BUG: Unable to reproduce the "Calculating Climatology and Departures from Time Series Data" Example

[mgrover1]

What happened?

I tried to run through and reproduce the "Calculating Climatology and Departures from Time Series Data" example included in the documentation, but ran into a bounds error.

What did you expect to happen? Are there are possible answers you came across?

I expected to be able to full execute the "Calculating Climatology and Departures from Time Series Data" example, specifically the "Daily Climatology" portion.

Minimal Complete Verifiable Example (MVCE)

import xcdat

filepath2 = "http://esgf.nci.org.au/thredds/dodsC/master/CMIP6/CMIP/CSIRO/ACCESS-ESM1-5/historical/r10i1p1f1/3hr/tas/gn/v20200605/tas_3hr_ACCESS-ESM1-5_historical_r10i1p1f1_gn_201001010300-201501010000.nc"
ds_hourly = xcdat.open_dataset(filepath2, chunks={"time": "auto"})

# Unit adjust (-273.15, K to C)
ds_hourly["tas"] = ds_hourly.tas - 273.15
ds_hourly

daily_climo = ds_hourly.temporal.climatology("tas", freq="day", weighted=True)

Relevant log output

KeyError                                  Traceback (most recent call last)
Cell In[14], line 1
----> 1 daily_climo = ds_hourly.temporal.climatology("tas", freq="day", weighted=True)

File ~/mambaforge/envs/xcdat-dev/lib/python3.12/site-packages/xcdat/temporal.py:512, in TemporalAccessor.climatology(self, data_var, freq, weighted, keep_weights, reference_period, season_config)
    371 """Returns a Dataset with the climatology of a data variable.
    372 
    373 Time bounds are used for generating weights to calculate weighted
   (...)
    508 }
    509 """
    510 self._set_data_var_attrs(data_var)
--> 512 return self._averager(
    513     data_var,
    514     "climatology",
    515     freq,
    516     weighted,
    517     keep_weights,
    518     reference_period,
    519     season_config,
    520 )

File ~/mambaforge/envs/xcdat-dev/lib/python3.12/site-packages/xcdat/temporal.py:762, in TemporalAccessor._averager(self, data_var, mode, freq, weighted, keep_weights, reference_period, season_config)
    760 # Get the data variable and the required time axis metadata.
    761 dv = _get_data_var(ds, data_var)
--> 762 time_bounds = ds.bounds.get_bounds("T", var_key=dv.name)
    764 if self._mode == "average":
    765     dv = self._average(dv, time_bounds)

File ~/mambaforge/envs/xcdat-dev/lib/python3.12/site-packages/xcdat/bounds.py:247, in BoundsAccessor.get_bounds(self, axis, var_key)
    244         bounds_keys = []
    246 if len(bounds_keys) == 0:
--> 247     raise KeyError(
    248         f"No bounds data variables were found for the '{axis}' axis. Make sure "
    249         "the dataset has bound data vars and their names match the 'bounds' "
    250         "attributes found on their related time coordinate variables. "
    251         "Alternatively, you can add bounds with `ds.bounds.add_missing_bounds()` "
    252         "or `ds.bounds.add_bounds()`."
    253     )
    255 bounds: Union[xr.Dataset, xr.DataArray] = self._dataset[
    256     bounds_keys if len(bounds_keys) > 1 else bounds_keys[0]
    257 ].copy()
    259 return bounds

KeyError: "No bounds data variables were found for the 'T' axis. Make sure the dataset has bound data vars and their names match the 'bounds' attributes found on their related time coordinate variables. Alternatively, you can add bounds with `ds.bounds.add_missing_bounds()` or `ds.bounds.add_bounds()`."

Anything else we need to know?

This is related to the JORS review

Environment

INSTALLED VERSIONS

commit: None
python: 3.12.2 | packaged by conda-forge | (main, Feb 16 2024, 20:54:21) [Clang 16.0.6 ]
python-bits: 64
OS: Darwin
OS-release: 23.4.0
machine: arm64
processor: arm
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.14.3
libnetcdf: 4.9.2

xarray: 2024.2.0
pandas: 2.2.1
numpy: 1.26.4
scipy: 1.12.0
netCDF4: 1.6.5
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.3
nc_time_axis: None
iris: None
bottleneck: None
dask: 2024.3.0
distributed: 2024.3.0
matplotlib: 3.8.3
cartopy: None
seaborn: None
numbagg: None
fsspec: 2024.3.0
cupy: None
pint: None
sparse: 0.15.1
flox: None
numpy_groupies: None
setuptools: 69.2.0
pip: 24.0
conda: None
pytest: None
mypy: None
IPython: 8.22.2
sphinx: None

[pochedls]

Thank you for your review! We will fix the documentation here (and ensure docs are up-to-date in general). The daily dataset does not have bounds, which can be added on open (or after open with ds_hourly = ds_hourly.bounds.add_missing_bounds(["T"])):

ds_hourly = xcdat.open_dataset(filepath2, chunks={"time": "auto"}, add_bounds=["T"])

xCDAT used to add the bounds automatically, but we decided that a user should make this decision.

[tomvothecoder]

This is now resolved in #623

[tomvothecoder]

I also checked if this issue was present in the other temporal averaging notebook, but it only uses the monthly file that already has bounds.