xcdat.create_grid#

xcdat.create_grid(x=None, y=None, z=None, attrs=None, **kwargs)[source]#

Creates a grid dataset using the specified axes.

Deprecated since version v0.6.0: **kwargs argument is being deprecated, please migrate to x, y, or z arguments to create future grids.

Parameters:

  • x (Optional[Union[xr.DataArray, Tuple[xr.DataArray]]]) – Data with optional bounds to use for the “X” axis, by default None.

  • y (Optional[Union[xr.DataArray, Tuple[xr.DataArray]]]) – Data with optional bounds to use for the “Y” axis, by default None.

  • z (Optional[Union[xr.DataArray, Tuple[xr.DataArray]]]) – Data with optional bounds to use for the “Z” axis, by default None.

  • attrs (Optional[Dict[str, str]]) – Custom attributes to be added to the generated xr.Dataset.

Returns:

xr.Dataset – Dataset with grid axes.

Examples

Create uniform 2.5 x 2.5 degree grid using create_axis:

>>> # NOTE: `create_axis` returns (axis, bnds)
>>> lat_axis = create_axis("lat", np.arange(-90, 90, 2.5))
>>> lon_axis = create_axis("lon", np.arange(1.25, 360, 2.5))
>>>
>>> grid = create_grid(x=lon_axis, y=lat_axis)

With custom attributes:

>>> grid = create_grid(
>>>    x=lon_axis, y=lat_axis, attrs={"created": str(datetime.date.today())}
>>> )

Create grid using existing xr.DataArray’s:

>>> lat = xr.DataArray(...)
>>> lon = xr.DataArray(...)
>>>
>>> grid = create_grid(x=lon, x=lat)

With existing bounds:

>>> lat_bnds = xr.DataArray(...)
>>> lon_bnds = xr.DataArray(...)
>>>
>>> grid = create_grid(x=(lat, lat_bnds), y=(lon, lon_bnds))

Create vertical grid:

>>> z = create_axis(
>>>   "lev", np.linspace(1000, 1, 20), attrs={"units": "meters", "positive": "down"}
>>> )
>>> grid = create_grid(z=z)