What is your issue?

When one reads a netCDF file, there is not solution to determine if there is an unlimited dimension, and determine which one.

I really need to be able to handle that. I need to process a variable, and write the result with the exact same informations about dimensions and coordinates, with all attributes and characteristics.

Thanks,

Olivier

``` import xarray as xr, os

print ( '==== Get an example file' ) file = 'tas_Amon_IPSL-CM6A-LR_piControl_r1i1p1f1_gr_185001-234912.nc' h_file = f"https://vesg.ipsl.upmc.fr/thredds/fileServer/cmip6/CMIP/IPSL/IPSL-CM6A-LR/piControl/r1i1p1f1/Amon/tas/gr/v20200326/{file}"

print ( '\n ==== Getting file ') os.system ( f"wget --no-clobber {h_file}")

print ( '\n ==== File header : this file has an unlimited dimension "time"' ) os.system ( f"ncdump -h {file} | head")

dd = xr.open_dataset ( file, decode_times=True, use_cftime=True)

xr.set_options ( display_expand_attrs=True) print ( '\n ==== General information : no information about the unlimited dimension(s)' ) print (dd)

print ( '\n ==== Dimensions : no information about the unlimited dimension(s)') print ( dd.dims )

print ( '\n === Attributes : no information about the unlimited dimension(s)' ) for attr in dd.attrs : print ( f'{attr} : {dd.attrs[attr]}' ) ```

Climatologists often use 'seasonal means', i.e. means over 3 months. Useful periods are DJF for December-January-February, MAM, JJA and SON. groupby or resample are nice functions to compute these seasonal means.

sea for example : https://xarray.pydata.org/en/stable/examples/monthly-means.html https://stackoverflow.com/questions/59234745/is-there-any-easy-way-to-compute-seasonal-mean-with-xarray

But some studies need means over 4 months : DJFM, MAMJ, JJAS and SOND. Would it be feasible that these 4-month periods are recognized by groupby and resample ?

For resample, we define 3-month means with a syntax like : resample(time='QS-DEC')

A resampling over 4 months is more tricky : it is not a real resampling, as some months are repeated. We still need 4 seasonal values ...

Thanks,

Olivier

When I create a DataSet from DataArrays, attributes are lost.

When are create attributes in a DataSet, they are know shown by print (DataSet), but are written in the NetCDF file.

Below is python code showing the xarray behaviour in details.

My requests : * When creating a DataSet from DataArrays, DataArrays attributes should be incorporated in the DataSet. (maybe optional) * Attributes present in a DataSet should appear with a print (DataSet). Like for DataArrays.

Thanks,

Olivier

```python

!/usr/bin/env python

coding: utf-8

import numpy as np import xarray as xr

Creates DataArrays

nt = 4 time = np.arange (nt) * 86400.0 time = xr.DataArray (time, coords=[time,], dims=["time",]) aa = time * 2.0

Adding attributes to DataArrays

time.attrs['units'] = "second" aa.attrs['units'] = "whatever"

Attributes are visible in the DataArrays

print ('----------> time DataArray: ') print (time) print ('----------> aa DataArray : ' ) print (aa) print ('----------> aa attributes : ') print (aa.attrs )

Creating a Dataset

ds = xr.Dataset( { "aa": (["time",], aa), }, coords={"time": (["time",], time), }, )

Attributes are not visible in the Dataset

print ('----------> DataSet before setting attributes') print (ds)

My request #1 : attributes of the DataArrays should be added to the DataSet (may be optional)

print ('----------> Attributes of aa in DataSet : none') print ( ds['aa'].attrs ) print ('----------> Attributes of aa outside DataSet : still here') print ( aa.attrs )

print ('----------> Attributes are not written to the NetCDF file') ds.to_netcdf ('sample1.nc')

Adding attributes directly to the Dataset

ds['time'].attrs['units'] = "second" ds['aa'].attrs['units'] = "whatever"

Attributes are still not visible in the Dataset

print ('----------> DataSet after setting attributes : attributes not shown' ) print (ds)

My request #2 : attributes added to the DataSet should be printed

print ('----------> But they are written in the NetCDF file') ds.to_netcdf ('sample2.nc')

MyRequest : coherency between the DataSet and the NetCDF file

What if I read a NetCDF file

dt = xr.open_dataset ( 'sample2.nc')

print ('----------> DataSet read in a NetCDF file : Attributes are not shown') print (dt)

print ('----------> Attributes of aa in DataSet : present') print ( dt['aa'].attrs )

```