How does xcdat's missing_bounds work?

[gkb999]

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• I searched the xCDAT GitHub Discussions to find a similar question and didn't find it.
• I searched the xCDAT documentation and/or Xarray documentation.

Describe your question

Greetings,
My data doesn't have a tim cordinate when I imported (below is an example):

xarray.Dataset
Dimensions:
x: 171y: 128time: 3287bnds: 2
Coordinates:
x  (x) float64 -5.344e+05 -5.281e+05 ... 5.281e+05
y (y) float64 -1.959e+06 ... -1.166e+06
Data variables:
polar_stereographic () int32 ...
z  (time, y, x) float32 ...
x_bnds (x, bnds) float64 -5.375e+05 -5.312e+05 ... 5.312e+05
Indexes:
x PandasIndex
y PandasIndex

Added Time-Cordinates like:

t1.time.attrs["units"] = "days since 2013-01-01"
t1.time.attrs["calendar"] = "proleptic_gregorian"
t1 = xr.decode_cf(t1)

Now the data looks like:

xarray.Dataset
Dimensions: x: 171y: 128time: 3287bnds: 2
Coordinates:
x (x) float64 -5.344e+05 -5.281e+05 ... 5.281e+05
y (y) float64 -1.959e+06 ... -1.166e+06
time (time) datetime64[ns] 2013-01-01 ... 2021-12-31
Data variables:
polar_stereographic () int32 ... 
z (time, y, x) float32 ...
x_bnds (x, bnds) float64 -5.375e+05 -5.312e+05 ... 5.312e+05
xcdat_bounds : True
Indexes:
x PandasIndex
y PandasIndex
time PandasIndex
PandasIndex(DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',
               '2013-01-05', '2013-01-06', '2013-01-07', '2013-01-08',
               '2013-01-09', '2013-01-10',
               ...
               '2021-12-22', '2021-12-23', '2021-12-24', '2021-12-25',
               '2021-12-26', '2021-12-27', '2021-12-28', '2021-12-29',
               '2021-12-30', '2021-12-31'],
              dtype='datetime64[ns]', name='time', length=3287, freq=None))

Here, pandas index of 'time' shows 'freq' as 'None'
So, when I try any of xcdat commands like "temporal accessors"

ds_season = xc_sic.temporal.group_average(
    "z",
    "season",
    season_config={
        "dec_mode": "DJF",}
)

The error abounds BOUNDS appear (below is a sample)

KeyError                                  Traceback (most recent call last)
Cell In[88], line 1
----> 1 ds_season = xc_sic.temporal.group_average(
      2     "z",
      3     "season",
      4     season_config={
      5         "dec_mode": "DJF",}
      6 )

File ~\Anaconda3\envs\xcdat_env\Lib\site-packages\xcdat\temporal.py:340, in TemporalAccessor.group_average(self, data_var, freq, weighted, keep_weights, season_config)
    215 """Returns a Dataset with average of a data variable by time group.
    216 
    217 Parameters
   (...)
    336 }
    337 """
    338 self._set_data_var_attrs(data_var)
--> 340 return self._averager(
    341     data_var,
    342     "group_average",
    343     freq,
    344     weighted=weighted,
    345     keep_weights=keep_weights,
    346     season_config=season_config,
    347 )

File ~\Anaconda3\envs\xcdat_env\Lib\site-packages\xcdat\temporal.py:772, in TemporalAccessor._averager(self, data_var, mode, freq, weighted, keep_weights, reference_period, season_config)
    770 # Get the data variable and the required time axis metadata.
    771 dv = _get_data_var(ds, data_var)
--> 772 time_bounds = ds.bounds.get_bounds("T", var_key=dv.name)
    774 if self._mode == "average":
    775     dv = self._average(dv, time_bounds)

File ~\Anaconda3\envs\xcdat_env\Lib\site-packages\xcdat\bounds.py:218, in BoundsAccessor.get_bounds(self, axis, var_key)
    215         bounds_keys = []
    217 if len(bounds_keys) == 0:
--> 218     raise KeyError(
    219         f"No bounds data variables were found for the '{axis}' axis. Make sure "
    220         "the dataset has bound data vars and their names match the 'bounds' "
    221         "attributes found on their related time coordinate variables. "
    222         "Alternatively, you can add bounds with `xcdat.add_missing_bounds` "
    223         "or `xcdat.add_bounds`."
    224     )
    226 bounds: Union[xr.Dataset, xr.DataArray] = self._dataset[
    227     bounds_keys if len(bounds_keys) > 1 else bounds_keys[0]
    228 ].copy()
    230 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 `xcdat.add_missing_bounds` or `xcdat.add_bounds`."

Now, I'm pretty sure the data doesn't have frequency - I read abound adding missing bounds

Are there are any possible answers you came across?

Relevant discussions:
#411
How are missing bounds handled in xarray and xcdat ?

Here @tomvothecoder talks about adding missing bounds through
`You have the option of adding bounds using xcdat.open_dataset() (by default missing bounds are added) or they can be explicitly added using ds.bounds.add_bounds()``

But, although I don't get an error while adding, it just doesn't work.
How do I add missing bounds in my case please?

From this discussion: #411 (reply in thread)
I want to set : setAxisTimeBoundsDaily but at which stage should I add and how? is my question.

Many Thanks in advance!!

Minimal Complete Verifiable Example (MVCE)

No response

Relevant log output

No response

Environment

NSTALLED VERSIONS

commit: None
python: 3.11.3 | packaged by conda-forge | (main, Apr 6 2023, 08:50:54) [MSC v.1934 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 165 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('English_New Zealand', '1252')
libhdf5: 1.14.0
libnetcdf: 4.9.2

xarray: 2023.4.2
pandas: 2.0.1
numpy: 1.24.3
scipy: 1.10.1
netCDF4: 1.6.3
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.2
nc_time_axis: 1.4.1
PseudoNetCDF: None
iris: None
bottleneck: None
dask: 2023.4.0
distributed: 2023.4.0
matplotlib: 3.7.1
cartopy: 0.21.1
seaborn: 0.12.2
numbagg: None
fsspec: 2023.4.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 67.7.2
pip: 23.1.2
conda: None
pytest: None
mypy: None
IPython: 8.13.1
sphinx: 7.0.0

Anything else we need to know?

No response

[lee1043]

It looks like you are dealing with daily dataset. Can you try below and see if that work?

xc_sic = xc_sic.bounds.add_time_bounds(method="freq", freq="day")

[pochedls]

I think this functionality is not yet released (scheduled for the 0.6.0 release).

[pochedls]

@gkb999 – it is super helpful/important that you post a "complete minimal example." From what you posted above, it seems like you have modified the dataset you are working on (I see pandas indexes in the dataset, which I'm not used to seeing – I think this means you may have taken some intermediate steps). It's also unclear how you opened the dataset, which is relevant to your issue. Could you post code that shows the following:

• The packages you've imported (e.g., import xcdat)
• The command to open the dataset (e.g., ds = xc.open_dataset("...")
• Any other commands (e.g., the axis information you added and anything else you did)
• The command that produces the error (e.g., ds_season = ds.temporal.group_average(...))

Also – it seems like you open the dataset and then manually decode the time axis. I suspect you may not have opened the dataset with xcdat, which defaults to decoding the time axis (and adding missing bounds, if need be). So if that is correct, you need to add the bounds yourself. You can do this manually, but the error message also give you some options. For example, did you try:

ds = ds.bounds.add_missing_bounds()

[gkb999]

@pochedls
This worked 12 hrs back - when I restarted and added bounds using :
ds = ds.bounds.add_missing_bounds()

Sorry for the late update (it was night for me).
Many thanks