b9aac6f4f32d755595c577c5fc5ac0936a914031,doc/examples/reconst_csd.py,,,#,32

Before Change

fetch_stanford_hardi()
img, gtab = read_stanford_hardi()

data = img.get_data()


You can verify the b-values of the dataset by looking at the attribute
``gtab.bvals``. Now that a datasets with multiple gradient directions is

After Change

from dipy.io.gradients import read_bvals_bvecs
from dipy.io.image import load_nifti

hardi_fname, hardi_bval, hardi_bvec = get_fnames("stanford_hardi")

data, affine = load_nifti(hardi_fname)

bvals, bvecs = read_bvals_bvecs(hardi_bval, hardi_bvec)

Instances