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from torchio import RandomNoise |
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from ...utils import TorchioTestCase |
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from numpy.testing import assert_array_equal |
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class TestRandomNoise(TorchioTestCase): |
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"""Tests for `RandomNoise`.""" |
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def test_no_noise(self): |
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transform = RandomNoise(mean=0., std=0.) |
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transformed = transform(self.sample) |
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assert_array_equal(self.sample.t1.data, transformed.t1.data) |
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def test_with_noise(self): |
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transform = RandomNoise() |
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transformed = transform(self.sample) |
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with self.assertRaises(AssertionError): |
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assert_array_equal(self.sample.t1.data, transformed.t1.data) |
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def test_constant_noise(self): |
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transform = RandomNoise(mean=(5., 5.), std=0.) |
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transformed = transform(self.sample) |
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assert_array_equal(self.sample.t1.data + 5, transformed.t1.data) |
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def test_negative_std(self): |
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with self.assertRaises(ValueError): |
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RandomNoise(std=-2) |
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def test_std_range_with_negative_min(self): |
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with self.assertRaises(ValueError): |
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RandomNoise(std=(-0.5, 4)) |
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def test_wrong_std_type(self): |
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with self.assertRaises(ValueError): |
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RandomNoise(std='wrong') |
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def test_wrong_mean_type(self): |
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with self.assertRaises(ValueError): |
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RandomNoise(mean='wrong') |
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fepegar /
torchio
