def test_syn_registration():
with nbtmp.InTemporaryDirectory() as tmpdir:
warped_moving, mapping = syn_registration(subset_b0,
subset_t2,
moving_affine=hardi_affine,
static_affine=MNI_T2_affine,
step_length=0.1,
metric='CC',
dim=3,
level_iters=[5, 5, 5],
sigma_diff=2.0,
radius=1,
prealign=None)
npt.assert_equal(warped_moving.shape, subset_t2.shape)
mapping_fname = op.join(tmpdir, 'mapping.nii.gz')
write_mapping(mapping, mapping_fname)
file_mapping = read_mapping(mapping_fname,
subset_b0_img,
subset_t2_img)
# Test that it has the same effect on the data:
warped_from_file = file_mapping.transform(subset_b0)
npt.assert_equal(warped_from_file, warped_moving)
# Test that it is, attribute by attribute, identical:
for k in mapping.__dict__:
npt.assert_((np.all(mapping.__getattribute__(k) ==
file_mapping.__getattribute__(k))))
def gen_mapping(self, subses_dict, reg_subject, reg_template, subject_sls,
template_sls, reg_prealign):
_, mapping = syn_registration(reg_subject.get_fdata(),
reg_template.get_fdata(),
moving_affine=reg_subject.affine,
static_affine=reg_template.affine,
prealign=reg_prealign,
**self.syn_kwargs)
if self.use_prealign:
mapping.codomain_world2grid = np.linalg.inv(reg_prealign)
return mapping
def syn_register_dwi(dwi, gtab, template=None, **syn_kwargs):
"""
Register DWI data to a template.
Parameters
-----------
dwi : nifti image or str
Image containing DWI data, or full path to a nifti file with DWI.
gtab : GradientTable or list of strings
The gradients associated with the DWI data, or a string with [fbcal, ]
template : nifti image or str, optional
syn_kwargs : key-word arguments for :func:`syn_registration`
Returns
-------
DiffeomorphicMap object
"""
if template is None:
import AFQ.data as afd
template = afd.read_mni_template()
if isinstance(template, str):
template = nib.load(template)
template_data = template.get_fdata()
template_affine = template.affine
if isinstance(dwi, str):
dwi = nib.load(dwi)
if not isinstance(gtab, dpg.GradientTable):
gtab = dpg.gradient_table(*gtab)
dwi_affine = dwi.affine
dwi_data = dwi.get_fdata()
mean_b0 = np.mean(dwi_data[..., gtab.b0s_mask], -1)
warped_b0, mapping = syn_registration(mean_b0,
template_data,
moving_affine=dwi_affine,
static_affine=template_affine,
**syn_kwargs)
return warped_b0, mapping