def f_stage3callback(**kwargs):
str_cwd = os.getcwd()
lst_subj = []
for key, val in kwargs.iteritems():
if key == 'subj': lst_subj = val
if key == 'obj': stage = val
for subj in lst_subj:
# find the relevant input files in each <subj> dir
os.chdir(subj)
l_ADC = misc.find(_str_adc)
if not l_ADC: error.fatal(pipe_hypothermia, 'noADC')
_str_ADCFile = l_ADC[0]
_str_outDir = 'outDir'
misc.mkdir(_str_outDir)
log = stage.log()
log('Scheduling masconorm for "%s: ADC"..\n' % (subj))
str_cmd = 'masconorm.py --input %s --mask %s/b0Brain_mask.nii.gz --outStem %s/adc' % (
_str_ADCFile,
_str_outDir,
_str_outDir)
cluster = crun.crun()
cluster.echo(False)
cluster.echoStdOut(False)
cluster.detach(False)
cluster(str_cmd, waitForChild=True, stdoutflush=True, stderrflush=True)
os.chdir(str_cwd)
return True
def run(self):
'''
Runs the DICOM conversion based on internal state.
'''
self._log('Converting DICOM image.\n')
self._log('PatientName: %s\n' % self._dcm.PatientName)
self._log('PatientAge: %s\n' % self._dcm.PatientAge)
self._log('PatientSex: %s\n' % self._dcm.PatientSex)
self._log('PatientID: %s\n' % self._dcm.PatientID)
self._log('SeriesDescription: %s\n' % self._dcm.SeriesDescription)
self._log('ProtocolName: %s\n' % self._dcm.ProtocolName)
if self._b_convertMiddleSlice:
self._log('Converting middle slice in DICOM series: %d\n' % self._sliceToConvert)
l_rot90 = [ True, True, False ]
misc.mkdir(self._str_outputDir)
if not self._b_3D:
str_outputFile = '%s/%s.%s' % (self._str_outputDir,
self._str_outputFileStem,
self._str_outputFileType)
self.slice_save(str_outputFile)
if self._b_3D:
rotCount = 0
if self._b_reslice:
for dim in ['x', 'y', 'z']:
self.dim_save(dimension = dim, makeSubDir = True, rot90 = l_rot90[rotCount], indexStart = 0, indexStop = -1)
rotCount += 1
else:
self.dim_save(dimension = 'z', makeSubDir = False, rot90 = False, indexStart = 0, indexStop = -1)
def f_stage2callback(**kwargs):
str_cwd = os.getcwd()
lst_subj = []
for key, val in kwargs.iteritems():
if key == 'subj': lst_subj = val
if key == 'obj': stage = val
for subj in lst_subj:
# find the relevant input files in each <subj> dir
os.chdir(subj)
l_B0 = misc.find(_str_b0)
l_ASL = misc.find(_str_asl)
if not l_B0: error.fatal(pipe_hypothermia, 'noB0')
if not l_ASL: error.fatal(pipe_hypothermia, 'noASL')
_str_B0File = l_B0[0]
_str_ASLFile = l_ASL[0]
_str_outDir = 'outDir'
_str_outFile = 'asl2b0.nii'
misc.mkdir(_str_outDir)
log = stage.log()
log('Scheduling masconorm for "%s: ASL"..\n' % (subj))
str_cmd = 'masconorm.py --input %s/asl2b0.nii.gz --mask %s/b0Brain_mask.nii.gz --outStem %s/asl' % (
_str_outDir,
_str_outDir,
_str_outDir)
#cluster = crun.crun_mosix()
cluster = crun.crun()
cluster.echo(False)
cluster.echoStdOut(False)
cluster.detach(False)
cluster(str_cmd, waitForChild=True, stdoutflush=True, stderrflush=True)
if cluster.exitCode():
error.fatal(pipe_hypothermia, 'stageExec', cluster.stderr())
os.chdir(str_cwd)
return True
def __init__(self, **kwargs):
# global settings
self._log = message.Message()
self._l_subject = []
self._l_hemi = []
self._l_surface = []
self._l_curv = []
# Internal tracking vars
self._str_subj = ''
self._str_hemi = ''
self._str_surface = ''
self._str_curv = ''
self._str_workingDir = os.getcwd()
self._browser = webdriver.Chrome()
self._str_outDir = _str_outDir
for key, value in kwargs.iteritems():
if key == 'subjectList': self._l_subject = value
if key == 'hemiList': self._l_hemi = value.split(',')
if key == 'surfaceList': self._l_surface = value.split(',')
if key == 'curvList': self._l_curv = value.split(',')
if key == 'syslog': self._log.syslog(value)
if key == 'logTo': self._log.to(value)
if key == 'logTee': self._log.tee(value)
if key == 'outDir': self._str_outDir = value
if not os.path.exists(self._str_outDir):
self._log('Output image dir not found, creating...\n')
misc.mkdir(self._str_outDir)
def f_stage0callback(**kwargs):
str_cwd = os.getcwd()
lst_subj = []
for key, val in kwargs.iteritems():
if key == 'subj': lst_subj = val
if key == 'obj': stage = val
for subj in lst_subj:
# find the relevant input files in each <subj> dir
os.chdir(subj)
l_B0 = misc.find(_str_b0)
if not l_B0: error.fatal(pipe_hypothermia, 'noB0')
_str_B0File = l_B0[0]
_str_outDir = '%s/outDir' % os.getcwd()
_str_outFile = 'b0Brain.nii'
misc.mkdir(_str_outDir)
str_prefixCmd = '( cd %s ; ' % (os.getcwd())
log = stage.log()
log('Scheduling brain extraction for "%s"...\n' % (subj))
str_cmd = 'bet.py --input %s --output %s/%s' % (_str_B0File,
_str_outDir, _str_outFile)
#cluster = crun.crun_mosix(cmdPrefix=str_prefixCmd)
#cluster = crun.crun_mosix()
cluster = crun.crun()
#str_ccmd = cluster.echo(True)
#log(str_ccmd)
cluster.echo(False)
cluster.echoStdOut(False)
cluster.detach(False)
cluster(str_cmd, waitForChild=True, stdoutflush=True, stderrflush=True)
if cluster.exitCode():
error.fatal(pipe_hypothermia, 'stageExec', cluster.stderr())
os.chdir(str_cwd)
return True
def run(self):
'''
Runs the NIfTI conversion based on internal state.
'''
self._log('About to perform NifTI to %s conversion...\n' %
self._str_outputFileType)
frames = 1
frameStart = 0
frameEnd = 0
sliceStart = 0
sliceEnd = 0
if self._b_4D:
self._log('4D volume detected.\n')
frames = self._Vnp_4DVol.shape[3]
if self._b_3D:
self._log('3D volume detected.\n')
if self._b_convertMiddleFrame:
self._frameToConvert = int(frames / 2)
if self._frameToConvert == -1:
frameEnd = frames
else:
frameStart = self._frameToConvert
frameEnd = self._frameToConvert + 1
for f in range(frameStart, frameEnd):
if self._b_4D:
self._Vnp_3DVol = self._Vnp_4DVol[:, :, :, f]
slices = self._Vnp_3DVol.shape[2]
if self._b_convertMiddleSlice:
self._sliceToConvert = int(slices / 2)
if self._sliceToConvert == -1:
sliceEnd = -1
else:
sliceStart = self._sliceToConvert
sliceEnd = self._sliceToConvert + 1
misc.mkdir(self._str_outputDir)
if self._b_reslice:
for dim in ['x', 'y', 'z']:
self.dim_save(dimension=dim,
makeSubDir=True,
indexStart=sliceStart,
indexStop=sliceEnd,
rot90=True)
else:
self.dim_save(dimension='z',
makeSubDir=False,
indexStart=sliceStart,
indexStop=sliceEnd,
rot90=True)
def run(self):
'''
Runs the NIfTI conversion based on internal state.
'''
self._log('About to perform NifTI to %s conversion...\n' %
self._str_outputFileType)
frames = 1
frameStart = 0
frameEnd = 0
sliceStart = 0
sliceEnd = 0
if self._b_4D:
self._log('4D volume detected.\n')
frames = self._Vnp_4DVol.shape[3]
if self._b_3D:
self._log('3D volume detected.\n')
if self._b_convertMiddleFrame:
self._frameToConvert = int(frames/2)
if self._frameToConvert == -1:
frameEnd = frames
else:
frameStart = self._frameToConvert
frameEnd = self._frameToConvert + 1
for f in range(frameStart, frameEnd):
if self._b_4D:
self._Vnp_3DVol = self._Vnp_4DVol[:,:,:,f]
slices = self._Vnp_3DVol.shape[2]
if self._b_convertMiddleSlice:
self._sliceToConvert = int(slices/2)
if self._sliceToConvert == -1:
sliceEnd = -1
else:
sliceStart = self._sliceToConvert
sliceEnd = self._sliceToConvert + 1
misc.mkdir(self._str_outputDir)
if self._b_reslice:
for dim in ['x', 'y', 'z']:
self.dim_save(dimension = dim, makeSubDir = True, indexStart = sliceStart, indexStop = sliceEnd, rot90 = True)
else:
self.dim_save(dimension = 'z', makeSubDir = False, indexStart = sliceStart, indexStop = sliceEnd, rot90 = True)
def run(self):
'''
Runs the DICOM conversion based on internal state.
'''
self._log('Converting DICOM image.\n')
self._log('PatientName: %s\n' %
self._dcm.PatientName)
self._log('PatientAge: %s\n' %
self._dcm.PatientAge)
self._log('PatientSex: %s\n' %
self._dcm.PatientSex)
self._log('PatientID: %s\n' %
self._dcm.PatientID)
self._log('SeriesDescription: %s\n' %
self._dcm.SeriesDescription)
self._log('ProtocolName: %s\n' %
self._dcm.ProtocolName)
if self._b_convertMiddleSlice:
self._log('Converting middle slice in DICOM series: %d\n' %
self._sliceToConvert)
l_rot90 = [True, True, False]
misc.mkdir(self._str_outputDir)
if not self._b_3D:
str_outputFile = '%s/%s.%s' % (self._str_outputDir,
self._str_outputFileStem,
self._str_outputFileType)
self.slice_save(str_outputFile)
if self._b_3D:
rotCount = 0
if self._b_reslice:
for dim in ['x', 'y', 'z']:
self.dim_save(dimension=dim,
makeSubDir=True,
rot90=l_rot90[rotCount],
indexStart=0,
indexStop=-1)
rotCount += 1
else:
self.dim_save(dimension='z',
makeSubDir=False,
rot90=False,
indexStart=0,
indexStop=-1)
def initialize(self):
'''
This method provides some "post-constructor" initialization. It is
typically called after the constructor and after other class flags
have been set (or reset).
'''
# Set the stages
self._pipeline.stages_canRun(False)
lst_stages = list(self._stageslist)
for index in lst_stages:
stage = self._pipeline.stage_get(int(index))
stage.canRun(True)
# Set absolute dir specs for topDir and outDir
log = self.log()
log('Setting dir specs...\n')
os.chdir(self.topDir())
self.topDir(os.path.abspath(self.topDir()))
if os.path.isdir(self.outDir()):
log('Existing output directory found. Deleting and recreating...\n')
shutil.rmtree(self.outDir())
misc.mkdir(self.outDir())
os.chdir(self.outDir())
self.outDir(os.getcwd())
os.chdir(self.topDir())
# check dirs for each subsample dir
# print(os.getcwd())
# print(self._l_subsample)
for directory in self._l_subsample:
if os.path.isdir(os.path.join(self.topDir(), directory)):
os.chdir(directory)
self._l_subsampleDir.append(os.path.abspath(os.getcwd()))
os.chdir(self.topDir())
else:
error.fatal(self, 'subsampleDirNotFound')
self._d_subsampleDir = dict(zip(self._l_subsample, self._l_subsampleDir))
# print(self._d_subsampleDir)
self.dtree_build()
self._dtree.tree_metaData_print(False)
def dim_save(self, **kwargs):
dims = self._Vnp_3DVol.shape
self._log('Image volume logical (i, j, k) size: %s\n' % str(dims))
str_dim = 'z'
b_makeSubDir = False
b_rot90 = False
frame = 0
indexStart = -1
indexStop = -1
for key, val in kwargs.iteritems():
if key == 'dimension': str_dim = val
if key == 'makeSubDir': b_makeSubDir = val
if key == 'frame': frame = val
if key == 'indexStart': indexStart = val
if key == 'indexStop': indexStop = val
if key == 'rot90': b_rot90 = val
str_subDir = ''
if b_makeSubDir:
str_subDir = str_dim
misc.mkdir('%s/%s' % (self._str_outputDir, str_subDir))
if str_dim == 'x':
if indexStart == 0 and indexStop == -1:
indexStop = dims[0]
for i in range(indexStart, indexStop):
self._Mnp_2Dslice = self._Vnp_3DVol[i,:,:]
if b_rot90: self._Mnp_2Dslice = np.rot90(self._Mnp_2Dslice)
self.dim_sliceSave(index = i, subDir = str_subDir)
if str_dim == 'y':
if indexStart == 0 and indexStop == -1:
indexStop = dims[1]
for j in range(indexStart, indexStop):
self._Mnp_2Dslice = self._Vnp_3DVol[:,j,:]
if b_rot90: self._Mnp_2Dslice = np.rot90(self._Mnp_2Dslice)
self.dim_sliceSave(index = j, subDir = str_subDir)
if str_dim == 'z':
if indexStart == 0 and indexStop == -1:
indexStop = dims[2]
for k in range(indexStart, indexStop):
self._Mnp_2Dslice = self._Vnp_3DVol[:,:,k]
if b_rot90: self._Mnp_2Dslice = np.rot90(self._Mnp_2Dslice)
self.dim_sliceSave(index = k, subDir = str_subDir)
def dim_save(self, **kwargs):
dims = self._Vnp_3DVol.shape
self._log('Image volume logical (i, j, k) size: %s\n' % str(dims))
str_dim = 'z'
b_makeSubDir = False
b_rot90 = False
frame = 0
indexStart = -1
indexStop = -1
for key, val in kwargs.iteritems():
if key == 'dimension': str_dim = val
if key == 'makeSubDir': b_makeSubDir = val
if key == 'frame': frame = val
if key == 'indexStart': indexStart = val
if key == 'indexStop': indexStop = val
if key == 'rot90': b_rot90 = val
str_subDir = ''
if b_makeSubDir:
str_subDir = str_dim
misc.mkdir('%s/%s' % (self._str_outputDir, str_subDir))
if str_dim == 'x':
if indexStart == 0 and indexStop == -1:
indexStop = dims[0]
for i in range(indexStart, indexStop):
self._Mnp_2Dslice = self._Vnp_3DVol[i, :, :]
if b_rot90: self._Mnp_2Dslice = np.rot90(self._Mnp_2Dslice)
self.dim_sliceSave(index=i, subDir=str_subDir)
if str_dim == 'y':
if indexStart == 0 and indexStop == -1:
indexStop = dims[1]
for j in range(indexStart, indexStop):
self._Mnp_2Dslice = self._Vnp_3DVol[:, j, :]
if b_rot90: self._Mnp_2Dslice = np.rot90(self._Mnp_2Dslice)
self.dim_sliceSave(index=j, subDir=str_subDir)
if str_dim == 'z':
if indexStart == 0 and indexStop == -1:
indexStop = dims[2]
for k in range(indexStart, indexStop):
self._Mnp_2Dslice = self._Vnp_3DVol[:, :, k]
if b_rot90: self._Mnp_2Dslice = np.rot90(self._Mnp_2Dslice)
self.dim_sliceSave(index=k, subDir=str_subDir)
def run(self):
'''
Runs the DICOM header tag to index.html class.
'''
misc.mkdir(self._str_outputDir)
f = open('%s/%s' % (self._str_outputDir, self._str_outputFile), 'w')
dicomTag.run(self)
htmlPage = '''
<!DOCTYPE html>
<html>
<head>
<title>DCM tags: %s</title>
</head>
<body>
<pre>
%s
</pre>
</body>
</html> ''' % (self._str_inputFile, self._strRaw)
print(htmlPage, file=f)
def run(self):
'''
Runs the DICOM header tag to index.html class.
'''
misc.mkdir(self._str_outputDir)
f = open('%s/%s' % (self._str_outputDir, self._str_outputFile), 'w')
dicomTag.run(self)
htmlPage = '''
<!DOCTYPE html>
<html>
<head>
<title>DCM tags: %s</title>
</head>
<body>
<pre>
%s
</pre>
</body>
</html> ''' % (self._str_inputFile, self._strRaw)
print(htmlPage, file=f)
def f_stage4callback(**kwargs):
str_cwd = os.getcwd()
lst_subj = []
for key, val in kwargs.iteritems():
if key == 'subj': lst_subj = val
if key == 'obj': stage = val
for subj in lst_subj:
# find the relevant input files in each <subj> dir
_str_outDir = 'outDir'
misc.mkdir(_str_outDir)
os.chdir("%s/outDir" % subj)
log = stage.log()
log('Scheduling MatLAB basac analysis for subject "%s"...\n' % (subj))
str_cmd = 'eval "/chb/pices/arch/x86_64-Linux/bin/matlab -nodesktop -nosplash -nojvm -r \\\"c = basac_drive(\'%s\'); exit\\\"" |tee basac_process.log' % (
os.getcwd()
)
cluster = crun.crun()
cluster.echo(False)
cluster.echoStdOut(False)
cluster.detach(False)
cluster(str_cmd, waitForChild=True, stdoutflush=True, stderrflush=True)
os.chdir(str_cwd)
return True
def f_stage0callback(**kwargs):
'''
STAGE 0
-------
Build output directory trees for the analysis.
'''
str_cwd = os.getcwd()
for key, val in kwargs.iteritems():
if key == 'obj': stage = val
if key == 'pipe': pipeline = val
log = stage.log()
b_alreadyResampled = False
b_outAnnotDirExist = False
for pipeline._str_annotation in pipeline.l_annotation():
for pipeline._str_subsample in pipeline.l_subsample():
b_parentContainsSamples = False
str_outDir = "%s%s/groupCurvAnalysis/%s" % \
( pipeline.outDir(),
pipeline._str_subsample,
pipeline._str_annotation )
str_outParentDir = "/".join(str_outDir.split('/')[0:-2])
log('Building output tree for "%s", annotation "%s"\n' % \
( str_outParentDir,
pipeline._str_annotation))
b_outAnnotDirExist = os.path.isdir(str_outDir)
if not b_outAnnotDirExist:
misc.mkdir(str_outDir)
# Check if outParentDir contains samples
l_numer = l_filterNumeric(os.listdir(str_outParentDir))
if len(l_numer): b_parentContainsSamples = True
stage.exitCode(0)
return True
def initialize(self):
'''
This method provides some "post-constructor" initialization. It is
typically called after the constructor and after other class flags
have been set (or reset).
'''
# Set the stages
self._pipeline.stages_canRun(False)
lst_stages = list(self._stageslist)
for index in lst_stages:
stage = self._pipeline.stage_get(int(index))
stage.canRun(True)
# Set absolute dir specs for topDir and outDir
os.chdir(self.topDir())
self.topDir(os.path.abspath(self.topDir()))
if os.path.isdir(self.outDir()):
os.chdir(self.outDir())
self.outDir(os.path.abspath(self.outDir()))
else:
error.warn(self, 'outDirNotFound')
misc.mkdir(self.outDir())
def f_stage1callback(**kwargs):
for key, val in kwargs.iteritems():
if key == 'obj': stage = val
if key == 'pipe': pipeline = val
log = stage.log()
lst_subj = pipeline.l_subj()
os.chdir(pipeline.outDir())
misc.mkdir('groupCurvAnalysis')
os.chdir('groupCurvAnalysis')
misc.mkdir(pipeline.annotationDir())
os.chdir(pipeline.dirSpecAnnot(base='orig'))
for bashFile in glob.glob(r'*.bash'):
shutil.copy(bashFile, pipeline.dirSpecAnnot(base='rsampled'))
for lstFile in glob.glob(r'*.lst'):
shutil.copy(lstFile, pipeline.dirSpecAnnot(base='rsampled'))
str_CMDoriginalROI = "find . -maxdepth 1 -mindepth 1 -type d | grep -v ROItag | awk -F\/ '{print $2}'"
pipeline.l_ROI(OSshell(str_CMDoriginalROI)[0].strip().split('\n'))
lst_ROI = pipeline.l_ROI()
os.chdir(pipeline.dirSpecAnnot(base='rsampled'))
# print(os.getcwd())
total = 0
for pipeline._str_ROI in lst_ROI:
os.chdir(pipeline.dirSpecAnnot(base='rsampled'))
log('Creating ROI dir %s\n' % (pipeline._str_ROI))
misc.mkdir(pipeline._str_ROI)
os.chdir(pipeline._str_ROI)
tagCentroidCMD = 'ls %s/%s/*centroid*txt' % (pipeline.dirSpecAnnot(
base='orig'), pipeline._str_ROI)
pipeline.l_centroidTXT(
OSshell(tagCentroidCMD)[0].strip().split('\n'))
for pipeline._str_centroidTXT in pipeline.l_centroidTXT():
log('\tCopying original sample %s\n' %
os.path.basename(pipeline._str_centroidTXT))
shutil.copy(
pipeline._str_centroidTXT,
os.path.join(pipeline.outDir(), 'groupCurvAnalysis',
pipeline.annotationDir(), pipeline._str_ROI))
total += 1
stage.exitCode(0)
return True
else:
v_ind = reltran/v_reltranScale + \
v_indoffset - v_nonBaseOffset
M_pval[v_ind[0],v_ind[1]] = f_pvalMin
M_pvalmNorm[v_ind[0],v_ind[1]] = f_pvalmNorm
M_pvalvNorm[v_ind[0],v_ind[1]] = f_pvalvNorm
print("\tmin p-val for comparison between group '%s' and '%s' is %f" % \
(l_cloudFile[g1], l_cloudFile[g2], f_pvalMin))
print("\tnorm p-val for comparison between group '%s' and '%s' is %f" % \
(l_cloudFile[g1], l_cloudFile[g2], f_pvalmNorm))
print("\tp-val for comparison between normed groups '%s' and '%s' is %f" % \
(l_cloudFile[g1], l_cloudFile[g2], f_pvalvNorm))
if Gb_saveFig:
print("\tsaving figure '%s'..." % _str_title)
misc.mkdir(_str_title)
#aspectRatio_square(aspect=1)
savefig('%s/%s.pdf' % (_str_title, _str_title), bbox_inches=0)
savefig('%s/%s.png' % (_str_title, _str_title), bbox_inches=0)
# Save pval matrices on each loop... allows for some data storage
# even while processing is incomplete.
np.savetxt('%s/%s-pval.txt' % (_str_title, _str_title), M_pval, fmt='%10.7f')
np.savetxt('%s/%s-pvalmNorm.txt' % (_str_title, _str_title), M_pvalmNorm, fmt='%10.7f')
np.savetxt('%s/%s-pvalvNorm.txt' % (_str_title, _str_title), M_pvalvNorm, fmt='%10.7f')
else:
if Gb_saveFig:
_str_title = '%s' % (
os.path.splitext(os.path.basename(l_cloudFile[0]))[0],
)
if Gb_titlePrint: title(_str_title)
misc.mkdir(_str_title)
