def test_plot_2d_diffeomorphic_map():
# Test the regtools plotting interface (lightly).
mv_shape = (11, 12)
moving = np.random.rand(*mv_shape)
st_shape = (13, 14)
static = np.random.rand(*st_shape)
dim = static.ndim
metric = SSDMetric(dim)
level_iters = [200, 100, 50, 25]
sdr = SymmetricDiffeomorphicRegistration(metric,
level_iters,
inv_iter=50)
mapping = sdr.optimize(static, moving)
# Smoke testing of plots
ff = regtools.plot_2d_diffeomorphic_map(mapping, 10)
# Defualt shape is static shape, moving shape
npt.assert_equal(ff[0].shape, st_shape)
npt.assert_equal(ff[1].shape, mv_shape)
# Can specify shape
ff = regtools.plot_2d_diffeomorphic_map(mapping,
delta = 10,
direct_grid_shape=(7, 8),
inverse_grid_shape=(9, 10))
npt.assert_equal(ff[0].shape, (7, 8))
npt.assert_equal(ff[1].shape, (9, 10))
sdr = SymmetricDiffeomorphicRegistration(metric=SSDMetric(img_ref.ndim),
step_length=1.0,
level_iters=[50, 100],
inv_iter=50,
ss_sigma_factor=0.1,
opt_tol=1.e-3)
"""
Perform the registration with equal images.
"""
mapping = sdr.optimize(img_ref.astype(float), img_ref.astype(float))
img_warp = mapping.transform(img_ref, 'linear')
show_images(img_ref, img_warp, 'output-0')
regtools.plot_2d_diffeomorphic_map(mapping, 5, 'map-0.png')
"""
.. figure:: output-0.png
:align: center
.. figure:: map-0.png
:align: center
Registration results for default parameters and equal images.
"""
"""
Perform the registration with binary and fuzzy images.
"""
mapping = sdr.optimize(img_ref.astype(float), img_in.astype(float))
"""
sdr = SymmetricDiffeomorphicRegistration(metric=SSDMetric(img_ref.ndim),
step_length=1.0,
level_iters=[50, 100],
inv_iter=50,
ss_sigma_factor=0.1,
opt_tol=1.e-3)
"""
Perform the registration with equal images.
"""
mapping = sdr.optimize(img_ref.astype(float), img_ref.astype(float))
img_warp = mapping.transform(img_ref, 'linear')
show_images(img_ref, img_warp, 'output-0')
regtools.plot_2d_diffeomorphic_map(mapping, 5, 'map-0.png')
"""
.. figure:: output-0.png
:align: center
.. figure:: map-0.png
:align: center
Registration results for default parameters and equal images.
"""
"""
Perform the registration with binary and fuzzy images.
"""
mapping = sdr.optimize(img_ref.astype(float), img_in.astype(float))
img_warp = mapping.transform(img_in, 'linear')
show_images(img_ref, img_warp, 'output-1')
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters, inv_iter = 50) """ Now we execute the optimization, which returns a DiffeomorphicMap object, that can be used to register images back and forth between the static and moving domains """ mapping = sdr.optimize(static, moving) """ It is a good idea to visualize the resulting deformation map to make sure the result is reasonable (at least, visually) """ regtools.plot_2d_diffeomorphic_map(mapping, 10, 'diffeomorphic_map.png') """ .. figure:: diffeomorphic_map.png :align: center Deformed lattice under the resulting diffeomorphic map. """ """ Now let's warp the moving image and see if it gets similar to the static image """ warped_moving = mapping.transform(moving, 'linear') regtools.overlay_images(static, warped_moving, 'Static','Overlay','Warped moving', 'direct_warp_result.png')
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters, inv_iter = 50) """ Now we execute the optimization, which returns a DiffeomorphicMap object, that can be used to register images back and forth between the static and moving domains """ mapping = sdr.optimize(static, moving) """ It is a good idea to visualize the resulting deformation map to make sure the result is reasonable (at least, visually) """ regtools.plot_2d_diffeomorphic_map(mapping, 10, 'diffeomorphic_map.png') """ .. figure:: diffeomorphic_map.png :align: center Deformed lattice under the resulting diffeomorphic map. """ """ Now let's warp the moving image and see if it gets similar to the static image """ warped_moving = mapping.transform(moving, 'linear') regtools.overlay_images(static, warped_moving, 'Static','Overlay','Warped moving', 'direct_warp_result.png')
