Recipes

How do I do X in DIPY? This page contains a collection of recipes that will help you quickly resolve common basic/advanced operation. If you have a question that is not answered here, please ask on the dipy discussions or even better, answer it yourself and contribute to the documentation!

How do I convert my tractograms?

We recommend to look at the tutorials Streamline File Formats

from dipy.io.streamline import load_tractogram, save_tractogram

# convert from fib to trk
my_fib_file_path = '/<my_folder>/<my_path>/my_tractogram.fib'
my_trk_file_path = '/<my_folder>/<my_path>/my_tractogram.trk'
my_trk = load_tractogram(my_fib_file_path, 'same')
save_tractogram(my_trk.streamlines, my_trk_file_path, 'same')

How do I convert my Spherical Harmonics from MRTRIX3 to DIPY?

Available from DIPY 1.9.0+. See this thread for more information.

from dipy.reconst.shm import convert_sh_descoteaux_tournier
convert_sh_descoteaux_tournier(sh_coeffs)

How do I convert my tensors from FSL to DIPY or MRTRIX3 to DIPY?

Available with DIPY 1.9.0+

from dipy.reconst.utils import convert_tensors
from dipy.io.image import load_nifti, save_nifti

data, affine, img = load_nifti('my_data.nii.gz', return_img=True)
# convert from FSL to DIPY
otensor = convert_tensors(data, 'fsl', 'dipy')
save_nifti(otensor, data, affine, image.header)
# convert from MRTRIX3 to DIPY
otensor = convert_tensors(data, 'mrtrix', 'dipy')
save_nifti(otensor, data, affine, image.header)

How do I save/read the output fields from the Symmetric Diffeomorphic Registration?

The mapping fields is saved in a Nifti file. The data in the file is organized with shape (X, Y, Z, 3, 2), such that the forward mapping in each voxel is in data[i, j, k, :, 0] and the backward mapping in each voxel is in data[i, j, k, :, 1].

The output fields from the Symmetric Diffeomorphic Registration can be saved and read using the functions write_mapping and read_mapping respectively.

from dipy.align import read_mapping, write_mapping
from dipy.align.imwarp import DiffeomorphicMap, SymmetricDiffeomorphicRegistration

# Load your static and moving images and setup the registration parameters.
# Then apply the registration

sdr = SymmetricDiffeomorphicRegistration(metric, level_iters)
mapping = sdr.optimize(static, moving)

# Save the mapping
write_mapping(mapping,'outputField.nii.gz')

# If you need to read the mapping back
mapping = read_mapping('outputField.nii.gz', static_filename, moving_filename)