tests.transforms.preprocessing.test_onehot

Complexity

Total Complexity

3

Size/Duplication

Total Lines	17
Duplicated Lines	0 %

Importance

Changes

0

2 Methods

Rating	Name	Duplication	Size	Complexity
A	TestOneHot.test_multichannel()	0	4	2
A	TestOneHot.test_one_hot()	0	4	1

import torch
import torchio as tio
from ...utils import TorchioTestCase


class TestOneHot(TorchioTestCase):
    """Tests for `OneHot`."""
    def test_one_hot(self):
        image = self.sample_subject.label
        one_hot = tio.OneHot(num_classes=3)(image)
        assert one_hot.num_channels == 3

    def test_multichannel(self):
        label_map = tio.LabelMap(tensor=torch.rand(2, 3, 3, 3) > 1)
        with self.assertRaises(RuntimeError):
            tio.OneHot()(label_map)