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  • to_netcdf with decoded time can create file with inconsistent time:units and time_bounds:units · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
489752548 https://github.com/pydata/xarray/issues/2921#issuecomment-489752548 https://api.github.com/repos/pydata/xarray/issues/2921 MDEyOklzc3VlQ29tbWVudDQ4OTc1MjU0OA== klindsay28 15570875 2019-05-06T19:52:47Z 2019-05-06T19:52:47Z NONE

It looks like ds.time.encoding is not getting set when open_mfdataset is opening multiple files. I suspect that this is leading to the surprising unit for time when the ds is written out. The code below demonstrates that ds.time.encoding is set by open_mfdataset in the single-file case and is not set in the multi-file case. However, ds.time_bounds.encoding is set in both the single- and multi-file cases.

The possibility of this is alluded to the in a comment in #2436, which relates the issue to #1614.

``` import numpy as np import xarray as xr

create time and time_bounds DataArrays for Jan-1850 and Feb-1850

time_bounds_vals = np.array([[0.0, 31.0], [31.0, 59.0]]) time_vals = time_bounds_vals.mean(axis=1)

time_var = xr.DataArray(time_vals, dims='time', coords={'time':time_vals}) time_bounds_var = xr.DataArray(time_bounds_vals, dims=('time', 'd2'), coords={'time':time_vals})

create Dataset of time and time_bounds

ds = xr.Dataset(coords={'time':time_var}, data_vars={'time_bounds':time_bounds_var}) ds.time.attrs = {'bounds':'time_bounds', 'calendar':'noleap', 'units':'days since 1850-01-01'}

write Jan-1850 values to file

ds.isel(time=slice(0,1)).to_netcdf('Jan-1850.nc', unlimited_dims='time')

write Feb-1850 values to file

ds.isel(time=slice(1,2)).to_netcdf('Feb-1850.nc', unlimited_dims='time')

use open_mfdataset to read in files, combining into 1 Dataset

decode_times = True decode_cf = True ds = xr.open_mfdataset(['Jan-1850.nc'], decode_cf=decode_cf, decode_times=decode_times)

print('time and time_bounds encoding, single-file open_mfdataset') print(ds.time.encoding) print(ds.time_bounds.encoding)

use open_mfdataset to read in files, combining into 1 Dataset

decode_times = True decode_cf = True ds = xr.open_mfdataset(['Jan-1850.nc', 'Feb-1850.nc'], decode_cf=decode_cf, decode_times=decode_times)

print('--------------------') print('time and time_bounds encoding, multi-file open_mfdataset') print(ds.time.encoding) print(ds.time_bounds.encoding) ```

produces

``` time and time_bounds encoding, single-file open_mfdataset {'zlib': False, 'shuffle': False, 'complevel': 0, 'fletcher32': False, 'contiguous': False, 'chunksizes': (512,), 'source': '/gpfs/fs1/work/klindsay/analysis/CESM2_coup_carb_cycle_JAMES/Jan-1850.nc', 'original_shape': (1,), 'dtype': dtype('float64'), '_FillValue': nan, 'units': 'days since 1850-01-01', 'calendar': 'noleap'} {'zlib': False, 'shuffle': False, 'complevel': 0, 'fletcher32': False, 'contiguous': False, 'chunksizes': (1, 2), 'source': '/gpfs/fs1/work/klindsay/analysis/CESM2_coup_carb_cycle_JAMES/Jan-1850.nc', 'original_shape': (1, 2), 'dtype': dtype('float64'), '_FillValue': nan, 'units': 'days since 1850-01-01', 'calendar': 'noleap'}

time and time_bounds encoding, multi-file open_mfdataset {} {'zlib': False, 'shuffle': False, 'complevel': 0, 'fletcher32': False, 'contiguous': False, 'chunksizes': (1, 2), 'source': '/gpfs/fs1/work/klindsay/analysis/CESM2_coup_carb_cycle_JAMES/Jan-1850.nc', 'original_shape': (1, 2), 'dtype': dtype('float64'), '_FillValue': nan, 'units': 'days since 1850-01-01', 'calendar': 'noleap'} ```

 
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   to_netcdf with decoded time can create file with inconsistent time:units and time_bounds:units 437418525

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