issue_comments: 42835510
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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/66#issuecomment-42835510 | https://api.github.com/repos/pydata/xarray/issues/66 | 42835510 | MDEyOklzc3VlQ29tbWVudDQyODM1NTEw | 514053 | 2014-05-12T14:04:11Z | 2014-05-12T14:04:11Z | CONTRIBUTOR | @alimanfoo Glad you're enjoying xray! From your description it sounds like it should be relatively simple for you to get xray working with your dataset. NetCDF4 is a subset of h5py and simply adding dimension scales should get you most of the way there. Re: groups, each xray.Dataset corresponds to one HDF5 group. So while xray doesn't currently support groups, you could split your HDF5 dataset into separate files for each group and load those files using xray. Alternatively (if you feel ambitious) it shouldn't be too hard to get xray's NetCDF4DataStore (backends.netCDF4_.py) to work with groups, allowing you to do something like:
This gives some good examples of how groups work within the netCDF4. Also, as @shoyer mentioned, it might make sense to modify xray so that NetCDF4 support is obtained by wrapping h5py instead of netCDF4 which might make your life even easier. |
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