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doco tweaks
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README.rst

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@@ -159,18 +159,18 @@ If you're working with really big arrays, try the 'lazy' option:
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nbytes: 3.6P; cbytes: 0; initialized: 0/1000000000
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mode: w; path: big.zarr
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See the [persistence documentation](PERSISTENCE.rst) for more details of the
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file format.
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See the `persistence documentation <PERSISTENCE.rst>`_ for more
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details of the file format.
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Tuning
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------
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``zarr`` is optimised for accessing and storing data in contiguous slices,
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of the same size or larger than chunks. It is not and will never be
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optimised for single item access.
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``zarr`` is optimised for accessing and storing data in contiguous
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slices, of the same size or larger than chunks. It is not and probably
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never will be optimised for single item access.
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Chunks sizes >= 1M are generally good. Optimal chunk shape will depend on
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the correlation structure in your data.
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Chunks sizes >= 1M are generally good. Optimal chunk shape will depend
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on the correlation structure in your data.
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``zarr`` is designed for use in parallel computations working
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chunk-wise over data. Try it with `dask.array
@@ -179,12 +179,6 @@ multi-threaded, set zarr to use blosc in contextual mode::
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>>> zarr.set_blosc_options(use_context=True)
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If using zarr in a single-threaded context, set zarr to use blosc in
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non-contextual mode, which allows blosc to use multiple threads
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internally::
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>>> zarr.set_blosc_options(use_context=False, nthreads=4)
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Acknowledgments
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---------------
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