issues: 818266159

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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
818266159 MDU6SXNzdWU4MTgyNjYxNTk= 4973 NetCDF encoded data not automatically decoded back into original dtype 625462 closed 0     2 2021-02-28T17:57:33Z 2022-04-09T01:41:22Z 2022-04-09T01:41:22Z NONE      

What happened: When reading in an encoded netCDF4 file, encoded variables are not transformed back to their original dtype in the resulting xarray.

What you expected to happen: As with the raw netCDF4 package, if an xarray.DataArray of dtype float64 is encoded into a netCDF4 file as a float32, it should be converted back to the original float64 when the netCDF4 dataset is read back in.

Minimal Complete Verifiable Example:

python import xarray as xr import numpy as np foo = xr.DataArray(np.random.uniform(size=[100,100]).astype(np.float64)) foo.dtype # float64 ds = xr.Dataset({'foo': foo}) ds.to_netcdf("foo.nc", encoding={'foo': {'dtype': 'float32', 'scale_factor': 1.0, 'add_offset': 0.0}}) ds1 = xr.open_dataset("foo.nc") ds1['foo'].dtype # float32, not float64 as expected

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.7.7 (default, Mar 23 2020, 22:36:06) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 5.4.0-66-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 0.17.0 pandas: 1.1.5 numpy: 1.19.5 scipy: None netCDF4: 1.5.6 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2021.02.0 distributed: None matplotlib: None cartopy: None seaborn: None numbagg: None pint: None setuptools: 49.6.0 pip: 20.2.2 conda: None pytest: None IPython: 7.21.0 sphinx: None 
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