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test_from_ngff_zarr.py
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test_from_ngff_zarr.py
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from ngff_zarr import Methods, to_ngff_zarr, from_ngff_zarr, to_multiscales, to_ngff_image
from zarr.storage import MemoryStore
from ._data import input_images, store_new_multiscales, verify_against_baseline
from dask_image import imread
def test_gaussian_isotropic_scale_factors(input_images):
dataset_name = "cthead1"
image = input_images[dataset_name]
baseline_name = "2_4/DASK_IMAGE_GAUSSIAN.zarr"
multiscales = to_multiscales(image, [2, 4], method=Methods.DASK_IMAGE_GAUSSIAN)
# store_new_multiscales(dataset_name, f'{baseline_name}', multiscales)
verify_against_baseline(dataset_name, baseline_name, multiscales)
def test_from_ngff_zarr(input_images):
dataset_name = "lung_series"
data = imread.imread(input_images[dataset_name])
image = to_ngff_image(data=data,
dims=('z', 'y', 'x'),
scale={'z': 2.5, 'y': 1.40625, 'x': 1.40625},
translation={'z': 332.5, 'y': 360., 'x': 0.0},
name='LIDC2')
multiscales = to_multiscales(image)
multiscales.scale_factors = None
multiscales.method = None
multiscales.chunks = None
baseline_name = "from_ngff_zarr"
# store_new_multiscales(dataset_name, baseline_name, multiscales)
verify_against_baseline(dataset_name, baseline_name, multiscales)
test_store = MemoryStore(dimension_separator='/')
to_ngff_zarr(test_store, multiscales)
multiscales_back = from_ngff_zarr(test_store)
# verify_against_baseline(dataset_name, baseline_name, multiscales_back)