regrid (high-level) with precomputed weights

New in version 0.5.0.

regrid(data, grid=None, *, interpolation='linear', backend='precomputed', inventory='ecmwf')

Regrid the high-level data object (with geography information) using precomputed weights.

Parameters:

• data (fieldlist, field) –

  the input data. The following types are supported:

  • an earthkit-data GRIB fieldlist (requires earthkit-data >= 0.6.0).

  • an earthkit-data GRIB field (requires earthkit-data >= 0.6.0).

  • an xarray.DataArray or xarray.Dataset

• grid (dict) – the gridspec describing the target grid that data will be interpolated onto

• interpolation (str) – the interpolation method. Possible values are linear and nearest-neighbour. For nearest-neighbour the following aliases are also supported: nn, nearest-neighbor.

• inventory (str) –

  the path to the inventory of the precomputed weights. The interpolation only works when the weights are available for the given input grid (automatically determined from the data), target grid and interpolation combination. At present, two inventory types are available:

  • If inventory is “ecmwf” on None, the remote inventory managed by ECMWF is used. In this case the weights are automatically downloaded and stored in a local cache (at "~/.cache/earthkit-regrid") and when it is needed again the cached version is used. See the inventory for the list of supported grid to grid combinations with this backend.

  • If inventory is a local path, a local inventory is used. Please note this in experimental feature only used for development purposes.

Returns:

The same type of data as data containing the interpolated values.

Return type:

fieldlist, field

Raises:

ValueError – if the precomputed weights are not available

The regridding is performed by multiplying the data vector with the interpolation weights, which forms a sparse matrix (sparse matrix) -vector multiplication).