---------------------------------------------------------------------------
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.
icclimoutputs 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).