Discrete Sampling Geometries

See also

1. CF conventions on Discrete Sampling Geometries

2. Dataset.cf.cf_roles

cf_xarray supports identifying variables by the cf_role attribute.

ds = xr.Dataset(
    {"temp": ("x", np.arange(10))},
    coords={"cast": ("x", np.arange(10), {"cf_role": "profile_id"})}
)
ds.cf

Discrete Sampling Geometry:
            CF Roles:   profile_id: ['cast']

Coordinates:
             CF Axes:   X, Y, Z, T: n/a

      CF Coordinates:   longitude, latitude, vertical, time: n/a

       Cell Measures:   area, volume: n/a

      Standard Names:   n/a

              Bounds:   n/a

       Grid Mappings:   n/a

Data Variables:
       Cell Measures:   area, volume: n/a

      Standard Names:   n/a

              Bounds:   n/a

       Grid Mappings:   n/a

Access "cast" using it’s cf_role

ds.cf["profile_id"]

<xarray.DataArray 'cast' (x: 10)> Size: 80B
0 1 2 3 4 5 6 7 8 9
Dimensions without coordinates: x
Attributes:
    cf_role:  profile_id

xarray.DataArray

'cast'

• x: 10

• 0 1 2 3 4 5 6 7 8 9

  array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

• Coordinates: (0)
• Indexes: (0)
• Attributes: (1)

  cf_role :

  profile_id

Find all cf_role variables using Dataset.cf.cf_roles and DataArray.cf.cf_roles

ds.cf.cf_roles

{'profile_id': ['cast']}