TorchIO-project /
torchio
| @@ 290-304 (lines=15) @@ | ||
| 287 | transformed = aff(image) |
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| 288 | assert all(n in (0, 1) for n in transformed.data.flatten()) |
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| 289 | ||
| 290 | def test_no_inverse(self): |
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| 291 | tensor = torch.zeros((1, 2, 2, 2)) |
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| 292 | tensor[0, 1, 1, 1] = 1 # most RAS voxel |
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| 293 | expected = torch.zeros((1, 2, 2, 2)) |
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| 294 | expected[0, 0, 1, 1] = 1 |
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| 295 | scales = 1, 1, 1 |
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| 296 | degrees = 0, 0, 90 # anterior should go left |
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| 297 | translation = 0, 0, 0 |
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| 298 | apply_affine = tio.Affine( |
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| 299 | scales, |
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| 300 | degrees, |
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| 301 | translation, |
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| 302 | ) |
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| 303 | transformed = apply_affine(tensor) |
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| 304 | self.assert_tensor_almost_equal(transformed, expected) |
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| 305 | ||
| 306 | def test_different_spaces(self): |
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| 307 | t1 = self.sample_subject.t1 |
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| @@ 210-224 (lines=15) @@ | ||
| 207 | with pytest.raises(ValueError): |
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| 208 | tio.RandomAffine(default_pad_label='minimum') |
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| 209 | ||
| 210 | def test_no_inverse(self): |
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| 211 | tensor = torch.zeros((1, 2, 2, 2)) |
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| 212 | tensor[0, 1, 1, 1] = 1 # most RAS voxel |
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| 213 | expected = torch.zeros((1, 2, 2, 2)) |
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| 214 | expected[0, 0, 1, 1] = 1 |
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| 215 | scales = 1, 1, 1 |
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| 216 | degrees = 0, 0, 90 # anterior should go left |
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| 217 | translation = 0, 0, 0 |
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| 218 | apply_affine = tio.Affine( |
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| 219 | scales, |
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| 220 | degrees, |
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| 221 | translation, |
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| 222 | ) |
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| 223 | transformed = apply_affine(tensor) |
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| 224 | self.assert_tensor_almost_equal(transformed, expected) |
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| 225 | ||
| 226 | def test_different_spaces(self): |
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| 227 | t1 = self.sample_subject.t1 |
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