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When a Zarr array uses no compression, if data are stored in a dict, currently data can end up being shared with another array, which could lead to strange and unexpected behaviour. E.g.:
In [31]: a = np.arange(20)
In [32]: z = zarr.zeros(20, chunks=10, compressor=None, dtype=a.dtype)
In [35]: z[:] = a
In [36]: z[:]
Out[36]:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19])
In [37]: a[:] = 0
In [38]: z[:]
Out[38]: array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
The text was updated successfully, but these errors were encountered:
When a Zarr array uses no compression, if data are stored in a dict, currently data can end up being shared with another array, which could lead to strange and unexpected behaviour. E.g.:
The text was updated successfully, but these errors were encountered: