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import torch |
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import torchio as tio |
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3
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from ...utils import TorchioTestCase |
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5
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6
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class TestClamp(TorchioTestCase): |
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"""Tests for :class:`tio.Clamp` class.""" |
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9
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def test_out_min_max(self): |
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transform = tio.Clamp(out_min=0, out_max=1) |
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transformed = transform(self.sample_subject) |
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self.assertEqual(transformed.t1.data.min(), 0) |
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self.assertEqual(transformed.t1.data.max(), 1) |
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15
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def test_ct(self): |
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ct_max = 1500 |
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ct_min = -2000 |
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ct_range = ct_max - ct_min |
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tensor = torch.rand(1, 30, 30, 30) * ct_range + ct_min |
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ct = tio.ScalarImage(tensor=tensor) |
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ct_air = -1000 |
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ct_bone = 1000 |
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clamp = tio.Clamp(ct_air, ct_bone) |
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clamped = clamp(ct) |
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assert clamped.data.min() == ct_air |
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assert clamped.data.max() == ct_bone |
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def test_too_many_values_for_out_min(self): |
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with self.assertRaises(TypeError): |
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clamp = tio.Clamp(out_min=(1, 2)) |
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clamp(self.sample_subject) |
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33
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def test_too_many_values_for_out_max(self): |
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with self.assertRaises(TypeError): |
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clamp = tio.Clamp(out_max=(1, 2)) |
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clamp(self.sample_subject) |
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38
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def test_wrong_out_min_type(self): |
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with self.assertRaises(TypeError): |
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clamp = tio.Clamp(out_min='foo') |
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clamp(self.sample_subject) |
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def test_wrong_out_max_type(self): |
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with self.assertRaises(TypeError): |
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clamp = tio.Clamp(out_max='foo') |
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clamp(self.sample_subject) |
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fepegar /
torchio
