Comments (4)
Thanks for opening your first issue here at xarray! Be sure to follow the issue template!
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It's not clear to me what changes you're asking for in xarray. If you want to create a new on-disk storage format you can, and you can teach xarray to read it using the backend entrypoint system. Are you asking for something that falls outside of that framework?
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Thank you @TomNicholas for your quick response.
Currently, the interface between Xarray and other multidimensional tools like scipp or NDData only process part of the data because the internal structures of each tool are different.
To have reversible 'lossless round-trip' interfaces it is necessary to define a common data structure and a mapping between this structure and the structure of the tool (here Xarray).
This is what was defined in the proposed format and implemented in the indicated package. This shows for example that an Xarray Dataset can be transformed reversibly into a Scipp Dataset and vice versa or even into JSON data in an equally reversible manner.
To be clearer, my requests for Xarray are as follows:
- does Xarray wish to participate in the definition (or validation) of this common data structure (so as to ensure that it covers all the developments envisaged for Xarray)?
- is Xarray interested in integrating the interface defined towards this structure (or is it better to include it in a third party)?
- is Xarray interested in integrating the defined JSON interface (or is it better to include it in a third party)?
- does Xarray have use cases associated with interfaces between tools (or is this to do with Xarray discussions)?
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Thanks for the clarification @loco-philippe .
Xarray Dataset can be transformed reversibly into a Scipp Dataset and vice versa
That's cool to know!
I'll attempt to answer these questions, but others feel free to correct me.
does Xarray wish to participate in the definition (or validation) of this common data structure (so as to ensure that it covers all the developments envisaged for Xarray)?
is Xarray interested in integrating the interface defined towards this structure (or is it better to include it in a third party)?
I don't really think we need to be active participants until you ask for a specific change in xarray. Our data model is well-defined, and would need a very good reason to change.
is Xarray interested in integrating the defined JSON interface (or is it better to include it in a third party)?
Note that xarray maps well to the zarr format, which already stores all metadata in JSON files. If the numerical data arrays themselves can also be serialized to JSON (e.g. through numpy/numpy#12481), then you have a JSON representation of an entire xarray.Dataset
right there.
is Xarray interested in integrating the defined JSON interface (or is it better to include it in a third party)?
Xarray deliberately tries to make it easy for third parties to write code to serialize/deserialize to any data format they like. Again see our backend entrypoint system. I don't see a need to add any Dataset.to_new_format()
or open_new_format_as_dataset
functions to xarray, because these can live in your third party library (possibly as a BackendEntryPoint
subclass). Once the new format becomes popular then we could consider accepting a PR.
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Related Issues (20)
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- xarray and pyinstaller HOT 3
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- Using the xarray.Dataset.where() function takes up a lot of memory HOT 4
- Unexpected empty spots in xarray quiver plot with hue of masked data HOT 1
- combine_first() fails when DataArrays are read from netcdf HOT 2
- xr.cftime_range fails when using proleptic_gregorian calendar in cftime.datetime object HOT 2
- When opening a zipped Dataset stored under Zarr on a s3 bucket, `botocore.exceptions.NoCredentialsError: Unable to locate credentials` HOT 2
- netCDF4 indexing: `reindex_like` is very slow if dataset not loaded into memory HOT 4
- Mapping DataTree methods over nodes with variables for which the args are invalid
- ENH: Make `_to_dataframe` faster for extension array columns after `pandas` fix
- `isel(multi_index_level_name = MultiIndex.level)` corrupts the MultiIndex HOT 1
- netCDF encoding and decoding issues. HOT 7
- DataArray .rolling() unclear behaviour when center=False HOT 3
- Dataset constructor always coerces 1D data variables with same name as dim to coordinates HOT 10
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