issue_comments: 364817111

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https://github.com/pydata/xarray/pull/1528#issuecomment-364817111 https://api.github.com/repos/pydata/xarray/issues/1528 364817111 MDEyOklzc3VlQ29tbWVudDM2NDgxNzExMQ== 6042212 2018-02-12T02:43:43Z 2018-02-12T03:47:48Z CONTRIBUTOR

OK, so the way to do this in pure-zarr appears to be to simply create the appropriate zarr array and set it's dimensions attribute:

ds = xr.Dataset(coords={'b': np.arange(-4, 6, 0.005), 'l': np.arange(150, 72, -0.005), 'v': np.arange(58722.24288, -164706.4225401, -8.2446e2)}, ds.to_zarr(mapping) g = zarr.open_group(mapping) arr = g.zeros(..., shape like l, b, v) arr.attrs['_ARRAY_DIMENSIONS'] = ['l', 'b', 'v']

xr..open_zarr(mapping) now shows the new array, without having to materialize any data into it, and arr can be written to piecemeal - without the convenience of the coordinate mapping, of course.

 
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