normalize_chunks(chunks, shape=None, limit=None, dtype=None, previous_chunks=None)
This takes in a variety of input types and information and produces a full tuple-of-tuples result for chunks, suitable to be passed to Array or rechunk or any other operation that creates a Dask array.
The chunks to be normalized. See examples below for more details
The shape of the array
The maximum block size to target in bytes, if freedom is given to choose
Chunks from a previous array that we should use for inspiration when rechunking auto dimensions. If not provided but auto-chunking exists then auto-dimensions will prefer square-like chunk shapes.
Normalize chunks to tuple of tuples
Specify uniform chunk sizes
This example is valid syntax, but we were not able to check execution>>> from dask.array.core import normalize_chunks
... normalize_chunks((2, 2), shape=(5, 6)) ((2, 2, 1), (2, 2, 2))
Also passes through fully explicit tuple-of-tuples
This example is valid syntax, but we were not able to check execution>>> normalize_chunks(((2, 2, 1), (2, 2, 2)), shape=(5, 6)) ((2, 2, 1), (2, 2, 2))
Cleans up lists to tuples
This example is valid syntax, but we were not able to check execution>>> normalize_chunks([[2, 2], [3, 3]]) ((2, 2), (3, 3))
Expands integer inputs 10 -> (10, 10)
This example is valid syntax, but we were not able to check execution>>> normalize_chunks(10, shape=(30, 5)) ((10, 10, 10), (5,))
Expands dict inputs
This example is valid syntax, but we were not able to check execution>>> normalize_chunks({0: 2, 1: 3}, shape=(6, 6)) ((2, 2, 2), (3, 3))
The values -1 and None get mapped to full size
This example is valid syntax, but we were not able to check execution>>> normalize_chunks((5, -1), shape=(10, 10)) ((5, 5), (10,))
Use the value "auto" to automatically determine chunk sizes along certain dimensions. This uses the limit=
and dtype=
keywords to determine how large to make the chunks. The term "auto" can be used anywhere an integer can be used. See array chunking documentation for more information.
>>> normalize_chunks(("auto",), shape=(20,), limit=5, dtype='uint8') ((5, 5, 5, 5),)
You can also use byte sizes (see dask.utils.parse_bytes
) in place of "auto" to ask for a particular size
>>> normalize_chunks("1kiB", shape=(2000,), dtype='float32') ((250, 250, 250, 250, 250, 250, 250, 250),)
Respects null dimensions
This example is valid syntax, but we were not able to check execution>>> normalize_chunks((), shape=(0, 0)) ((0,), (0,))See :
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.core.auto_chunks
dask.array.core.normalize_chunks
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