def map(  # type: ignore[override]
        self,
        func: Callable,
        keep_attrs: bool | None = None,
        args: Iterable[Any] = (),
        **kwargs: Any,
    ) -> Dataset:
        """Apply a function to each data variable in this dataset

        Parameters
        ----------
        func : callable
            Function which can be called in the form `func(x, *args, **kwargs)`
            to transform each DataArray `x` in this dataset into another
            DataArray.
        keep_attrs : bool | None, optional
            If True, both the dataset's and variables' attributes (`attrs`) will be
            copied from the original objects to the new ones. If False, the new dataset
            and variables will be returned without copying the attributes.
        args : iterable, optional
            Positional arguments passed on to `func`.
        **kwargs : Any
            Keyword arguments passed on to `func`.

        Returns
        -------
        applied : Dataset
            Resulting dataset from applying ``func`` to each data variable.

        Examples
        --------
        >>> da = xr.DataArray(np.random.randn(2, 3))
        >>> ds = xr.Dataset({"foo": da, "bar": ("x", [-1, 2])})
        >>> ds
        <xarray.Dataset> Size: 64B
        Dimensions:  (dim_0: 2, dim_1: 3, x: 2)
        Dimensions without coordinates: dim_0, dim_1, x
        Data variables:
            foo      (dim_0, dim_1) float64 48B 1.764 0.4002 0.9787 2.241 1.868 -0.9773
            bar      (x) int64 16B -1 2
        >>> ds.map(np.fabs)
        <xarray.Dataset> Size: 64B
        Dimensions:  (dim_0: 2, dim_1: 3, x: 2)
        Dimensions without coordinates: dim_0, dim_1, x
        Data variables:
            foo      (dim_0, dim_1) float64 48B 1.764 0.4002 0.9787 2.241 1.868 0.9773
            bar      (x) float64 16B 1.0 2.0
        """

        # Copied from xarray.Dataset so as not to call type(self), which causes problems (see https://github.com/xarray-contrib/datatree/issues/188).
        # TODO Refactor xarray upstream to avoid needing to overwrite this.
        if keep_attrs is None:
            keep_attrs = _get_keep_attrs(default=False)
        variables = {
            k: maybe_wrap_array(v, func(v, *args, **kwargs))
            for k, v in self.data_vars.items()
        }
        if keep_attrs:
            for k, v in variables.items():
                v._copy_attrs_from(self.data_vars[k])
        attrs = self.attrs if keep_attrs else None
        # return type(self)(variables, attrs=attrs)
        return Dataset(variables, attrs=attrs)
Apply a function to each data variable in this dataset

        Parameters
        ----------
        func : callable
            Function which can be called in the form `func(x, *args, **kwargs)`
            to transform each DataArray `x` in this dataset into another
            DataArray.
        keep_attrs : bool | None, optional
            If True, both the dataset's and variables' attributes (`attrs`) will be
            copied from the original objects to the new ones. If False, the new dataset
            and variables will be returned without copying the attributes.
        args : iterable, optional
            Positional arguments passed on to `func`.
        **kwargs : Any
            Keyword arguments passed on to `func`.

        Returns
        -------
        applied : Dataset
            Resulting dataset from applying ``func`` to each data variable.

        Examples
        --------
        >>> da = xr.DataArray(np.random.randn(2, 3))
        >>> ds = xr.Dataset({"foo": da, "bar": ("x", [-1, 2])})
        >>> ds
        <xarray.Dataset> Size: 64B
        Dimensions:  (dim_0: 2, dim_1: 3, x: 2)
        Dimensions without coordinates: dim_0, dim_1, x
        Data variables:
            foo      (dim_0, dim_1) float64 48B 1.764 0.4002 0.9787 2.241 1.868 -0.9773
            bar      (x) int64 16B -1 2
        >>> ds.map(np.fabs)
        <xarray.Dataset> Size: 64B
        Dimensions:  (dim_0: 2, dim_1: 3, x: 2)
        Dimensions without coordinates: dim_0, dim_1, x
        Data variables:
            foo      (dim_0, dim_1) float64 48B 1.764 0.4002 0.9787 2.241 1.868 0.9773
            bar      (x) float64 16B 1.0 2.0
        
xarray/core/datatree.py