def test_pkg_info():
"""Smoke test nibabel.get_info()
Hits:
- nibabel.get_info
- nibabel.pkg_info.get_pkg_info
- nibabel.pkg_info.pkg_commit_hash
"""
info = nib.get_info()
def test_pkg_info():
"""Simple smoke test
Hits:
- nibabel.get_info
- nibabel.pkg_info.get_pkg_info
- nibabel.pkg_info.pkg_commit_hash
"""
info = nib.get_info()
#===============================================================================
sTime = time.time()
waveName = 'coif1';
waveLevel = 5
InputFileName = os.path.basename(niftiFileDir)
(InputFileDir, InputFileName) = os.path.split(niftiFileDir)
InputfileBaseName = fStripExtension( InputFileName )
#print InputFileName, InputfileBaseName, InputFileDir
nimBabel = nib.load(niftiFileDir)
nimBabelData = nimBabel.get_data()
nimBabelInfo = nib.get_info()
nimBabelAffine = nimBabel.get_affine()
nimBabelHeader = nimBabel.get_header().structarr
nimBabelPixDim = nimBabelHeader['pixdim']
numpyBabelDataSz = numpy.asarray(nimBabelData.shape)
if len(numpyBabelDataSz) <= 3:
print 'ERROR: Wrong dim size input...'
exit -1
#VoxelSD = scipy.std( nimBabelData, axis=3 )
#frameRMS = list()
#frameRMS_MM = list()
#frameSD = list()
nStats = 6
fileID.write('%.8f' % inputData[2, i] + "\n")
#===============================================================================
sTime = time.time()
InputFileName = os.path.basename(niftiFileDir)
(InputFileDir, InputFileName) = os.path.split(niftiFileDir)
InputfileBaseName = fStripExtension(InputFileName)
#print InputFileName, InputfileBaseName, InputFileDir
nimBabel = nib.load(niftiFileDir)
nimBabelData = nimBabel.get_data()
nimBabelInfo = nib.get_info()
nimBabelAffine = nimBabel.get_affine()
nimBabelHeader = nimBabel.get_header().structarr
nimBabelPixDim = nimBabelHeader['pixdim']
numpyBabelDataSz = numpy.asarray(nimBabelData.shape)
if len(numpyBabelDataSz) <= 3:
print 'ERROR: Wrong dim size input...'
exit - 1
# Temporal SNR in brain mask
# Simple SNR (mean/SNR)
# of frames greater than .5 from motion outliers in FLS
# of frames with DVARs above 0.5
# of frames with DVARs above 0.7
# of frames with rms/mm frame above .2
# read the nifti file...
#===============================================================================
if (niftiDir[-1] != os.sep):
niftiDir = niftiDir + os.sep
if (outputDir[-1] != os.sep):
outputDir = outputDir + os.sep
InputFileBase = dwiFile.split('.')[0]
dwiDirFile = os.path.normpath(niftiDir +os.sep+ dwiFile)
print "Nifti File: " + dwiDirFile
nibDWI = nib.load(dwiDirFile)
nibDWIData = nibDWI.get_data()
nibDWIInfo = nib.get_info()
nibDWIAffine = nibDWI.get_affine()
nibDWIHeader = nibDWI.get_header().structarr
nibDWIPixDim = nibDWIHeader['pixdim']
nibDWIDataSz = numpy.asarray(nibDWIData.shape)
print nibDWIDataSz
#===============================================================================
# read the bval file...
#===============================================================================
if bvalsFile:
bvalsFile = os.path.normpath(niftiDir +os.sep+ bvalsFile)
else:
bvalsFile = os.path.normpath(niftiDir +os.sep+ InputFileBase + '.bval')
print 'Bvals File: %s' % bvalsFile
# read the nifti file...
#===============================================================================
if (niftiDir[-1] != os.sep):
niftiDir = niftiDir + os.sep
if (outputDir[-1] != os.sep):
outputDir = outputDir + os.sep
InputFileBase = dwiFile.split('.')[0]
dwiDirFile = os.path.normpath(niftiDir + os.sep + dwiFile)
print "Nifti File: " + dwiDirFile
nibDWI = nib.load(dwiDirFile)
nibDWIData = nibDWI.get_data()
nibDWIInfo = nib.get_info()
nibDWIAffine = nibDWI.get_affine()
nibDWIHeader = nibDWI.get_header().structarr
nibDWIPixDim = nibDWIHeader['pixdim']
nibDWIDataSz = numpy.asarray(nibDWIData.shape)
print nibDWIDataSz
#===============================================================================
# read the bval file...
#===============================================================================
if bvalsFile:
bvalsFile = os.path.normpath(niftiDir + os.sep + bvalsFile)
else:
bvalsFile = os.path.normpath(niftiDir + os.sep + InputFileBase + '.bval')
print 'Bvals File: %s' % bvalsFile
