@@ -178,8 +178,8 @@ print some diagnostics, e.g.::
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: blocksize=0)
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Store type : builtins.dict
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No. bytes : 400000000 (381.5M)
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- No. bytes stored : 3702484 (3.5M )
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- Storage ratio : 108.0
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+ No. bytes stored : 3242241 (3.1M )
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+ Storage ratio : 123.4
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Chunks initialized : 100/100
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If you don't specify a compressor, by default Zarr uses the Blosc
@@ -270,8 +270,8 @@ Here is an example using a delta filter with the Blosc compressor::
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Compressor : Blosc(cname='zstd', clevel=1, shuffle=SHUFFLE, blocksize=0)
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Store type : builtins.dict
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No. bytes : 400000000 (381.5M)
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- No. bytes stored : 328085 (320 .4K)
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- Storage ratio : 1219.2
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+ No. bytes stored : 648605 (633 .4K)
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+ Storage ratio : 616.7
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Chunks initialized : 100/100
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For more information about available filter codecs, see the `Numcodecs
@@ -394,8 +394,8 @@ property. E.g.::
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Compressor : Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)
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Store type : zarr.storage.DictStore
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No. bytes : 8000000 (7.6M)
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- No. bytes stored : 34840 (34.0K )
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- Storage ratio : 229.6
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+ No. bytes stored : 33460 (32.7K )
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+ Storage ratio : 239.1
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Chunks initialized : 10/10
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>>> baz.info
@@ -1143,8 +1143,8 @@ ratios, depending on the correlation structure within the data. E.g.::
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Compressor : Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)
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Store type : builtins.dict
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No. bytes : 400000000 (381.5M)
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- No. bytes stored : 15857834 (15.1M )
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- Storage ratio : 25.2
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+ No. bytes stored : 10502688 (10.0M )
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+ Storage ratio : 38.1
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Chunks initialized : 100/100
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>>> f = zarr.array(a, chunks=(1000, 1000), order='F')
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>>> f.info
@@ -1157,8 +1157,8 @@ ratios, depending on the correlation structure within the data. E.g.::
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Compressor : Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)
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Store type : builtins.dict
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No. bytes : 400000000 (381.5M)
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- No. bytes stored : 7233241 (6.9M )
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- Storage ratio : 55 .3
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+ No. bytes stored : 5530511 (5.3M )
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+ Storage ratio : 72 .3
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Chunks initialized : 100/100
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In the above example, Fortran order gives a better compression ratio. This is an
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