def __init__(self, space, data, forward=None):
self.space = space
self.image_space = self.space[0]
self.affine_space = self.space[1]
self.rest_space = self.space[2]
self.deformation_space = ProductSpace(self.affine_space,
self.rest_space)
self.data = data
if forward is None:
self.forward = IdentityOperator(self.image_space)
else:
self.forward = forward
self.datafit = 0.5 * L2NormSquared(self.image_space).translated(
self.data)
self.embedding_affine_rest = ops.Embedding_Affine_Rest(
self.deformation_space, self.image_space.tangent_bundle)
self.embedding_affine = ops.Embedding_Affine(
self.affine_space, self.image_space.tangent_bundle)
super(DataFitL2DispAffRest, self).__init__(space=space,
linear=False,
grad_lipschitz=np.nan)
def __init__(self, space, datafit, forward=None):
self.space = space
self.image_space = self.space[0]
self.affine_space = self.space[1]
if forward is None:
self.forward = IdentityOperator(self.image_space)
else:
self.forward = forward
self.datafit = datafit
if isinstance(self.image_space, odl.ProductSpace):
tangent_bundle = self.image_space[0].tangent_bundle
else:
tangent_bundle = self.image_space.tangent_bundle
self.embedding = ops.Embedding_Affine(self.affine_space,
tangent_bundle)
super(DataFitDisp, self).__init__(space=space,
linear=False,
grad_lipschitz=np.nan)
niter=None,
callback=cb,
L=[1e2, 1e4],
tol=tol)
niter_diff = [niter[0]] + list(np.diff(niter))
clim = [0, 1]
proj = odl.solvers.IndicatorBox(X_res,
lower=clim[0],
upper=clim[1]).proximal(1)
for ni, nid in zip(niter, niter_diff):
recon.run(nid)
vf = ops.Embedding_Affine(Yaff, V_plot)(recon.x[1])
plt.quiver(x, y, vf[0], vf[1], color='red'),
plt.axis('equal'),
plt.axis([-1.3, 1.3, -1.3, 1.3]),
# plt.axis('off'),
plt.gca().set_aspect('equal', adjustable='box'),
if save2Disk is True:
file_out_ni = '{}_{:04d}'.format(file_out, ni)
file_out_def_ni = '{}_def_{:04d}'.format(file_out, ni)
plt.savefig(folder_out + '/' + file_out_def_ni +
'.png',
bbox_inches='tight',
pad_inches=0,
transparent=True,
dpi=600,
format='png')