tests.transforms.preprocessing.test_copy_affine

Complexity

Total Complexity

5

Size/Duplication

Total Lines	29
Duplicated Lines	0 %

Importance

Changes

0

3 Methods

Rating	Name	Duplication	Size	Complexity
A	TestCopyAffine.test_missing_reference()	0	4	2
A	TestCopyAffine.test_wrong_target_type()	0	3	2
A	TestCopyAffine.test_same_affine()	0	10	1

import torch

import torchio as tio
from ...utils import TorchioTestCase


class TestCopyAffine(TorchioTestCase):
    """Tests for `CopyAffine`."""

    def test_missing_reference(self):
        transform = tio.CopyAffine(target='missing')
        with self.assertRaises(RuntimeError):
            transform(self.sample_subject)

    def test_wrong_target_type(self):
        with self.assertRaises(ValueError):
            tio.CopyAffine(target=[1])

    def test_same_affine(self):
        image = tio.ScalarImage(tensor=torch.rand(2, 2, 2, 2))
        mask = tio.LabelMap(tensor=torch.rand(2, 2, 2, 2))
        mask.affine *= 1.1
        subject = tio.Subject(t1=image, mask=mask)
        transform = tio.CopyAffine('t1')
        transformed = transform(subject)
        self.assertTensorEqual(
            transformed['t1'].affine,
            transformed['mask'].affine,
        )