Comments (3)
If you read in an image or netcdf into numpy/xarray it will also be of shape (height, width) so I believe it would make more sense to the user if we used (t-bands-y-x) wherever possible.
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In the last discussion it was decided to ensure that the user writes code that works independent of the ordering of the input or output datacube. So they should use named accessors as much as possible. If they do return a datacube that is not in (t, bands, y, x) format then the backend will automatically transpose this to the correct order (using the dimension names as guide).
In the geopyspark-driver we already do this for spatiotemporal UDFs but not yet for spatial UDFs:
https://github.com/Open-EO/openeo-geopyspark-driver/blob/master/openeogeotrellis/geopysparkdatacube.py#L764
I will push a commit for this soon.
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I think this now fixed and can be closed
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Related Issues (20)
- Promote unit test based UDF development
- load_stac: get asset metadata from "item_assets" in collection instead of from items HOT 4
- load_stac() -> metadata_from_stac() Long error HOT 3
- Improve docs on MultiBackendJobManager
- Include UDF context parameters when using execute_local_udf
- refresh token info logs contradict each other HOT 3
- MultiBackendJobManager.run_jobs() doesn't add new jobs to existing job_tracker HOT 2
- How to get "Open-EO-Costs" from synchronous `download` HOT 4
- Keep polling after computer went to sleep
- Internal: Server error: KazooTimeoutError('Connection time-out') HOT 1
- Add method to load the results of a previous job HOT 1
- Reduce_temporal throws MetadataException after load_stac HOT 4
- support "identy" callbacks HOT 2
- Rename/deprecated `BatchJob.run_synchronous`
- JobManager: store joblist on http url as Parquet
- `metadata_from_stac` can't handle STAC API ItemCollection HOT 1
- OpenEO produced image with spatial distortion and discontinuities as compared with original image HOT 2
- Support unordered band collection in BandDimension
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- GitHub Actions warnings
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