"""
Test ants.registration module
nptest.assert_allclose
self.assertEqual
self.assertTrue
"""
import os
import unittest
from common import run_tests
from tempfile import mktemp
import numpy as np
import numpy.testing as nptest
import pandas as pd
import ants
class TestModule_affine_initializer(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
# test ANTsPy/ANTsR example
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r27"))
txfile = ants.affine_initializer(fi, mi)
tx = ants.read_transform(txfile)
class TestModule_apply_transforms(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
# test ANTsPy/ANTsR example
fixed = ants.image_read(ants.get_ants_data("r16"))
moving = ants.image_read(ants.get_ants_data("r64"))
fixed = ants.resample_image(fixed, (64, 64), 1, 0)
moving = ants.resample_image(moving, (128, 128), 1, 0)
mytx = ants.registration(fixed=fixed, moving=moving, type_of_transform="SyN")
mywarpedimage = ants.apply_transforms(
fixed=fixed, moving=moving, transformlist=mytx["fwdtransforms"]
)
self.assertEqual(mywarpedimage.pixeltype, moving.pixeltype)
self.assertTrue(ants.image_physical_space_consistency(fixed, mywarpedimage,
0.0001, datatype = False))
# Call with float precision for transforms, but should still return input type
mywarpedimage2 = ants.apply_transforms(
fixed=fixed, moving=moving, transformlist=mytx["fwdtransforms"], singleprecision=True
)
self.assertEqual(mywarpedimage2.pixeltype, moving.pixeltype)
self.assertLessEqual(np.sum((mywarpedimage.numpy() - mywarpedimage2.numpy()) ** 2), 0.1)
# bad interpolator
with self.assertRaises(Exception):
mywarpedimage = ants.apply_transforms(
fixed=fixed,
moving=moving,
transformlist=mytx["fwdtransforms"],
interpolator="unsupported-interp",
)
# transform doesnt exist
with self.assertRaises(Exception):
mywarpedimage = ants.apply_transforms(
fixed=fixed,
moving=moving,
transformlist=["blah-blah.mat"],
interpolator="unsupported-interp",
)
class TestModule_create_jacobian_determinant_image(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r64"))
fi = ants.resample_image(fi, (128, 128), 1, 0)
mi = ants.resample_image(mi, (128, 128), 1, 0)
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform=("SyN"))
try:
jac = ants.create_jacobian_determinant_image(
fi, mytx["fwdtransforms"][0], 1
)
except:
pass
class TestModule_create_warped_grid(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r64"))
mygr = ants.create_warped_grid(mi)
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform=("SyN"))
mywarpedgrid = ants.create_warped_grid(
mi,
grid_directions=(False, True),
transform=mytx["fwdtransforms"],
fixed_reference_image=fi,
)
class TestModule_fsl2antstransform(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
fslmat = np.zeros((4, 4))
np.fill_diagonal(fslmat, 1)
img = ants.image_read(ants.get_ants_data("ch2"))
tx = ants.fsl2antstransform(fslmat, img, img)
class TestModule_interface(unittest.TestCase):
def setUp(self):
self.transform_types = {
"SyNBold",
"SyNBoldAff",
"ElasticSyN",
"SyN",
"SyNRA",
"SyNOnly",
"SyNAggro",
"SyNCC",
"TRSAA",
"SyNabp",
"SyNLessAggro",
"TVMSQ",
"TVMSQC",
"Rigid",
"Similarity",
"Translation",
"Affine",
"AffineFast",
"BOLDAffine",
"QuickRigid",
"DenseRigid",
"BOLDRigid",
"antsRegistrationSyNQuick[b,32,26]",
"antsRegistrationSyNQuick[s]",
"antsRegistrationSyNRepro[s]",
"antsRegistrationSyN[s]"
}
def tearDown(self):
pass
def test_example(self):
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r64"))
fi = ants.resample_image(fi, (60, 60), 1, 0)
mi = ants.resample_image(mi, (60, 60), 1, 0)
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform="SyN")
def test_affine_interface(self):
print("Starting affine interface registration test")
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r64"))
with self.assertRaises(ValueError):
ants.registration(
fixed=fi,
moving=mi,
type_of_transform="Translation",
aff_iterations=4,
aff_shrink_factors=4,
aff_smoothing_sigmas=(4, 4),
)
mytx = ants.registration(
fixed=fi,
moving=mi,
type_of_transform="Affine",
aff_iterations=(4, 4),
aff_shrink_factors=(4, 4),
aff_smoothing_sigmas=(4, 4),
)
mytx = ants.registration(
fixed=fi,
moving=mi,
type_of_transform="Translation",
aff_iterations=4,
aff_shrink_factors=4,
aff_smoothing_sigmas=4,
)
def test_registration_types(self):
print("Starting long registration interface test")
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r64"))
fi = ants.resample_image(fi, (60, 60), 1, 0)
mi = ants.resample_image(mi, (60, 60), 1, 0)
for ttype in self.transform_types:
print(ttype)
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform=ttype)
# with mask
fimask = fi > fi.mean()
mytx = ants.registration(
fixed=fi, moving=mi, mask=fimask, type_of_transform=ttype
)
print("Finished long registration interface test")
class TestModule_metrics(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
fi = ants.image_read(ants.get_ants_data("r16")).clone("float")
mi = ants.image_read(ants.get_ants_data("r64")).clone("float")
mival = ants.image_mutual_information(fi, mi) # -0.1796141
class TestModule_reflect_image(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
fi = ants.image_read(ants.get_ants_data("r16"))
axis = 2
asym = ants.reflect_image(fi, axis, "Affine")["warpedmovout"]
asym = asym - fi
class TestModule_reorient_image(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_reorient_image(self):
mni = ants.image_read(ants.get_data('mni'))
mni2 = mni.reorient_image2()
def test_get_center_of_mass(self):
fi = ants.image_read(ants.get_ants_data("r16"))
com = ants.get_center_of_mass(fi)
self.assertEqual(len(com), fi.dimension)
fi = ants.image_read(ants.get_ants_data("r64"))
com = ants.get_center_of_mass(fi)
self.assertEqual(len(com), fi.dimension)
fi = fi.clone("unsigned int")
com = ants.get_center_of_mass(fi)
self.assertEqual(len(com), fi.dimension)
# 3d
img = ants.image_read(ants.get_ants_data("mni"))
com = ants.get_center_of_mass(img)
self.assertEqual(len(com), img.dimension)
class TestModule_resample_image(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_resample_image_example(self):
fi = ants.image_read(ants.get_ants_data("r16"))
finn = ants.resample_image(fi, (50, 60), True, 0)
filin = ants.resample_image(fi, (1.5, 1.5), False, 1)
def test_resample_channels(self):
img = ants.image_read( ants.get_ants_data("r16"))
img = ants.merge_channels([img, img])
outimg = ants.resample_image(img, (128,128), True)
self.assertEqual(outimg.shape, (128, 128))
self.assertEqual(outimg.components, 2)
def test_resample_image_to_target_example(self):
fi = ants.image_read(ants.get_ants_data("r16"))
fi2mm = ants.resample_image(fi, (2, 2), use_voxels=0, interp_type=1)
resampled = ants.resample_image_to_target(fi2mm, fi, verbose=True)
self.assertTrue(ants.image_physical_space_consistency(fi, resampled, 0.0001, datatype=True))
class TestModule_symmetrize_image(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
image = ants.image_read(ants.get_ants_data("r16"))
simage = ants.symmetrize_image(image)
class TestModule_build_template(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
image = ants.image_read(ants.get_ants_data("r16"))
image2 = ants.image_read(ants.get_ants_data("r27"))
timage = ants.build_template(image_list=(image, image2))
def test_type_of_transform(self):
image = ants.image_read(ants.get_ants_data("r16"))
image2 = ants.image_read(ants.get_ants_data("r27"))
timage = ants.build_template(image_list=(image, image2))
timage = ants.build_template(
image_list=(image, image2), type_of_transform="SyNCC"
)
class TestModule_multivar(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_example(self):
image = ants.image_read(ants.get_ants_data("r16"))
image2 = ants.image_read(ants.get_ants_data("r27"))
demonsMetric = ["demons", image, image2, 1, 1]
ccMetric = ["CC", image, image2, 2, 1]
metrics = list()
metrics.append(demonsMetric)
reg3 = ants.registration(image, image2, "SyNOnly", multivariate_extras=metrics)
metrics.append(ccMetric)
reg2 = ants.registration(
image, image2, "SyNOnly", multivariate_extras=metrics, verbose=True
)
class TestModule_random(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_landmark_transforms(self):
fixed = np.array([[50.0,50.0],[200.0,50.0],[200.0,200.0]])
moving = np.array([[50.0,50.0],[50.0,200.0],[200.0,200.0]])
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="syn",
domain_image=ants.image_read(ants.get_data('r16')),
verbose=True)
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="tv",
domain_image=ants.image_read(ants.get_data('r16')))
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="affine")
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="rigid")
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="similarity")
domain_image = ants.image_read(ants.get_ants_data("r16"))
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="bspline", domain_image=domain_image, number_of_fitting_levels=5)
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="diffeo", domain_image=domain_image, number_of_fitting_levels=6)
res = ants.fit_time_varying_transform_to_point_sets([fixed, moving, moving],
domain_image=ants.image_read(ants.get_data('r16')),
verbose=True)
def test_deformation_gradient(self):
fi = ants.image_read( ants.get_ants_data('r16'))
mi = ants.image_read( ants.get_ants_data('r64'))
fi = ants.resample_image(fi,(128,128),1,0)
mi = ants.resample_image(mi,(128,128),1,0)
mytx = ants.registration(fixed=fi , moving=mi, type_of_transform = ('SyN') )
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ) )
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ),
py_based=True)
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ),
to_rotation=True)
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ),
to_rotation=True, py_based=True)
def test_jacobian(self):
fi = ants.image_read( ants.get_ants_data('r16'))
mi = ants.image_read( ants.get_ants_data('r64'))
fi = ants.resample_image(fi,(128,128),1,0)
mi = ants.resample_image(mi,(128,128),1,0)
mytx = ants.registration(fixed=fi , moving=mi, type_of_transform = ('SyN') )
jac = ants.create_jacobian_determinant_image(fi,mytx['fwdtransforms'][0],1)
def test_apply_transforms(self):
fixed = ants.image_read( ants.get_ants_data('r16') )
moving = ants.image_read( ants.get_ants_data('r64') )
fixed = ants.resample_image(fixed, (64,64), 1, 0)
moving = ants.resample_image(moving, (64,64), 1, 0)
mytx = ants.registration(fixed=fixed , moving=moving ,
type_of_transform = 'SyN' )
mywarpedimage = ants.apply_transforms( fixed=fixed, moving=moving,
transformlist=mytx['fwdtransforms'] )
def test_apply_transforms_to_points(self):
fixed = ants.image_read( ants.get_ants_data('r16') )
moving = ants.image_read( ants.get_ants_data('r27') )
reg = ants.registration( fixed, moving, 'Affine' )
d = {'x': [128, 127], 'y': [101, 111]}
pts = pd.DataFrame(data=d)
ptsw = ants.apply_transforms_to_points( 2, pts, reg['fwdtransforms'])
def test_warped_grid(self):
fi = ants.image_read( ants.get_ants_data( 'r16' ) )
mi = ants.image_read( ants.get_ants_data( 'r64' ) )
mygr = ants.create_warped_grid( mi )
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = ('SyN') )
mywarpedgrid = ants.create_warped_grid( mi, grid_directions=(False,True),
transform=mytx['fwdtransforms'], fixed_reference_image=fi )
def test_more_registration(self):
fi = ants.image_read(ants.get_ants_data('r16'))
mi = ants.image_read(ants.get_ants_data('r64'))
fi = ants.resample_image(fi, (60,60), 1, 0)
mi = ants.resample_image(mi, (60,60), 1, 0)
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'SyN' )
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'antsRegistrationSyN[t]' )
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'antsRegistrationSyN[b]' )
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'antsRegistrationSyN[s]' )
def test_motion_correction(self):
fi = ants.image_read(ants.get_ants_data('ch2'))
mytx = ants.motion_correction( fi )
def test_label_image_registration(self):
fi = ants.image_read(ants.get_ants_data('r16'))
mi = ants.image_read(ants.get_ants_data('r64'))
fi = ants.resample_image(fi, (60,60), 1, 0)
mi = ants.resample_image(mi, (60,60), 1, 0)
fi_seg = ants.threshold_image(fi, "Kmeans", 3)-1
mi_seg = ants.threshold_image(mi, "Kmeans", 3)-1
mytx = ants.label_image_registration([fi_seg],
[mi_seg],
fixed_intensity_images=fi,
moving_intensity_images=mi)
def test_reg_precision_option(self):
# Check that registration and apply transforms works with float and double precision
fi = ants.image_read(ants.get_ants_data("r16"))
mi = ants.image_read(ants.get_ants_data("r64"))
fi = ants.resample_image(fi, (60, 60), 1, 0)
mi = ants.resample_image(mi, (60, 60), 1, 0)
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform="SyN") # should be float precision
info = ants.image_header_info(mytx["fwdtransforms"][0])
self.assertEqual(info['pixeltype'], 'float')
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform="SyN", singleprecision=False)
info = ants.image_header_info(mytx["fwdtransforms"][0])
self.assertEqual(info['pixeltype'], 'double')
if __name__ == "__main__":
run_tests()
