def test_transfo_skip_pix2phys():
# "Recipe" useful if you want to skip pix2phys, which is *not* a good idea
dir_tmp = "."
print("Achieving a shifting of +1,+1,+1 (in LPI)")
print(" Create data")
path_src = "warp-src.nii"
img_src = fake_3dimage_sct().save(path_src)
print(" Create a warping field" \
"""
Now we want to shift things by (+1,+1,+1), meaning
that a destination voxel at position (x_1, y_1, z_1)
contains the stuff that was in the source voxel at position
(x_1-1, y_1-1, z_1-1).
""")
shape = tuple(list(img_src.data.shape) + [1,3])
data = np.ones(shape, order="F")
data[...,2] *= -1 # invert Z so that the result is what we expect
# See test_transfo_exhaustive_wrt_orientations()
path_warp = "warp-field111.nii"
img_warp = fake_image_sct_custom(data)
img_warp.header.set_intent('vector', (), '')
img_warp.save(path_warp)
path_dst = "warp-dst111.nii"
xform = sct_apply_transfo.Transform(path_src, path_warp, path_src, path_dst)
xform.apply()
img_src2 = msct_image.Image(path_src)
img_dst = msct_image.Image(path_dst)
print(" Check that the source wasn't altered")
assert (img_src.data == img_src2.data).all()
assert img_src.orientation == img_dst.orientation
assert img_src.data.shape == img_dst.data.shape
print(" Check the contents")
dat_src = img_src.data
dat_dst = np.array(img_dst.data)
if 0:
for idx_slice in range(shape[2]):
print("")
print(dat_src[...,idx_slice])
print(dat_dst[...,idx_slice])
# The volume should be shifted by 1 and the "lowest faces" of the destination
# should be empty
assert np.allclose(dat_dst[0,:,:], 0)
assert np.allclose(dat_dst[:,0,:], 0)
assert np.allclose(dat_dst[:,:,0], 0)
assert np.allclose(dat_src[:-1,:-1,:-1], dat_dst[1:,1:,1:])
def test_transfo_null():
dir_tmp = "."
print("Null warping field")
print(" Create some recognizable data")
data = np.ones((7, 8, 9), order="F")
path_src = "warp-src.nii"
img_src = fake_image_sct_custom(data).save(path_src)
print(" Create a null warping field")
data = np.zeros((7, 8, 9, 1, 3), order="F")
path_warp = "warp-field.nii"
img_warp = fake_image_sct_custom(data)
img_warp.header.set_intent('vector', (), '')
img_warp.save(path_warp)
print(" Apply")
path_dst = "warp-dst.nii"
xform = sct_apply_transfo.Transform(input_filename=path_src,
fname_dest=path_src,
list_warp=[path_warp],
output_filename=path_dst)
xform.apply()
img_src2 = msct_image.Image(path_src)
img_dst = msct_image.Image(path_dst)
print(" Check that the source wasn't altered")
assert (img_src.data == img_src2.data).all()
assert img_src.orientation == img_dst.orientation
assert img_src.data.shape == img_dst.data.shape
print(
" Check that the destination is identical to the source since the field was null"
)
dat_src = img_src.data
dat_dst = np.array(img_dst.data)
for idx_slice, (slice_src, slice_dst) in enumerate(
msct_image.SlicerMany((img_src, img_dst), msct_image.Slicer)):
slice_src = np.array(slice_src)
slice_dst = np.array(slice_dst)
print(slice_src)
print(slice_dst)
assert np.allclose(slice_src, slice_dst)
assert np.allclose(dat_src, dat_dst)
def notest_transfo_more_exhaustive_wrt_orientations():
dir_tmp = "."
print("Figuring out which orientations work without workaround")
all_orientations = msct_image.all_refspace_strings()
orientations_ok = []
orientations_ng = []
orientations_dk = []
for orientation_src in all_orientations:
for orientation_ref in all_orientations:
shift = np.array([1,2,3])
shift_wanted = shift.copy()
shift[2] *= -1 # ANTs / ITK reference frame is LPS, ours is LPI
# (see docs or test_transfo_figure_out_ants_frame_exhaustive())
print(" Shifting {} in {} ref {}".format(shift_wanted, orientation_src, orientation_ref))
path_src = "warp2-{}.nii".format(orientation_src)
img_src = fake_3dimage_sct().change_orientation(orientation_src).save(path_src)
path_ref = "warp2-{}.nii".format(orientation_ref)
img_ref = fake_3dimage_sct().change_orientation(orientation_ref).save(path_ref)
# Create warping field
shape = tuple(list(img_src.data.shape) + [1,3])
data = np.zeros(shape, order="F")
data[:,:,:,0] = shift
path_warp = "warp-{}-{}-field.nii".format(orientation_src, orientation_ref)
img_warp = fake_image_sct_custom(data)
img_warp.header.set_intent('vector', (), '')
img_warp.change_orientation(orientation_ref).save(path_warp)
#print(" Affine:\n{}".format(img_warp.header.get_best_affine()))
path_dst = "warp-{}-{}-dst.nii".format(orientation_src, orientation_ref)
xform = sct_apply_transfo.Transform(path_src, path_warp, path_ref, path_dst)
xform.apply()
img_src2 = msct_image.Image(path_src)
img_dst = msct_image.Image(path_dst)
assert img_ref.orientation == img_dst.orientation
assert img_ref.data.shape == img_dst.data.shape
dat_src = img_src.data
dat_dst = np.array(img_dst.data)
value = 50505
aff_src = img_src.header.get_best_affine()
aff_dst = img_dst.header.get_best_affine()
pt_src = np.argwhere(dat_src == value)[0]
try:
pt_dst = np.argwhere(dat_dst == value)[0]
1/0
except:
# Work around numerical inaccuracy, that is somehow introduced by ANTs
min_ = np.round(np.min(np.abs(dat_dst - value)), 1)
pt_dst = np.array(np.unravel_index(np.argmin(np.abs(dat_dst - value)), dat_dst.shape))#, order="F"))
print(" Point %s -> %s (%s) %s" % (pt_src, pt_dst, dat_dst[tuple(pt_dst)], min_))
if min_ != 0:
orientations_dk.append((orientation_src, orientation_ref))
continue
pos_src = np.matmul(aff_src, np.hstack((pt_src, [1])).reshape((4,1)))
pos_dst = np.matmul(aff_dst, np.hstack((pt_dst, [1])).reshape((4,1)))
displacement = (pos_dst - pos_src).reshape((-1))[:3]
displacement_log = pt_dst - pt_src
#print(" Displacement (logical): %s" % (displacement_log))
if not np.allclose(displacement, shift_wanted):
orientations_ng.append((orientation_src, orientation_ref))
print(" \x1B[31;1mDisplacement (physical): %s\x1B[0m" % (displacement))
else:
orientations_ok.append((orientation_src, orientation_ref))
print(" Displacement (physical): %s" % (displacement))
print("")
def ori_str(x):
return " ".join(["{}->{}".format(x,y) for (x,y) in x])
print("Orientations OK: {}".format(ori_str(orientations_ok)))
print("Orientations NG: {}".format(ori_str(orientations_ng)))
print("Orientations DK: {}".format(ori_str(orientations_dk)))
def test_transfo_figure_out_ants_frame_exhaustive():
dir_tmp = "."
all_orientations = msct_image.all_refspace_strings()
#all_orientations = ("LPS", "LPI")
print("Wondering which orientation is native to ANTs")
working_orientations = [] # there can't be only one...
for orientation in all_orientations:
print(" Shifting +1,+1,+1 (in {})".format(orientation))
path_src = "warp-{}-src.nii".format(orientation)
img_src = fake_3dimage_sct().change_orientation(orientation).save(path_src)
# Create warping field
shape = tuple(list(img_src.data.shape) + [1,3])
data = np.ones(shape, order="F")
path_warp = "warp-{}-field.nii".format(orientation)
img_warp = fake_image_sct_custom(data)
img_warp.header.set_intent('vector', (), '')
img_warp.change_orientation(orientation).save(path_warp)
print(" Affine:\n{}".format(img_warp.header.get_best_affine()))
path_dst = "warp-{}-dst.nii".format(orientation)
xform = sct_apply_transfo.Transform(path_src, path_warp, path_src, path_dst)
xform.apply()
img_src2 = msct_image.Image(path_src)
img_dst = msct_image.Image(path_dst)
assert img_src.orientation == img_dst.orientation
assert img_src.data.shape == img_dst.data.shape
dat_src = img_src.data
dat_dst = np.array(img_dst.data)
value = 222
aff_src = img_dst.header.get_best_affine()
aff_dst = img_dst.header.get_best_affine()
pt_src = np.array(np.unravel_index(np.argmin(np.abs(dat_src - value)), dat_src.shape))#, order="F"))
pt_dst = np.array(np.unravel_index(np.argmin(np.abs(dat_dst - value)), dat_dst.shape))#, order="F"))
print("Point %s -> %s" % (pt_src, pt_dst))
pos_src = np.matmul(aff_src, np.hstack((pt_src, [1])).reshape((4,1)))
pos_dst = np.matmul(aff_dst, np.hstack((pt_dst, [1])).reshape((4,1)))
displacement = (pos_dst - pos_src).T[:3]
print("Displacement (physical): %s" % (displacement))
displacement = pt_dst - pt_src
print("Displacement (logical): %s" % (displacement))
assert dat_src.shape == dat_dst.shape
if 0:
for idx_slice in range(9):
print(dat_src[...,idx_slice])
print(dat_dst[...,idx_slice])
print("")
try:
# Check same as before
assert np.allclose(dat_dst[0,:,:], 0)
assert np.allclose(dat_dst[:,0,:], 0)
assert np.allclose(dat_dst[:,:,0], 0)
assert np.allclose(dat_src[:-1,:-1,:-1], dat_dst[1:,1:,1:])
working_orientations.append(orientation)
except AssertionError as e:
continue
print("\x1B[31;1m Failed in {}\x1B[0m".format(orientation))
for idx_slice in range(shape[2]):
print(dat_src[...,idx_slice])
print(dat_dst[...,idx_slice])
print("")
print("-> Working orientation: {}".format(" ".join(working_orientations)))