issue_comments: 1472766481
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
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| https://github.com/pydata/xarray/pull/7019#issuecomment-1472766481 | https://api.github.com/repos/pydata/xarray/issues/7019 | 1472766481 | IC_kwDOAMm_X85XyKIR | 35968931 | 2023-03-16T21:26:36Z | 2023-03-16T21:26:36Z | MEMBER | Thanks @dcherian ! Once I copied that explicit indexer business I was able to get serialization to and from zarr working with cubed! ```python In [1]: import xarray as xr In [2]: from cubed import Spec In [3]: ds = xr.open_dataset( ...: 'airtemps.zarr', ...: chunks={}, ...: from_array_kwargs={ ...: 'manager': 'cubed', ...: 'spec': Spec(work_dir="tmp", max_mem=20e6), ...: } ...: ) /home/tom/Documents/Work/Code/xarray/xarray/backends/plugins.py:139: RuntimeWarning: 'netcdf4' fails while guessing warnings.warn(f"{engine!r} fails while guessing", RuntimeWarning) /home/tom/Documents/Work/Code/xarray/xarray/backends/plugins.py:139: RuntimeWarning: 'scipy' fails while guessing warnings.warn(f"{engine!r} fails while guessing", RuntimeWarning) In [4]: ds['air'] Out[4]: <xarray.DataArray 'air' (time: 2920, lat: 25, lon: 53)> cubed.Array<array-004, shape=(2920, 25, 53), dtype=float32, chunks=((730, 730, 730, 730), (13, 12), (27, 26))> Coordinates: * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0 * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0 * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00 Attributes: GRIB_id: 11 ... In [5]: ds.isel(time=slice(100, 300)).to_zarr("cubed_subset.zarr") /home/tom/Documents/Work/Code/xarray/xarray/core/dataset.py:2118: SerializationWarning: saving variable None with floating point data as an integer dtype without any _FillValue to use for NaNs return to_zarr( # type: ignore Out[5]: <xarray.backends.zarr.ZarrStore at 0x7f34953033c0> ``` |
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