lines)))
return False
for line in lines:
if len(line.split()) != nbDirection:
self.logger.warning("Expecting {} values in {} file, counting {}"
.format(nbDirection, encoding, len(line.split())))
return False
elif type=='.b':
if len(lines) != nbDirection:
self.logger.warning("Expecting {} lines in {} file, counting {}".format(nbDirection, type, len(lines)))
return False
for index, line in enumerate(lines):
if index == 0:
for token in line.split():
if token not in "0" :
self.logger.warning("Expecting only zero values in the first line of file {}, found value {}"
.format(encoding, token))
return False
if len(line.split()) != 4:
self.logger.warning("Expecting 4 elements at line {} of file {}, counting {}"
.format(index+1, encoding, len(line.split())))
return False
else:
self.logger.warning("Unknown encoding file type")
return False
return True
def isAToadSubject(self):
"""Determine if the directory contain all the necessary images to be consider a toad subject.
Must have at least.
1 high resolution anatomical image (nii or nii.gz)
1 diffusion weighted image (nii or nii.gz)
A corresponding B (.b) encoding or a pair of bvecs (.bvecs), bvals (.bvals) encoding file
Returns:
False if one of those file are missing, True otherwise
"""
result = True
if os.path.exists(self.backupDir):
self.info("{} directory exists, assuming validation have already done before".format(self.backupDir))
result = True
else:
if not (util.getImage(self.config, self.workingDir, 'anat') or
util.getImage(self.config, self.workingDir, 'anat', None, 'nii')):
self.warning("No high resolution image found into {} directory".format(self.workingDir))
result = False
if not (util.getImage(self.config, self.workingDir, 'dwi') or
util.getImage(self.config, self.workingDir, 'dwi', None, 'nii')):
self.warning("No diffusion weight image found into {} directory".format(self.workingDir))
result = False
if (not util.getImage(self.config, self.workingDir,'grad', None, 'b')) and \
(not util.getImage(self.config, self.workingDir,'grad', None, 'bvals') or not
util.getImage(self.config, self.workingDir,'grad', None, 'bvecs')):
self.warning("No valid .b encoding or (.bvals, .bvecs) files found in directory: {}".format(self.workingDir))
result = False
return result
def getImage(self, dir, prefix, postfix=None, ext="nii"):
"""A simple utility function that return an mri image given certain criteria
this is a wrapper over mriutil getImage function
Args:
dir: the directory where looking for the image
prefix: an expression that the filename should start with
postfix: an expression that the filename should end with (excluding the extension)
ext: name of the extension of the filename
Returns:
the absolute filename if found, False otherwise
"""
return util.getImage(self.config, dir, prefix, postfix, ext)
def isAToadSubject(self):
"""Determine if the directory contain all the necessary images to be consider a toad subject.
Must have at least.
1 high resolution anatomical image (nii or nii.gz)
1 diffusion weighted image (nii or nii.gz)
A corresponding B (.b) encoding or a pair of bvecs (.bvecs), bvals (.bvals) encoding file
Returns:
False if one of those file are missing, True otherwise
"""
result = True
if os.path.exists(self.backupDir):
self.info(
"{} directory exists, assuming validation have already done before"
.format(self.backupDir))
result = True
else:
if not (util.getImage(self.config, self.workingDir, 'anat')
or util.getImage(self.config, self.workingDir, 'anat',
None, 'nii')):
self.warning(
"No high resolution image found into {} directory".format(
self.workingDir))
result = False
if not (util.getImage(self.config, self.workingDir, 'dwi')
or util.getImage(self.config, self.workingDir, 'dwi', None,
'nii')):
self.warning(
"No diffusion weight image found into {} directory".format(
self.workingDir))
result = False
if (not util.getImage(self.config, self.workingDir, 'grad', None, 'b')) and \
(not util.getImage(self.config, self.workingDir, 'grad', None, 'bvals') or not
util.getImage(self.config, self.workingDir, 'grad', None, 'bvecs')):
self.warning(
"No valid .b encoding or (.bvals, .bvecs) files found in directory: {}"
.format(self.workingDir))
result = False
return result
def wrapper(*args):
arguments = [self.config, directory] + list(args)
return util.getImage(*arguments)
def __isAValidStructure(self):
"""Determine if the directory is a valid structure
Returns:
a Boolean that represent if the subject integrity test pass for that directory
"""
#Anatomical, Dwi and gradient encoding direction are mandatory input
anat = util.getImage(self.config, self.workingDir, 'anat')
if not anat:
if util.getImage(self.config, self.workingDir, 'anat', None, 'nii'):
self.warning("Found some uncompressed nifti images into {} directory. "
"Please gzip those images and resubmit the pipeline again".format(self.workingDir))
return False
self.warning("No high resolution image found into {} directory".format(self.workingDir))
return False
dwi = util.getImage(self.config, self.workingDir, 'dwi')
if not dwi:
if util.getImage(self.config, self.workingDir, 'dwi', None, 'nii'):
self.warning("Found some uncompressed nifti image into {} directory. "
"Please gzip those images and resubmit the pipeline again".format(self.workingDir))
return False
self.warning("No diffusion weight image found into {} directory".format(self.workingDir))
return False
bEnc = util.getImage(self.config, self.workingDir,'grad', None, 'b')
bVals = util.getImage(self.config, self.workingDir,'grad', None, 'bvals')
bVecs = util.getImage(self.config, self.workingDir,'grad', None, 'bvecs')
if (not bEnc) and (not bVals or not bVecs):
self.warning("No valid .b encoding or (.bvals, .bvecs) files found in directory: {}".format(self.workingDir))
return False
else:
nbDirections = mriutil.getNbDirectionsFromDWI(dwi)
if nbDirections <= 45:
msg = "Found only {} directions into {} image. Hardi model will not be accurate with diffusion weighted image " \
"that contain less than 45 directions\n\n".format(nbDirections, dwi)
self.warning(msg)
#return False
if bEnc and not self.__isValidEncoding(nbDirections, '.b'):
self.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVals and not self.__isValidEncoding(nbDirections, '.bvals'):
self.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVecs and not self.__isValidEncoding(nbDirections, '.bvecs'):
self.warning("Encoding file {} is invalid".format(bVecs))
return False
#Validate optionnal images
images = {
'anat': (anat, 'high resolution'),
'dwi': (dwi,'diffusion weighted'),
'mag': (util.getImage(self.config, self.workingDir, 'mag'), 'MR magnitude '),
'phase': (util.getImage(self.config, self.workingDir, 'phase'), 'MR phase '),
'b0_ap': (util.getImage(self.config, self.workingDir, 'b0_ap'), "posterior to anterior b0 "),
'b0_pa': (util.getImage(self.config, self.workingDir, 'b0_pa'), "anterior to posterior b0")}
if self.config.get('arguments', 'debug') == 'True':
self.debug("Images found into {} directory: {}".format(self.workingDir, images))
if self.config.getboolean('arguments', 'prompt'):
for key, (value, description) in images.iteritems():
if value:
if not mriutil.isDataStridesOrientationExpected(value, self.config.get('preparation', 'stride_orientation'))\
and self.config.getboolean("preparation", "force_realign_strides"):
msg = "Data strides layout for {} is unexpected and force_realign_strides is set to True.\n \
If you continue, all unexpected images will be realign accordingly.\n\
Only a copy of the original images will be alter.".format(value)
if not util.displayYesNoMessage(msg):
self.warning("Remove this subject from the list?")
return False
else:
break
#if one and only one b0 image is given, make sure that the b0 image is not on same direction than the dwi.
if (not (images['b0_ap'][0] and images['b0_pa'][0])) and (images['b0_ap'][0] or images['b0_pa'][0]) \
and (self.config.get("correction", "ignore") == "False"):
if ((self.config.get("correction", "phase_enc_dir") == "0") and images['b0_pa'][0]) \
or ((self.config.get("correction", "phase_enc_dir") == "1") and images['b0_ap'][0]):
msg = "Found only one B0 image into the subject directory and that B0 is in " \
"the same phase encoding direction than the DWI.\n" \
"We recommend to remove the B0 image so at least a motion correction will be perform"
if not util.displayYesNoMessage(msg):
self.warning("Remove this subject from the list?")
return False
if images['mag'][0] and images['phase'][0] and (images['b0_ap'][0] or images['b0_pa'][0]):
msg = "Found both Fieldmap and B0 images into the subject directory\n" \
"We recommend to disabled fieldmap correction?"
if not util.displayYesNoMessage(msg):
self.warning("Remove this subject from the list?")
return False
return True
def __isValidEncoding(self, nbDirection, type):
"""Determine if an image with a prefix exists into the subject directory
Args:
nbDirection: number of direction into DWI image
type: type of encoding file. Valid values are: .b, .bval, .bvec
Returns:
a Boolean that represent if the encoding file is valid
"""
encoding = util.getImage(self.config, self.workingDir, 'grad', None,
type)
if not encoding:
self.logger.warning(
"No {} encoding file found in directory: {}".format(
type, self.workingDir))
return False
f = open(encoding, 'r')
lines = f.readlines()
f.close()
if type == '.bval':
for line in lines:
nbElements = len(line.split())
if nbElements != nbDirection:
self.logger.warning(
"Expecting {} elements in {} file, counting {}".format(
nbDirection, encoding, nbElements))
return False
elif type == '.bvec':
if len(lines) != 3:
self.logger.warning(
"Expecting 3 vectors in {} file, counting {}".format(
encoding, len(lines)))
return False
for line in lines:
if len(line.split()) != nbDirection:
self.logger.warning(
"Expecting {} values in {} file, counting {}".format(
nbDirection, encoding, len(line.split())))
return False
elif type == '.b':
if len(lines) != nbDirection:
self.logger.warning(
"Expecting {} lines in {} file, counting {}".format(
nbDirection, type, len(lines)))
return False
for index, line in enumerate(lines):
if index == 0:
for token in line.split():
if token not in "0":
self.logger.warning(
"Expecting only zero values in the first line of file {}, found value {}"
.format(encoding, token))
return False
if len(line.split()) != 4:
self.logger.warning(
"Expecting 4 elements at line {} of file {}, counting {}"
.format(index + 1, encoding, len(line.split())))
return False
else:
self.logger.warning("Unknown encoding file type")
return False
return True
def __isAValidStructure(self):
"""Determine if the directory is a valid structure
Returns:
a Boolean that represent if the subject integrity test pass for that directory
"""
#Anatomical, Dwi and gradient encoding direction are mandatory input
anat = util.getImage(self.config, self.workingDir, 'anat')
if not anat:
if util.getImage(self.config, self.workingDir, 'anat', None,
'nii'):
self.warning(
"Found some uncompressed nifti images into {} directory. "
"Please gzip those images and resubmit the pipeline again".
format(self.workingDir))
return False
self.warning(
"No high resolution image found into {} directory".format(
self.workingDir))
return False
dwi = util.getImage(self.config, self.workingDir, 'dwi')
if not dwi:
if util.getImage(self.config, self.workingDir, 'dwi', None, 'nii'):
self.warning(
"Found some uncompressed nifti image into {} directory. "
"Please gzip those images and resubmit the pipeline again".
format(self.workingDir))
return False
self.warning(
"No diffusion weight image found into {} directory".format(
self.workingDir))
return False
bEnc = util.getImage(self.config, self.workingDir, 'grad', None, 'b')
bVals = util.getImage(self.config, self.workingDir, 'grad', None,
'bvals')
bVecs = util.getImage(self.config, self.workingDir, 'grad', None,
'bvecs')
if (not bEnc) and (not bVals or not bVecs):
self.warning(
"No valid .b encoding or (.bvals, .bvecs) files found in directory: {}"
.format(self.workingDir))
return False
else:
nbDirections = mriutil.getNbDirectionsFromDWI(dwi)
if nbDirections <= 45:
msg = "Found only {} directions into {} image. Hardi model will not be accurate with diffusion weighted image " \
"that contain less than 45 directions\n\n".format(nbDirections, dwi)
self.warning(msg)
#return False
if bEnc and not self.__isValidEncoding(nbDirections, '.b'):
self.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVals and not self.__isValidEncoding(nbDirections, '.bvals'):
self.warning("Encoding file {} is invalid".format(bEnc))
return False
if bVecs and not self.__isValidEncoding(nbDirections, '.bvecs'):
self.warning("Encoding file {} is invalid".format(bVecs))
return False
#Validate optionnal images
images = {
'anat': (anat, 'high resolution'),
'dwi': (dwi, 'diffusion weighted'),
'mag': (util.getImage(self.config, self.workingDir,
'mag'), 'MR magnitude '),
'phase': (util.getImage(self.config, self.workingDir,
'phase'), 'MR phase '),
'b0_ap': (util.getImage(self.config, self.workingDir,
'b0_ap'), "posterior to anterior b0 "),
'b0_pa': (util.getImage(self.config, self.workingDir,
'b0_pa'), "anterior to posterior b0")
}
if self.config.get('arguments', 'debug') == 'True':
self.debug("Images found into {} directory: {}".format(
self.workingDir, images))
if self.config.getboolean('arguments', 'prompt'):
for key, (value, description) in images.iteritems():
if value:
if not mriutil.isDataStridesOrientationExpected(value, self.config.get('preparation', 'stride_orientation'))\
and self.config.getboolean("preparation", "force_realign_strides"):
msg = "Data strides layout for {} is unexpected and force_realign_strides is set to True.\n \
If you continue, all unexpected images will be realign accordingly.\n\
Only a copy of the original images will be alter.".format(
value)
if not util.displayYesNoMessage(msg):
self.warning("Remove this subject from the list?")
return False
else:
break
#if one and only one b0 image is given, make sure that the b0 image is not on same direction than the dwi.
if (not (images['b0_ap'][0] and images['b0_pa'][0])) and (images['b0_ap'][0] or images['b0_pa'][0]) \
and (self.config.get("correction", "ignore") == "False"):
if ((self.config.get("correction", "phase_enc_dir") == "0") and images['b0_pa'][0]) \
or ((self.config.get("correction", "phase_enc_dir") == "1") and images['b0_ap'][0]):
msg = "Found only one B0 image into the subject directory and that B0 is in " \
"the same phase encoding direction than the DWI.\n" \
"We recommend to remove the B0 image so at least a motion correction will be perform"
if not util.displayYesNoMessage(msg):
self.warning("Remove this subject from the list?")
return False
if images['mag'][0] and images['phase'][0] and (
images['b0_ap'][0] or images['b0_pa'][0]):
msg = "Found both Fieldmap and B0 images into the subject directory\n" \
"We recommend to disabled fieldmap correction?"
if not util.displayYesNoMessage(msg):
self.warning("Remove this subject from the list?")
return False
return True
def wrapper(*args):
arguments = [self.config, directory] + list(args)
return util.getImage(*arguments)
