icclim time bounds issues

[DamienIrving]

icclim outputs an xarray Dataset with a time bounds axis. For some reason I get the following error when reading CWD index data calculated from AGCD data (i.e. /g/data/xv83/dbi599/indices/cwd_year_AGCD_v1_r005_1900-2021.nc) but not for any other metric or dataset (even other AGCD data/metrics).

---------------------------------------------------------------------------
OverflowError                             Traceback (most recent call last)
File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:261, in decode_cf_datetime(num_dates, units, calendar, use_cftime)
    260 try:
--> 261     dates = _decode_datetime_with_pandas(flat_num_dates, units, calendar)
    262 except (KeyError, OutOfBoundsDatetime, OverflowError):

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:217, in _decode_datetime_with_pandas(flat_num_dates, units, calendar)
    216 warnings.filterwarnings("ignore", "invalid value encountered", RuntimeWarning)
--> 217 pd.to_timedelta(flat_num_dates.min(), delta) + ref_date
    218 pd.to_timedelta(flat_num_dates.max(), delta) + ref_date

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:148, in to_timedelta(arg, unit, errors)
    147 # ...so it must be a scalar value. Return scalar.
--> 148 return _coerce_scalar_to_timedelta_type(arg, unit=unit, errors=errors)

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:156, in _coerce_scalar_to_timedelta_type(r, unit, errors)
    155 try:
--> 156     result = Timedelta(r, unit)
    157 except ValueError:

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/pandas/_libs/tslibs/timedeltas.pyx:1357, in pandas._libs.tslibs.timedeltas.Timedelta.__new__()

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/pandas/_libs/tslibs/timedeltas.pyx:288, in pandas._libs.tslibs.timedeltas.convert_to_timedelta64()

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/pandas/_libs/tslibs/conversion.pyx:125, in pandas._libs.tslibs.conversion.cast_from_unit()

OverflowError: Python int too large to convert to C long

During handling of the above exception, another exception occurred:

OverflowError                             Traceback (most recent call last)
File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:174, in _decode_cf_datetime_dtype(data, units, calendar, use_cftime)
    173 try:
--> 174     result = decode_cf_datetime(example_value, units, calendar, use_cftime)
    175 except Exception:

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:263, in decode_cf_datetime(num_dates, units, calendar, use_cftime)
    262 except (KeyError, OutOfBoundsDatetime, OverflowError):
--> 263     dates = _decode_datetime_with_cftime(
    264         flat_num_dates.astype(float), units, calendar
    265     )
    267     if (
    268         dates[np.nanargmin(num_dates)].year < 1678
    269         or dates[np.nanargmax(num_dates)].year >= 2262
    270     ):

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:195, in _decode_datetime_with_cftime(num_dates, units, calendar)
    193     raise ModuleNotFoundError("No module named 'cftime'")
    194 return np.asarray(
--> 195     cftime.num2date(num_dates, units, calendar, only_use_cftime_datetimes=True)
    196 )

File src/cftime/_cftime.pyx:584, in cftime._cftime.num2date()

File src/cftime/_cftime.pyx:383, in cftime._cftime.cast_to_int()

OverflowError: time values outside range of 64 bit signed integers

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
Input In [24], in <cell line: 1>()
----> 1 cwd_annual_mean['AGCD'] = read_data(
      2     cwd_files['AGCD'], regrid=False, time_bounds=[start_date, end_date]
      3 )

Input In [8], in read_data(infile, regrid, time_bounds)
      1 def read_data(infile, regrid=False, time_bounds=None):
      2     """Read data and calculate annual mean.
      3     
      4     Parameters
   (...)
      9     
     10     """
---> 12     ds = xr.open_dataset(infile, decode_timedelta=False)
     13     if time_bounds:
     14         start_date, end_date = time_bounds

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/backends/api.py:495, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, *args, **kwargs)
    483 decoders = _resolve_decoders_kwargs(
    484     decode_cf,
    485     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)
    491     decode_coords=decode_coords,
    492 )
    494 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
--> 495 backend_ds = backend.open_dataset(
    496     filename_or_obj,
    497     drop_variables=drop_variables,
    498     **decoders,
    499     **kwargs,
    500 )
    501 ds = _dataset_from_backend_dataset(
    502     backend_ds,
    503     filename_or_obj,
   (...)
    510     **kwargs,
    511 )
    512 return ds

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:567, in NetCDF4BackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose)
    565 store_entrypoint = StoreBackendEntrypoint()
    566 with close_on_error(store):
--> 567     ds = store_entrypoint.open_dataset(
    568         store,
    569         mask_and_scale=mask_and_scale,
    570         decode_times=decode_times,
    571         concat_characters=concat_characters,
    572         decode_coords=decode_coords,
    573         drop_variables=drop_variables,
    574         use_cftime=use_cftime,
    575         decode_timedelta=decode_timedelta,
    576     )
    577 return ds

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/backends/store.py:27, in StoreBackendEntrypoint.open_dataset(self, store, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta)
     24 vars, attrs = store.load()
     25 encoding = store.get_encoding()
---> 27 vars, attrs, coord_names = conventions.decode_cf_variables(
     28     vars,
     29     attrs,
     30     mask_and_scale=mask_and_scale,
     31     decode_times=decode_times,
     32     concat_characters=concat_characters,
     33     decode_coords=decode_coords,
     34     drop_variables=drop_variables,
     35     use_cftime=use_cftime,
     36     decode_timedelta=decode_timedelta,
     37 )
     39 ds = Dataset(vars, attrs=attrs)
     40 ds = ds.set_coords(coord_names.intersection(vars))

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/conventions.py:516, in decode_cf_variables(variables, attributes, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime, decode_timedelta)
    509     continue
    510 stack_char_dim = (
    511     concat_characters
    512     and v.dtype == "S1"
    513     and v.ndim > 0
    514     and stackable(v.dims[-1])
    515 )
--> 516 new_vars[k] = decode_cf_variable(
    517     k,
    518     v,
    519     concat_characters=concat_characters,
    520     mask_and_scale=mask_and_scale,
    521     decode_times=decode_times,
    522     stack_char_dim=stack_char_dim,
    523     use_cftime=use_cftime,
    524     decode_timedelta=decode_timedelta,
    525 )
    526 if decode_coords in [True, "coordinates", "all"]:
    527     var_attrs = new_vars[k].attrs

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/conventions.py:364, in decode_cf_variable(name, var, concat_characters, mask_and_scale, decode_times, decode_endianness, stack_char_dim, use_cftime, decode_timedelta)
    362     var = times.CFTimedeltaCoder().decode(var, name=name)
    363 if decode_times:
--> 364     var = times.CFDatetimeCoder(use_cftime=use_cftime).decode(var, name=name)
    366 dimensions, data, attributes, encoding = variables.unpack_for_decoding(var)
    367 # TODO(shoyer): convert everything below to use coders

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:673, in CFDatetimeCoder.decode(self, variable, name)
    671 units = pop_to(attrs, encoding, "units")
    672 calendar = pop_to(attrs, encoding, "calendar")
--> 673 dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)
    674 transform = partial(
    675     decode_cf_datetime,
    676     units=units,
    677     calendar=calendar,
    678     use_cftime=self.use_cftime,
    679 )
    680 data = lazy_elemwise_func(data, transform, dtype)

File /g/data/xv83/dbi599/miniconda3/envs/model-eval/lib/python3.10/site-packages/xarray/coding/times.py:184, in _decode_cf_datetime_dtype(data, units, calendar, use_cftime)
    176     calendar_msg = (
    177         "the default calendar" if calendar is None else f"calendar {calendar!r}"
    178     )
    179     msg = (
    180         f"unable to decode time units {units!r} with {calendar_msg!r}. Try "
    181         "opening your dataset with decode_times=False or installing cftime "
    182         "if it is not installed."
    183     )
--> 184     raise ValueError(msg)
    185 else:
    186     dtype = getattr(result, "dtype", np.dtype("object"))

ValueError: unable to decode time units 'days since 1900-01-01 00:00:00' with "calendar 'proleptic_gregorian'". Try opening your dataset with decode_times=False or installing cftime if it is not installed.