Function _dataarray_concat

xarray/structure/concat.py:866–926

(
    arrays: Iterable[T_DataArray],
    dim: Hashable | T_Variable | T_DataArray | pd.Index,
    data_vars: T_DataVars | Iterable[Hashable] | CombineKwargDefault,
    coords: ConcatOptions | Iterable[Hashable] | CombineKwargDefault,
    compat: CompatOptions | CombineKwargDefault,
    positions: Iterable[Iterable[int]] | None,
    fill_value: object,
    join: JoinOptions | CombineKwargDefault,
    combine_attrs: CombineAttrsOptions,
    create_index_for_new_dim: bool,
)

def _dataarray_concat(
    arrays: Iterable[T_DataArray],
    dim: Hashable | T_Variable | T_DataArray | pd.Index,
    data_vars: T_DataVars | Iterable[Hashable] | CombineKwargDefault,
    coords: ConcatOptions | Iterable[Hashable] | CombineKwargDefault,
    compat: CompatOptions | CombineKwargDefault,
    positions: Iterable[Iterable[int]] | None,
    fill_value: object,
    join: JoinOptions | CombineKwargDefault,
    combine_attrs: CombineAttrsOptions,
    create_index_for_new_dim: bool,
) -> T_DataArray:
    from xarray.core.dataarray import DataArray

    arrays = list(arrays)

    if not all(isinstance(array, DataArray) for array in arrays):
        raise TypeError(
            "The elements in the input list need to be either all 'Dataset's or all 'DataArray's"
        )

    # Allow passing `all` or `None` even though we always use `data_vars='all'`
    # when passing off to `_dataset_concat`.
    if not isinstance(data_vars, CombineKwargDefault) and data_vars not in [
        "all",
        None,
    ]:
        raise ValueError(
            "data_vars is not a valid argument when concatenating DataArray objects"
        )

    datasets = []
    for n, arr in enumerate(arrays):
        if n == 0:
            name = arr.name
        elif name != arr.name:
            if compat == "identical":
                raise ValueError("array names not identical")
            else:
                arr = arr.rename(name)
        datasets.append(arr._to_temp_dataset())

    ds = _dataset_concat(
        datasets,
        dim=dim,
        data_vars="all",
        coords=coords,
        compat=compat,
        positions=positions,
        fill_value=fill_value,
        join=join,
        combine_attrs=combine_attrs,
        create_index_for_new_dim=create_index_for_new_dim,
    )

    merged_attrs = merge_attrs([da.attrs for da in arrays], combine_attrs)

    result = arrays[0]._from_temp_dataset(ds, name)