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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
322091500 MDU6SXNzdWUzMjIwOTE1MDA= 2116 time array with mixture of types decoded from non-standard calendar thenaomig 11436996 closed 0     2 2018-05-10T21:27:52Z 2018-05-10T22:04:15Z 2018-05-10T22:04:15Z NONE      

Reading a set of files with 360-day calendar with open_mf_dataset(), yields a time array with a mixture of types cftime._cftime.Datetime360Day and Timestamp. The files are CMIP5 output for HadGEM2-ES. I don't think there is a way to force it to use only cftime type for all times? All times should have the same type so slicing is possible (see below).

python precip = xy.open_mfdataset(dataDir+'prc_day_HadGEM2-ES_rcp85_r1i1p1_*.nc') precip['prc'].time outputs: <xarray.DataArray 'time' (time: 33870)> array([cftime._cftime.Datetime360Day(2005, 12, 1, 12, 0, 0, 0, -1, 331), cftime._cftime.Datetime360Day(2005, 12, 2, 12, 0, 0, 0, -1, 332), cftime._cftime.Datetime360Day(2005, 12, 3, 12, 0, 0, 0, -1, 333), ..., Timestamp('2099-12-28 12:00:00'), Timestamp('2099-12-29 12:00:00'), Timestamp('2099-12-30 12:00:00')], dtype=object) Coordinates: * time (time) object 2005-12-01 12:00:00 2005-12-02 12:00:00 ... Attributes: standard_name: time long_name: time bounds: time_bnds axis: T

Problem description

One consistent type is needed for slicing. It would be fine if they were all type cftime.Datetime360Day, as one could then do the following: python startslice = cftime.Datetime360Day(startYear, 1, 1,0,0,0,0,-1,1) endslice = cftime.Datetime360Day(endYear, 12, 30,23,0,0,0,-1,360) precip.sel(time=slice(startslice,endslice)) but with the mixture of types, this returns a KeyError

Expected Output

For some reason with another set of 360-day calendar files (from HadGEM2-CC for what it's worth) it did decode for me with all one type, the time array looks as expected, and slicing as above works: <xarray.DataArray 'time' (time: 34230)> array([cftime._cftime.Datetime360Day(2005, 12, 1, 12, 0, 0, 0, -1, 331), cftime._cftime.Datetime360Day(2005, 12, 2, 12, 0, 0, 0, -1, 332), cftime._cftime.Datetime360Day(2005, 12, 3, 12, 0, 0, 0, -1, 333), ..., cftime._cftime.Datetime360Day(2100, 12, 28, 12, 0, 0, 0, -1, 358), cftime._cftime.Datetime360Day(2100, 12, 29, 12, 0, 0, 0, -1, 359), cftime._cftime.Datetime360Day(2100, 12, 30, 12, 0, 0, 0, -1, 360)], dtype=object) Coordinates: * time (time) object 2005-12-01 12:00:00 2005-12-02 12:00:00 ... Attributes: standard_name: time long_name: time bounds: time_bnds axis: T

Output of xr.show_versions()

INSTALLED VERSIONS

commit: None python: 2.7.15.final.0 python-bits: 64 OS: Linux OS-release: 3.10.0-693.21.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: None.None

xarray: 0.10.3 pandas: 0.22.0 numpy: 1.14.3 scipy: 1.1.0 netCDF4: 1.4.0 h5netcdf: 0.5.1 h5py: 2.7.1 Nio: None zarr: None bottleneck: 1.2.1 cyordereddict: 1.0.0 dask: 0.17.4 distributed: 1.21.8 matplotlib: 2.2.2 cartopy: 0.16.0 seaborn: 0.8.1 setuptools: 39.1.0 pip: 9.0.3 conda: 4.5.3 pytest: None IPython: 5.6.0 sphinx: None

 
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   completed xarray 13221727 issue

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