issue_comments: 1042656377
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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/4118#issuecomment-1042656377 | https://api.github.com/repos/pydata/xarray/issues/4118 | 1042656377 | IC_kwDOAMm_X84-Jax5 | 226037 | 2022-02-17T07:39:15Z | 2022-02-17T08:17:51Z | MEMBER | @TomNicholas (cc @mraspaud)
The two main classes of on-disk formats that, I know of, which cannot be always represented in the "group is a Dataset" approach are: - in netCDF following the CF conventions for groups, it is legal for an array to refer to a dimension or a coordinate in a different group and so arrays in the same group may have dimensions with the same name, but different size / coordinate values, (this was the orginal motivation to explore the DataGroup approach) - the current spec for the Next-generation file formats (NGFF) for bio-imaging has all scales of the same 5D data in the same group. (cc @joshmoore) I don't have an example at hand, but my impression is that satellite products that use HDF5 file format also place arrays with inconsistent dimensions / coordinates in the same group. |
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