def tractography_from_trackvis_file(filename):
tracts_and_data, header = trackvis.read(filename, points_space='rasmm')
tracts, scalars, properties = izip(*tracts_and_data)
scalar_names = [n for n in header['scalar_name'] if len(n) > 0]
#scalar_names_unique = []
#scalar_names_subcomp = {}
#for sn in scalar_names:
# if re.match('.*_[0-9]{2}', sn):
# prefix = sn[:sn.rfind('_')]
# if prefix not in scalar_names_unique:
# scalar_names_unique.append(prefix)
# scalar_names_subcomp[prefix] = int(sn[-2:])
# scalar_names_subcomp[prefix] = max(sn[-2:], scalar_names_subcomp[prefix])
# else:
# scalar_names_unique.append(sn)
tracts_data = {}
for i, sn in enumerate(scalar_names):
tracts_data[sn] = [scalar[:, i][:, None] for scalar in scalars]
affine = header['vox_to_ras']
image_dims = header['dim']
tr = Tractography(tracts, tracts_data)
tr.affine = affine
tr.image_dims = image_dims
return tr
