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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1075765204 I_kwDOAMm_X85AHt_U 6055 Unexpected type conversion in variables with _FillValue jp-dark 24235303 closed 0     4 2021-12-09T16:26:54Z 2023-09-13T12:40:14Z 2023-09-13T12:40:13Z CONTRIBUTOR      

What happened: When opening a dataset with an int16 variable with the _FillValue attribute, the variable is converted from type int16 to float32. This was originally reported to the TileDB-CF-Py Git repo that contains a TileDB backend for xarray. See TileDB-CF-Py issue #117.

What you expected to happen: I would expect the type to remain the same when applying the _FillValue.

Minimal Complete Verifiable Example:

Original example from TileDB-CF-Py issue #117 using the TileDB backend. ```python import tiledb import xarray as xr import numpy as np

index = tiledb.Dim(name='index', domain=(0, 3)) domain = tiledb.Domain(index) var = tiledb.Attr(name='var', dtype=np.int16) schema = tiledb.ArraySchema(domain=domain, attrs=[var], sparse=False) tiledb.Array.create('dense_array0', schema)

with tiledb.open('dense_array0', 'w') as A: A[:] = np.array([5, 6, 7, 8], dtype=np.int16)

ds = xr.open_dataset('dense_array0', engine='tiledb') ds['var'].dtype ```

NetCDF example with the same behavior: ```python import netCDF4 import xarray as xr import numpy as np

filename = 'temp_file.nc' with netCDF4.Dataset(filename, mode="w") as group: group.createDimension("index", 4) var = group.createVariable("var", np.int16, ("index",), fill_value=-1) var[:] = np.array([5, 6, 7, 8], dtype=np.int16) dataset = xr.open_dataset(filename) dataset["var"].dtype ```

Anything else we need to know?: * I was able to verify the type conversion from int16 to float32 occurs in the conventions.decode_cf_variables call in the open_dataset method of StoreBackendEntrypoint. * I was able to verify the conversion does not happen if mask_and_scale=False. * Note that TileDB is automatically setting a fill value for all dense numerical arrays, and so we are always setting the _FillValue attribute for variables from the TileDB backend.

Environment: I was able to reproduce this with both xarray 0.19.0 and 0.20.1

 
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   completed xarray 13221727 issue
822419493 MDExOlB1bGxSZXF1ZXN0NTg1MDQ3NjYw 4998 (WIP) Proof-of-concept backend redesign jp-dark 24235303 closed 0     3 2021-03-04T19:11:10Z 2021-09-10T18:03:31Z 2021-09-10T18:03:31Z CONTRIBUTOR   1 pydata/xarray/pulls/4998

This branch is intended to demonstrate how the backend API could be modified to support a generic lazy loading DataStore. It should not be merged into master.

  • [ ] Closes #xxxx
  • [ ] Tests added
  • [ ] Passes pre-commit run --all-files
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull
820480606 MDU6SXNzdWU4MjA0ODA2MDY= 4987 A read-only TileDB backend jp-dark 24235303 closed 0     14 2021-03-02T23:36:46Z 2021-03-11T17:55:28Z 2021-03-09T15:14:37Z CONTRIBUTOR      

This is a feature request for a read-only TileDB backend for reading a dense TileDB array into an xarray Dataset.

 
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   completed xarray 13221727 issue
820485472 MDExOlB1bGxSZXF1ZXN0NTgzNDIxODQ3 4988 feat: Add a read-only TileDB backend jp-dark 24235303 closed 0     2 2021-03-02T23:47:32Z 2021-03-09T15:09:13Z 2021-03-09T15:09:13Z CONTRIBUTOR   0 pydata/xarray/pulls/4988
  • Add TileDB backend using plugin architecture
  • Add backend tests (82% coverage for xarray/backends/tiledb_.py)

  • Add dask/distributed integration tests for both integer and datetime TileDB dimensions.

  • [x] Closes #4987

  • [x] Tests added
  • [x] Passes pre-commit run --all-files
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull

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