tests.transforms.augmentation.test_random_blur

Complexity

Total Complexity

9

Size/Duplication

Total Lines	36
Duplicated Lines	0 %

Importance

Changes

0

6 Methods

Rating	Name	Duplication	Size	Complexity
A	TestRandomBlur.test_wrong_std_type()	0	3	2
A	TestRandomBlur.test_negative_std()	0	3	2
A	TestRandomBlur.test_std_range_with_negative_min()	0	3	2
A	TestRandomBlur.test_no_blurring()	0	4	1
A	TestRandomBlur.test_with_blurring()	0	4	1
A	TestRandomBlur.test_parse_stds()	0	7	1

from torchio import RandomBlur
from ...utils import TorchioTestCase


class TestRandomBlur(TorchioTestCase):
    """Tests for `RandomBlur`."""
    def test_no_blurring(self):
        transform = RandomBlur(std=0)
        transformed = transform(self.sample_subject)
        self.assertTensorAlmostEqual(self.sample_subject.t1.data, transformed.t1.data)

    def test_with_blurring(self):
        transform = RandomBlur(std=(1, 3))
        transformed = transform(self.sample_subject)
        self.assertTensorNotEqual(self.sample_subject.t1.data, transformed.t1.data)

    def test_negative_std(self):
        with self.assertRaises(ValueError):
            RandomBlur(std=-2)

    def test_std_range_with_negative_min(self):
        with self.assertRaises(ValueError):
            RandomBlur(std=(-0.5, 4))

    def test_wrong_std_type(self):
        with self.assertRaises(ValueError):
            RandomBlur(std='wrong')

    def test_parse_stds(self):
        def do_assert(transform):
            self.assertEqual(transform.std_ranges, 3 * (0, 1))
        do_assert(RandomBlur(std=1))
        do_assert(RandomBlur(std=(0, 1)))
        do_assert(RandomBlur(std=3 * (1,)))
        do_assert(RandomBlur(std=3 * [0, 1]))