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a |
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b/tests/test_registration.py |
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""" |
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Test ants.registration module |
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nptest.assert_allclose |
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self.assertEqual |
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self.assertTrue |
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""" |
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import os |
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import unittest |
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from common import run_tests |
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from tempfile import mktemp |
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import numpy as np |
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import numpy.testing as nptest |
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import pandas as pd |
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import ants |
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class TestModule_affine_initializer(unittest.TestCase): |
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def setUp(self): |
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pass |
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def tearDown(self): |
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pass |
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def test_example(self): |
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# test ANTsPy/ANTsR example |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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mi = ants.image_read(ants.get_ants_data("r27")) |
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txfile = ants.affine_initializer(fi, mi) |
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tx = ants.read_transform(txfile) |
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35 |
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class TestModule_apply_transforms(unittest.TestCase): |
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def setUp(self): |
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pass |
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def tearDown(self): |
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pass |
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def test_example(self): |
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# test ANTsPy/ANTsR example |
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fixed = ants.image_read(ants.get_ants_data("r16")) |
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moving = ants.image_read(ants.get_ants_data("r64")) |
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fixed = ants.resample_image(fixed, (64, 64), 1, 0) |
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moving = ants.resample_image(moving, (128, 128), 1, 0) |
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mytx = ants.registration(fixed=fixed, moving=moving, type_of_transform="SyN") |
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mywarpedimage = ants.apply_transforms( |
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fixed=fixed, moving=moving, transformlist=mytx["fwdtransforms"] |
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) |
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self.assertEqual(mywarpedimage.pixeltype, moving.pixeltype) |
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self.assertTrue(ants.image_physical_space_consistency(fixed, mywarpedimage, |
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0.0001, datatype = False)) |
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# Call with float precision for transforms, but should still return input type |
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mywarpedimage2 = ants.apply_transforms( |
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fixed=fixed, moving=moving, transformlist=mytx["fwdtransforms"], singleprecision=True |
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) |
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self.assertEqual(mywarpedimage2.pixeltype, moving.pixeltype) |
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self.assertLessEqual(np.sum((mywarpedimage.numpy() - mywarpedimage2.numpy()) ** 2), 0.1) |
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# bad interpolator |
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with self.assertRaises(Exception): |
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mywarpedimage = ants.apply_transforms( |
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fixed=fixed, |
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moving=moving, |
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transformlist=mytx["fwdtransforms"], |
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interpolator="unsupported-interp", |
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) |
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# transform doesnt exist |
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with self.assertRaises(Exception): |
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mywarpedimage = ants.apply_transforms( |
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fixed=fixed, |
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moving=moving, |
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transformlist=["blah-blah.mat"], |
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interpolator="unsupported-interp", |
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) |
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class TestModule_create_jacobian_determinant_image(unittest.TestCase): |
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def setUp(self): |
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pass |
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def tearDown(self): |
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pass |
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def test_example(self): |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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mi = ants.image_read(ants.get_ants_data("r64")) |
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fi = ants.resample_image(fi, (128, 128), 1, 0) |
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mi = ants.resample_image(mi, (128, 128), 1, 0) |
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mytx = ants.registration(fixed=fi, moving=mi, type_of_transform=("SyN")) |
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try: |
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jac = ants.create_jacobian_determinant_image( |
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fi, mytx["fwdtransforms"][0], 1 |
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) |
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except: |
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pass |
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102 |
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103 |
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class TestModule_create_warped_grid(unittest.TestCase): |
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def setUp(self): |
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pass |
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def tearDown(self): |
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pass |
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def test_example(self): |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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mi = ants.image_read(ants.get_ants_data("r64")) |
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mygr = ants.create_warped_grid(mi) |
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mytx = ants.registration(fixed=fi, moving=mi, type_of_transform=("SyN")) |
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mywarpedgrid = ants.create_warped_grid( |
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mi, |
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grid_directions=(False, True), |
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transform=mytx["fwdtransforms"], |
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fixed_reference_image=fi, |
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) |
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123 |
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124 |
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class TestModule_fsl2antstransform(unittest.TestCase): |
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def setUp(self): |
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pass |
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def tearDown(self): |
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pass |
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def test_example(self): |
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fslmat = np.zeros((4, 4)) |
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np.fill_diagonal(fslmat, 1) |
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img = ants.image_read(ants.get_ants_data("ch2")) |
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tx = ants.fsl2antstransform(fslmat, img, img) |
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137 |
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138 |
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class TestModule_interface(unittest.TestCase): |
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def setUp(self): |
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self.transform_types = { |
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"SyNBold", |
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"SyNBoldAff", |
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"ElasticSyN", |
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"SyN", |
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"SyNRA", |
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"SyNOnly", |
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"SyNAggro", |
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"SyNCC", |
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"TRSAA", |
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"SyNabp", |
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"SyNLessAggro", |
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"TVMSQ", |
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"TVMSQC", |
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"Rigid", |
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"Similarity", |
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"Translation", |
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"Affine", |
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"AffineFast", |
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"BOLDAffine", |
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"QuickRigid", |
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"DenseRigid", |
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"BOLDRigid", |
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"antsRegistrationSyNQuick[b,32,26]", |
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"antsRegistrationSyNQuick[s]", |
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"antsRegistrationSyNRepro[s]", |
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"antsRegistrationSyN[s]" |
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} |
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169 |
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def tearDown(self): |
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pass |
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172 |
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def test_example(self): |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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mi = ants.image_read(ants.get_ants_data("r64")) |
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fi = ants.resample_image(fi, (60, 60), 1, 0) |
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mi = ants.resample_image(mi, (60, 60), 1, 0) |
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mytx = ants.registration(fixed=fi, moving=mi, type_of_transform="SyN") |
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179 |
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def test_affine_interface(self): |
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print("Starting affine interface registration test") |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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mi = ants.image_read(ants.get_ants_data("r64")) |
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with self.assertRaises(ValueError): |
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ants.registration( |
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fixed=fi, |
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moving=mi, |
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type_of_transform="Translation", |
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aff_iterations=4, |
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aff_shrink_factors=4, |
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aff_smoothing_sigmas=(4, 4), |
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) |
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193 |
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mytx = ants.registration( |
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fixed=fi, |
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moving=mi, |
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type_of_transform="Affine", |
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aff_iterations=(4, 4), |
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aff_shrink_factors=(4, 4), |
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aff_smoothing_sigmas=(4, 4), |
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) |
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mytx = ants.registration( |
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fixed=fi, |
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moving=mi, |
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type_of_transform="Translation", |
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aff_iterations=4, |
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aff_shrink_factors=4, |
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aff_smoothing_sigmas=4, |
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) |
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210 |
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def test_registration_types(self): |
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print("Starting long registration interface test") |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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mi = ants.image_read(ants.get_ants_data("r64")) |
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fi = ants.resample_image(fi, (60, 60), 1, 0) |
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mi = ants.resample_image(mi, (60, 60), 1, 0) |
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217 |
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for ttype in self.transform_types: |
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print(ttype) |
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mytx = ants.registration(fixed=fi, moving=mi, type_of_transform=ttype) |
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221 |
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# with mask |
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fimask = fi > fi.mean() |
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mytx = ants.registration( |
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fixed=fi, moving=mi, mask=fimask, type_of_transform=ttype |
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) |
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print("Finished long registration interface test") |
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228 |
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229 |
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class TestModule_metrics(unittest.TestCase): |
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def setUp(self): |
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pass |
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233 |
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def tearDown(self): |
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pass |
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236 |
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def test_example(self): |
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fi = ants.image_read(ants.get_ants_data("r16")).clone("float") |
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mi = ants.image_read(ants.get_ants_data("r64")).clone("float") |
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mival = ants.image_mutual_information(fi, mi) # -0.1796141 |
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241 |
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242 |
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class TestModule_reflect_image(unittest.TestCase): |
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def setUp(self): |
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pass |
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246 |
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def tearDown(self): |
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pass |
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249 |
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def test_example(self): |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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axis = 2 |
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asym = ants.reflect_image(fi, axis, "Affine")["warpedmovout"] |
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asym = asym - fi |
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255 |
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256 |
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257 |
class TestModule_reorient_image(unittest.TestCase): |
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def setUp(self): |
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pass |
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260 |
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def tearDown(self): |
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262 |
pass |
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263 |
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264 |
def test_reorient_image(self): |
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mni = ants.image_read(ants.get_data('mni')) |
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mni2 = mni.reorient_image2() |
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267 |
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268 |
def test_get_center_of_mass(self): |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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com = ants.get_center_of_mass(fi) |
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271 |
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self.assertEqual(len(com), fi.dimension) |
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273 |
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274 |
fi = ants.image_read(ants.get_ants_data("r64")) |
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com = ants.get_center_of_mass(fi) |
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self.assertEqual(len(com), fi.dimension) |
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277 |
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fi = fi.clone("unsigned int") |
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com = ants.get_center_of_mass(fi) |
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280 |
self.assertEqual(len(com), fi.dimension) |
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281 |
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282 |
# 3d |
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283 |
img = ants.image_read(ants.get_ants_data("mni")) |
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com = ants.get_center_of_mass(img) |
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self.assertEqual(len(com), img.dimension) |
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286 |
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287 |
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288 |
class TestModule_resample_image(unittest.TestCase): |
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289 |
def setUp(self): |
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290 |
pass |
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291 |
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292 |
def tearDown(self): |
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293 |
pass |
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294 |
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295 |
def test_resample_image_example(self): |
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fi = ants.image_read(ants.get_ants_data("r16")) |
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finn = ants.resample_image(fi, (50, 60), True, 0) |
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filin = ants.resample_image(fi, (1.5, 1.5), False, 1) |
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299 |
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300 |
def test_resample_channels(self): |
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301 |
img = ants.image_read( ants.get_ants_data("r16")) |
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img = ants.merge_channels([img, img]) |
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303 |
outimg = ants.resample_image(img, (128,128), True) |
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304 |
self.assertEqual(outimg.shape, (128, 128)) |
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305 |
self.assertEqual(outimg.components, 2) |
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306 |
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307 |
def test_resample_image_to_target_example(self): |
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308 |
fi = ants.image_read(ants.get_ants_data("r16")) |
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309 |
fi2mm = ants.resample_image(fi, (2, 2), use_voxels=0, interp_type=1) |
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310 |
resampled = ants.resample_image_to_target(fi2mm, fi, verbose=True) |
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311 |
self.assertTrue(ants.image_physical_space_consistency(fi, resampled, 0.0001, datatype=True)) |
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312 |
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313 |
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314 |
class TestModule_symmetrize_image(unittest.TestCase): |
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315 |
def setUp(self): |
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316 |
pass |
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317 |
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318 |
def tearDown(self): |
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319 |
pass |
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320 |
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321 |
def test_example(self): |
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322 |
image = ants.image_read(ants.get_ants_data("r16")) |
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323 |
simage = ants.symmetrize_image(image) |
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324 |
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325 |
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326 |
class TestModule_build_template(unittest.TestCase): |
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327 |
def setUp(self): |
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328 |
pass |
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329 |
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330 |
def tearDown(self): |
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331 |
pass |
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332 |
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333 |
def test_example(self): |
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334 |
image = ants.image_read(ants.get_ants_data("r16")) |
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335 |
image2 = ants.image_read(ants.get_ants_data("r27")) |
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336 |
timage = ants.build_template(image_list=(image, image2)) |
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337 |
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338 |
def test_type_of_transform(self): |
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339 |
image = ants.image_read(ants.get_ants_data("r16")) |
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340 |
image2 = ants.image_read(ants.get_ants_data("r27")) |
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341 |
timage = ants.build_template(image_list=(image, image2)) |
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342 |
timage = ants.build_template( |
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343 |
image_list=(image, image2), type_of_transform="SyNCC" |
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344 |
) |
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|
345 |
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346 |
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347 |
class TestModule_multivar(unittest.TestCase): |
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|
348 |
def setUp(self): |
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|
349 |
pass |
|
|
350 |
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|
351 |
def tearDown(self): |
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|
352 |
pass |
|
|
353 |
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354 |
def test_example(self): |
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|
355 |
image = ants.image_read(ants.get_ants_data("r16")) |
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|
356 |
image2 = ants.image_read(ants.get_ants_data("r27")) |
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357 |
demonsMetric = ["demons", image, image2, 1, 1] |
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358 |
ccMetric = ["CC", image, image2, 2, 1] |
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359 |
metrics = list() |
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360 |
metrics.append(demonsMetric) |
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361 |
reg3 = ants.registration(image, image2, "SyNOnly", multivariate_extras=metrics) |
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362 |
metrics.append(ccMetric) |
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363 |
reg2 = ants.registration( |
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364 |
image, image2, "SyNOnly", multivariate_extras=metrics, verbose=True |
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365 |
) |
|
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366 |
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367 |
class TestModule_random(unittest.TestCase): |
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|
368 |
def setUp(self): |
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|
369 |
pass |
|
|
370 |
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371 |
def tearDown(self): |
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|
372 |
pass |
|
|
373 |
|
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374 |
def test_landmark_transforms(self): |
|
|
375 |
fixed = np.array([[50.0,50.0],[200.0,50.0],[200.0,200.0]]) |
|
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376 |
moving = np.array([[50.0,50.0],[50.0,200.0],[200.0,200.0]]) |
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377 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="syn", |
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|
378 |
domain_image=ants.image_read(ants.get_data('r16')), |
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|
379 |
verbose=True) |
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|
380 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="tv", |
|
|
381 |
domain_image=ants.image_read(ants.get_data('r16'))) |
|
|
382 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="affine") |
|
|
383 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="rigid") |
|
|
384 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="similarity") |
|
|
385 |
domain_image = ants.image_read(ants.get_ants_data("r16")) |
|
|
386 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="bspline", domain_image=domain_image, number_of_fitting_levels=5) |
|
|
387 |
xfrm = ants.fit_transform_to_paired_points(moving, fixed, transform_type="diffeo", domain_image=domain_image, number_of_fitting_levels=6) |
|
|
388 |
|
|
|
389 |
res = ants.fit_time_varying_transform_to_point_sets([fixed, moving, moving], |
|
|
390 |
domain_image=ants.image_read(ants.get_data('r16')), |
|
|
391 |
verbose=True) |
|
|
392 |
|
|
|
393 |
def test_deformation_gradient(self): |
|
|
394 |
fi = ants.image_read( ants.get_ants_data('r16')) |
|
|
395 |
mi = ants.image_read( ants.get_ants_data('r64')) |
|
|
396 |
fi = ants.resample_image(fi,(128,128),1,0) |
|
|
397 |
mi = ants.resample_image(mi,(128,128),1,0) |
|
|
398 |
mytx = ants.registration(fixed=fi , moving=mi, type_of_transform = ('SyN') ) |
|
|
399 |
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ) ) |
|
|
400 |
|
|
|
401 |
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ), |
|
|
402 |
py_based=True) |
|
|
403 |
|
|
|
404 |
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ), |
|
|
405 |
to_rotation=True) |
|
|
406 |
|
|
|
407 |
dg = ants.deformation_gradient( ants.image_read( mytx['fwdtransforms'][0] ), |
|
|
408 |
to_rotation=True, py_based=True) |
|
|
409 |
|
|
|
410 |
def test_jacobian(self): |
|
|
411 |
fi = ants.image_read( ants.get_ants_data('r16')) |
|
|
412 |
mi = ants.image_read( ants.get_ants_data('r64')) |
|
|
413 |
fi = ants.resample_image(fi,(128,128),1,0) |
|
|
414 |
mi = ants.resample_image(mi,(128,128),1,0) |
|
|
415 |
mytx = ants.registration(fixed=fi , moving=mi, type_of_transform = ('SyN') ) |
|
|
416 |
jac = ants.create_jacobian_determinant_image(fi,mytx['fwdtransforms'][0],1) |
|
|
417 |
|
|
|
418 |
def test_apply_transforms(self): |
|
|
419 |
fixed = ants.image_read( ants.get_ants_data('r16') ) |
|
|
420 |
moving = ants.image_read( ants.get_ants_data('r64') ) |
|
|
421 |
fixed = ants.resample_image(fixed, (64,64), 1, 0) |
|
|
422 |
moving = ants.resample_image(moving, (64,64), 1, 0) |
|
|
423 |
mytx = ants.registration(fixed=fixed , moving=moving , |
|
|
424 |
type_of_transform = 'SyN' ) |
|
|
425 |
mywarpedimage = ants.apply_transforms( fixed=fixed, moving=moving, |
|
|
426 |
transformlist=mytx['fwdtransforms'] ) |
|
|
427 |
|
|
|
428 |
def test_apply_transforms_to_points(self): |
|
|
429 |
fixed = ants.image_read( ants.get_ants_data('r16') ) |
|
|
430 |
moving = ants.image_read( ants.get_ants_data('r27') ) |
|
|
431 |
reg = ants.registration( fixed, moving, 'Affine' ) |
|
|
432 |
d = {'x': [128, 127], 'y': [101, 111]} |
|
|
433 |
pts = pd.DataFrame(data=d) |
|
|
434 |
ptsw = ants.apply_transforms_to_points( 2, pts, reg['fwdtransforms']) |
|
|
435 |
|
|
|
436 |
def test_warped_grid(self): |
|
|
437 |
fi = ants.image_read( ants.get_ants_data( 'r16' ) ) |
|
|
438 |
mi = ants.image_read( ants.get_ants_data( 'r64' ) ) |
|
|
439 |
mygr = ants.create_warped_grid( mi ) |
|
|
440 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = ('SyN') ) |
|
|
441 |
mywarpedgrid = ants.create_warped_grid( mi, grid_directions=(False,True), |
|
|
442 |
transform=mytx['fwdtransforms'], fixed_reference_image=fi ) |
|
|
443 |
|
|
|
444 |
def test_more_registration(self): |
|
|
445 |
fi = ants.image_read(ants.get_ants_data('r16')) |
|
|
446 |
mi = ants.image_read(ants.get_ants_data('r64')) |
|
|
447 |
fi = ants.resample_image(fi, (60,60), 1, 0) |
|
|
448 |
mi = ants.resample_image(mi, (60,60), 1, 0) |
|
|
449 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'SyN' ) |
|
|
450 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'antsRegistrationSyN[t]' ) |
|
|
451 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'antsRegistrationSyN[b]' ) |
|
|
452 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform = 'antsRegistrationSyN[s]' ) |
|
|
453 |
|
|
|
454 |
def test_motion_correction(self): |
|
|
455 |
fi = ants.image_read(ants.get_ants_data('ch2')) |
|
|
456 |
mytx = ants.motion_correction( fi ) |
|
|
457 |
|
|
|
458 |
def test_label_image_registration(self): |
|
|
459 |
fi = ants.image_read(ants.get_ants_data('r16')) |
|
|
460 |
mi = ants.image_read(ants.get_ants_data('r64')) |
|
|
461 |
fi = ants.resample_image(fi, (60,60), 1, 0) |
|
|
462 |
mi = ants.resample_image(mi, (60,60), 1, 0) |
|
|
463 |
fi_seg = ants.threshold_image(fi, "Kmeans", 3)-1 |
|
|
464 |
mi_seg = ants.threshold_image(mi, "Kmeans", 3)-1 |
|
|
465 |
mytx = ants.label_image_registration([fi_seg], |
|
|
466 |
[mi_seg], |
|
|
467 |
fixed_intensity_images=fi, |
|
|
468 |
moving_intensity_images=mi) |
|
|
469 |
|
|
|
470 |
|
|
|
471 |
def test_reg_precision_option(self): |
|
|
472 |
# Check that registration and apply transforms works with float and double precision |
|
|
473 |
fi = ants.image_read(ants.get_ants_data("r16")) |
|
|
474 |
mi = ants.image_read(ants.get_ants_data("r64")) |
|
|
475 |
fi = ants.resample_image(fi, (60, 60), 1, 0) |
|
|
476 |
mi = ants.resample_image(mi, (60, 60), 1, 0) |
|
|
477 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform="SyN") # should be float precision |
|
|
478 |
info = ants.image_header_info(mytx["fwdtransforms"][0]) |
|
|
479 |
self.assertEqual(info['pixeltype'], 'float') |
|
|
480 |
mytx = ants.registration(fixed=fi, moving=mi, type_of_transform="SyN", singleprecision=False) |
|
|
481 |
info = ants.image_header_info(mytx["fwdtransforms"][0]) |
|
|
482 |
self.assertEqual(info['pixeltype'], 'double') |
|
|
483 |
|
|
|
484 |
if __name__ == "__main__": |
|
|
485 |
run_tests() |