Function from_iris

xarray/convert.py:157–209

Convert an Iris cube into a DataArray

(cube)

def from_iris(cube):
    """Convert an Iris cube into a DataArray"""
    import iris.exceptions

    name = _name(cube)
    if name == "unknown":
        name = None
    dims = []
    for i in range(cube.ndim):
        try:
            dim_coord = cube.coord(dim_coords=True, dimensions=(i,))
            dims.append(_name(dim_coord))
        except iris.exceptions.CoordinateNotFoundError:
            dims.append(f"dim_{i}")

    if len(set(dims)) != len(dims):
        duplicates = [k for k, v in Counter(dims).items() if v > 1]
        raise ValueError(f"Duplicate coordinate name {duplicates}.")

    coords = {}

    for coord in cube.coords():
        coord_attrs = _iris_obj_to_attrs(coord)
        coord_dims = [dims[i] for i in cube.coord_dims(coord)]
        if coord_dims:
            coords[_name(coord)] = (coord_dims, coord.points, coord_attrs)
        else:
            coords[_name(coord)] = ((), coord.points.item(), coord_attrs)

    array_attrs = _iris_obj_to_attrs(cube)
    cell_methods = _iris_cell_methods_to_str(cube.cell_methods)
    if cell_methods:
        array_attrs["cell_methods"] = cell_methods

    # Deal with iris 1.* and 2.*
    cube_data = cube.core_data() if hasattr(cube, "core_data") else cube.data

    # Deal with dask and numpy masked arrays
    dask_array_type = array_type("dask")
    if isinstance(cube_data, dask_array_type):
        from dask.array import ma as dask_ma

        filled_data = dask_ma.filled(cube_data, get_fill_value(cube.dtype))
    elif isinstance(cube_data, np.ma.MaskedArray):
        filled_data = np.ma.filled(cube_data, get_fill_value(cube.dtype))
    else:
        filled_data = cube_data

    dataarray = DataArray(
        filled_data, coords=coords, name=name, attrs=array_attrs, dims=dims
    )
    decoded_ds = decode_cf(dataarray._to_temp_dataset())
    return dataarray._from_temp_dataset(decoded_ds)