Closed tcompa closed 2 months ago
I run scripts 0 and 1, as a setup, and then rechunk all multiscale levels
$ python rechunk_zarr.py old_array=dask.array<from-zarr, shape=(3, 1, 2160, 5120), dtype=uint16, chunksize=(1, 1, 2160, 2560), chunktype=numpy.ndarray> new_array=dask.array<rechunk-merge, shape=(3, 1, 2160, 5120), dtype=uint16, chunksize=(1, 1, 50, 50), chunktype=numpy.ndarray> old_array=dask.array<from-zarr, shape=(3, 1, 1080, 2560), dtype=uint16, chunksize=(1, 1, 1080, 2560), chunktype=numpy.ndarray> new_array=dask.array<rechunk-merge, shape=(3, 1, 1080, 2560), dtype=uint16, chunksize=(1, 1, 50, 50), chunktype=numpy.ndarray> old_array=dask.array<from-zarr, shape=(3, 1, 540, 1280), dtype=uint16, chunksize=(1, 1, 540, 1280), chunktype=numpy.ndarray> new_array=dask.array<rechunk-merge, shape=(3, 1, 540, 1280), dtype=uint16, chunksize=(1, 1, 50, 50), chunktype=numpy.ndarray> old_array=dask.array<from-zarr, shape=(3, 1, 270, 640), dtype=uint16, chunksize=(1, 1, 270, 640), chunktype=numpy.ndarray> new_array=dask.array<rechunk-merge, shape=(3, 1, 270, 640), dtype=uint16, chunksize=(1, 1, 50, 50), chunktype=numpy.ndarray> old_array=dask.array<from-zarr, shape=(3, 1, 135, 320), dtype=uint16, chunksize=(1, 1, 135, 320), chunktype=numpy.ndarray> new_array=dask.array<rechunk-merge, shape=(3, 1, 135, 320), dtype=uint16, chunksize=(1, 1, 50, 50), chunktype=numpy.ndarray>
And here is the content of 20200812-CardiomyocyteDifferentiation14-Cycle1_mip.zarr/B/03/0/0/.zarray:
20200812-CardiomyocyteDifferentiation14-Cycle1_mip.zarr/B/03/0/0/.zarray
{ "chunks": [ 1, 1, 50, 50 ], "compressor": { "blocksize": 0, "clevel": 5, "cname": "lz4", "id": "blosc", "shuffle": 1 }, "dimension_separator": "/", "dtype": "<u2", "fill_value": 0, "filters": null, "order": "C", "shape": [ 3, 1, 2160, 5120 ], "zarr_format": 2 }
I run scripts 0 and 1, as a setup, and then rechunk all multiscale levels
And here is the content of
20200812-CardiomyocyteDifferentiation14-Cycle1_mip.zarr/B/03/0/0/.zarray
: