def test_interpolate_displacement_field(args=None):
shape = (10, 5)
test_img = np.random.rand(*shape)
subsample = 3
voxel_size = (3.0, 2.5)
jitter_sigma = (5.0, ) * len(shape)
jitter_sigma_voxels = tuple(j / vs
for j, vs in zip(jitter_sigma, voxel_size))
identity = augment.create_identity_transformation(shape=shape,
subsample=subsample)
np.random.seed(100)
elastic = augment.create_elastic_transformation(
shape=shape,
control_point_spacing=(1, 1),
jitter_sigma=jitter_sigma_voxels,
subsample=subsample)
np.random.seed(100)
elastic_w = augment.create_elastic_transformation(
shape=shape,
control_point_spacing=(1, 1),
jitter_sigma=jitter_sigma,
subsample=subsample)
transform = identity + elastic
print(transform)
print('-----')
print(elastic)
print(elastic_w)
print(elastic_w / elastic)
displacement = augment.upscale_transformation(elastic, shape)
transform = augment.upscale_transformation(transform, shape)
displace_w = augment.upscale_transformation(elastic_w, shape)
tf1 = transform
tf2 = displacement + augment.create_identity_transformation(shape=shape,
subsample=1)
print()
print('-----')
print(tf1)
print('-----')
print(tf2)
d1 = transform - augment.create_identity_transformation(shape=shape,
subsample=1)
d2 = displacement
print()
print('-----')
print(d1)
print('-----')
print(d2)
print(np.abs(tf1 - tf2))
def _create_rotation_transformation(shape, angle, subsample=1, voxel_size=None):
dims = len(shape)
subsample_shape = tuple(max(1,int(s/subsample)) for s in shape)
control_points = (2,)*dims
if voxel_size is None:
voxel_size = Coordinate((1,) * dims)
# map control points to world coordinates
control_point_scaling_factor = tuple(float(s-1) * vs for s, vs in zip(shape, voxel_size))
# rotate control points
center = np.array([0.5*(d-1)*vs for d, vs in zip(shape, voxel_size)])
# print("Creating rotation transformation with:")
# print("\tangle : " + str(angle))
# print("\tcenter: " + str(center))
control_point_offsets = np.zeros((dims,) + control_points, dtype=np.float32)
for control_point in np.ndindex(control_points):
point = np.array(control_point)*control_point_scaling_factor
center_offset = np.array([p-c for c,p in zip(center, point)], dtype=np.float32)
rotated_offset = np.array(center_offset)
rotated_offset[-2:] = _rotate(center_offset[-2:], angle)
displacement = rotated_offset - center_offset
control_point_offsets[(slice(None),) + control_point] += displacement
return augment.upscale_transformation(control_point_offsets, subsample_shape)
shape=shape,
control_point_spacing=(1, 1),
jitter_sigma=jitter_sigma_voxels,
subsample=subsample)
np.random.seed(100)
elastic_w = augment.create_elastic_transformation(shape=shape,
control_point_spacing=(1, 1),
jitter_sigma=jitter_sigma,
subsample=subsample)
transform = identity + elastic
print(transform)
print('-----')
print(elastic)
print(elastic_w)
print(elastic_w / elastic)
displacement = augment.upscale_transformation(elastic, shape)
transform = augment.upscale_transformation(transform, shape)
displace_w = augment.upscale_transformation(elastic_w, shape)
tf1 = transform
tf2 = displacement + augment.create_identity_transformation(shape=shape,
subsample=1)
print()
print('-----')
print(tf1)
print('-----')
print(tf2)
d1 = transform - augment.create_identity_transformation(shape=shape,
subsample=1)