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"""
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
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