def test_put_probmap_data_dimorder_zxyc(self):
img_path = os.path.join(
base_path, '../test_data/ilastik/dimensionstest/images/*')
label_path = os.path.join(
base_path,
'../test_data/ilastik/dimensionstest/x15_y10_z2_c4_classes2.ilp')
with tempfile.TemporaryDirectory() as tmpdirname:
c = TiffConnector(img_path, 'some/path', savepath=tmpdirname)
d = Dataset(c)
size = (2, 3, 5) # zxy
batch_size = 1
# shape: 1 batch, 4 channels, 2 z, 3 x, 5 y
p = PredictionBatch(d, batch_size, size)
self.assertEqual((1, 4, 2, 3, 5), p[0].pixels().shape)
self.assertEqual((1, 4, 2, 3, 5), p[1].pixels().shape)
p.set_pixel_dimension_order('bzxyc')
self.assertEqual((1, 2, 3, 5, 4), p[0].pixels().shape)
self.assertEqual((1, 2, 3, 5, 4), p[1].pixels().shape)
pixels = p[0].pixels()
for tile in p:
tile.put_probmap_data(pixels)
def test_pixel_dimensions(self):
img_path = os.path.abspath(
os.path.join(base_path, '../test_data/tiffconnector_1/im/*'))
c = io_connector(img_path, '', savepath=self.tmpdir)
d = Dataset(c)
size = (1, 5, 4)
batch_size = 2
p = PredictionBatch(d, batch_size, size)[0]
print(p.pixels().shape)
self.assertEqual((2, 3, 1, 5, 4), p.pixels().shape)
p.set_pixel_dimension_order('bzxyc')
self.assertEqual((2, 1, 5, 4, 3), p.pixels().shape)
