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import pytest |
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import SimpleITK as sitk |
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import torch |
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import torchio as tio |
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from torchio.data.io import sitk_to_nib |
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from ...utils import TorchioTestCase |
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class TestPad(TorchioTestCase): |
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"""Tests for `Pad`.""" |
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def test_pad(self): |
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image = self.sample_subject.t1 |
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padding = 1, 2, 3, 4, 5, 6 |
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sitk_image = image.as_sitk() |
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low, high = padding[::2], padding[1::2] |
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sitk_padded = sitk.ConstantPad(sitk_image, low, high, 0) |
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tio_padded = tio.Pad(padding, padding_mode=0)(image) |
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sitk_tensor, sitk_affine = sitk_to_nib(sitk_padded) |
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tio_tensor, tio_affine = sitk_to_nib(tio_padded.as_sitk()) |
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self.assert_tensor_equal(sitk_tensor, tio_tensor) |
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self.assert_tensor_equal(sitk_affine, tio_affine) |
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def test_nans_history(self): |
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padded = tio.Pad(1, padding_mode=2)(self.sample_subject) |
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again = padded.history[0](self.sample_subject) |
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assert not torch.isnan(again.t1.data).any() |
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def test_padding_modes(self): |
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def padding_func(): |
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return |
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for padding_mode in [0, *tio.Pad.PADDING_MODES, padding_func]: |
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tio.Pad(0, padding_mode=padding_mode) |
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with self.assertRaises(KeyError): |
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tio.Pad(0, padding_mode='abc') |
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def test_padding_mean_label_map(self): |
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with self.assertWarns(RuntimeWarning): |
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tio.Pad(1, padding_mode='mean')(self.sample_subject.label) |
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def test_padding_modes_global(self): |
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x = torch.ones(1, 1, 2, 2, dtype=torch.int) |
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x[..., 0, 0] = 0 |
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# The image should look like this: |
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# 0 1 |
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# 1 1 |
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add_bottom_row = 0, 0, 0, 1, 0, 0 |
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with_zeros = tio.Pad(add_bottom_row)(x) |
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assert with_zeros[0, 0, 2].tolist() == [0, 0] |
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with_minimum = tio.Pad(add_bottom_row, padding_mode='minimum')(x) |
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assert with_minimum[0, 0, 2].tolist() == [0, 0] |
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with_maximum = tio.Pad(add_bottom_row, padding_mode='maximum')(x) |
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assert with_maximum[0, 0, 2].tolist() == [1, 1] |
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with_median = tio.Pad(add_bottom_row, padding_mode='median')(x) |
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assert with_median[0, 0, 2].tolist() == [1, 1] |
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# This is a special case: as we instantiated the tensor with integers, |
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# the mean (3/4) will be trucated to 0. |
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with_mean = tio.Pad(add_bottom_row, padding_mode='mean')(x) |
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assert with_mean[0, 0, 2].tolist() == [0, 0] |
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# So let's test with floats too |
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x = x.float() |
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with_mean = tio.Pad(add_bottom_row, padding_mode='mean')(x) |
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assert with_mean[0, 0, 2].tolist() == [0.75, 0.75] |
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def test_truncation_warning(self): |
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x = torch.ones(1, 1, 2, 2, dtype=torch.int) |
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pad = tio.Pad(1, padding_mode='mean') |
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with pytest.warns(RuntimeWarning): |
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pad(x) |
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TorchIO-project /
torchio
