def test_rsquared():
ii = ozm.rsquared(TM1, TM2)
# Test for regression:
npt.assert_almost_equal(ii,
np.array([[[ 0.41738295, 0.5686638 , 0.66632678, 0.66796424],
[ 0.55782746, 0.52997752, 0.65248008, 0.79295422]],
[[ 0.49519897, 0.52195252, 0.70362685, 0.62545745],
[ 0.43410031, 0.56910023, 0.76395852, 0.73071651]],
[[ 0.50371373, 0.56810418, 0.53169063, 0.60985997],
[ 0.53667339, 0.69261167, 0.70018453, 0.63229423]]]))
help='Bvals file (FSL format)')
parser.add_argument('out_file', action='store', metavar='File',
help='Output file name (.nii.gz)')
parser.add_argument('--mask_file', action='store', metavar='File',
help='Mask file (only the voxels within the binary mask will be analyzed (.nii.gz; default: analyze all) ',
default=None)
params = parser.parse_args()
if __name__ == "__main__":
Model1 = dti.TensorModel(params.dwi_file1,
params.bvecs_file1,
params.bvals_file1,
mask=params.mask_file,
params_file='temp')
Model2 = dti.TensorModel(params.dwi_file2,
params.bvecs_file2,
params.bvals_file2,
mask=params.mask_file,
params_file='temp')
# Do it and save:
nib.Nifti1Image(ana.rsquared(Model1, Model2),
Model1.affine).to_filename(params.out_file)
metavar='File',
help='Output file name (.nii.gz)')
parser.add_argument(
'--mask_file',
action='store',
metavar='File',
help=
'Mask file (only the voxels within the binary mask will be analyzed (.nii.gz; default: analyze all) ',
default=None)
params = parser.parse_args()
if __name__ == "__main__":
Model1 = dti.TensorModel(params.dwi_file1,
params.bvecs_file1,
params.bvals_file1,
mask=params.mask_file,
params_file='temp')
Model2 = dti.TensorModel(params.dwi_file2,
params.bvecs_file2,
params.bvals_file2,
mask=params.mask_file,
params_file='temp')
# Do it and save:
nib.Nifti1Image(ana.rsquared(Model1, Model2),
Model1.affine).to_filename(params.out_file)
