| """ | |
| Copyright 2021, Dana-Farber Cancer Institute and Weill Cornell Medicine | |
| License: GNU GPL 2.0 | |
| """ | |
| import copy | |
| import numpy as np | |
| from pathml.core import HESlide | |
| from pathml.preprocessing.pipeline import Pipeline | |
| def test_h5manager(example_slide_data): | |
| """ | |
| See issue #181. | |
| """ | |
| pipe = Pipeline([]) | |
| example_slide_data.run(pipe, distributed=False, tile_size=200) | |
| for tile in example_slide_data.tiles: | |
| assert np.count_nonzero(tile.image) > 0 | |
| def test_h5manager2(tileHE): | |
| slidedata1 = HESlide("tests/testdata/small_HE.svs") | |
| slidedata2 = HESlide("tests/testdata/small_HE.svs") | |
| tiles1 = slidedata1.tiles | |
| tiles2 = slidedata2.tiles | |
| coordslist = [(0, 0), (0, 500), (0, 0)] | |
| for coord in coordslist[0:2]: | |
| tile = copy.deepcopy(tileHE) | |
| tile.coords = coord | |
| tiles1.add(tile) | |
| for coord in coordslist: | |
| tile = copy.deepcopy(tileHE) | |
| tile.coords = coord | |
| tiles2.add(tile) | |
| for tile1, tile2 in zip(tiles1, tiles2): | |
| np.testing.assert_array_equal(tile1.image, tile2.image) | |
| def test_tile_dtype_HE(tileHE): | |
| """make sure that retrieved tiles and corresponding masks are float16""" | |
| slidedata = HESlide("tests/testdata/small_HE.svs") | |
| slidedata.tiles.add(tileHE) | |
| tile_retrieved = slidedata.tiles[tileHE.coords] | |
| assert tile_retrieved.image.dtype == np.float16 | |
| assert tile_retrieved.masks["testmask"].dtype == np.float16 | |
| def test_tile_dtype_IF(tileVectra, vectra_slide): | |
| """make sure that retrieved tiles and corresponding masks are float16""" | |
| vectra_slide.tiles.add(tileVectra) | |
| tile_retrieved = vectra_slide.tiles[tileVectra.coords] | |
| assert tile_retrieved.image.dtype == np.float16 | |
| assert tile_retrieved.masks["testmask"].dtype == np.float16 | |