Method test_loading_array

tests/data/test_patch_dataset.py:47–88

(self)

        self.assertEqual(output, expected)

    def test_loading_array(self):
        set_determinism(seed=1234)
        # image dataset
        images = [np.arange(16, dtype=float).reshape(1, 4, 4), np.arange(16, dtype=float).reshape(1, 4, 4)]
        # image patch sampler
        n_samples = 8
        sampler = RandSpatialCropSamples(roi_size=(3, 3), num_samples=n_samples, random_center=True, random_size=False)

        # image level
        patch_intensity = RandShiftIntensity(offsets=1.0, prob=1.0)
        image_ds = Dataset(images, transform=patch_intensity)
        # patch level
        ds = PatchDataset(data=image_ds, patch_func=sampler, samples_per_image=n_samples, transform=patch_intensity)

        np.testing.assert_equal(len(ds), n_samples * len(images))
        # use the patch dataset, length: len(images) x samplers_per_image
        for item in DataLoader(ds, batch_size=2, shuffle=False, num_workers=0):
            np.testing.assert_equal(tuple(item.shape), (2, 1, 3, 3))
        np.testing.assert_allclose(
            item[0],
            np.array(
                [[[4.970372, 5.970372, 6.970372], [8.970372, 9.970372, 10.970372], [12.970372, 13.970372, 14.970372]]]
            ),
            rtol=1e-5,
        )
        if sys.platform != "win32":
            for item in DataLoader(ds, batch_size=2, shuffle=False, num_workers=2):
                np.testing.assert_equal(tuple(item.shape), (2, 1, 3, 3))
            np.testing.assert_allclose(
                item[0],
                np.array(
                    [
                        [
                            [5.028125, 6.028125, 7.028125],
                            [9.028125, 10.028125, 11.028125],
                            [13.028125, 14.028125, 15.028125],
                        ]
                    ]
                ),
                rtol=1e-5,
            )
        set_determinism(seed=None)


if __name__ == "__main__":