Modify a selection of individual items, by providing the indices (coordinates)
        for each item to be modified.

        Parameters
        ----------
        selection : tuple
            An integer (coordinate) array for each dimension of the array.
        value : scalar or array-like
            Value to be stored into the array.
        fields : str or sequence of str, optional
            For arrays with a structured dtype, one or more fields can be specified to set
            data for.

        Examples
        --------
        Setup a 2-dimensional array::

            >>> import zarr
            >>> import numpy as np
            >>> z = zarr.zeros((5, 5), dtype=int)

        Set data for a selection of items::

            >>> z.set_coordinate_selection(([1, 4], [1, 4]), 1)
            >>> z[...]
            array([[0, 0, 0, 0, 0],
                   [0, 1, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 1]])

        For convenience, this functionality is also available via the `vindex` property.
        E.g.::

            >>> z.vindex[[1, 4], [1, 4]] = 2
            >>> z[...]
            array([[0, 0, 0, 0, 0],
                   [0, 2, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 2]])

        Notes
        -----
        Coordinate indexing is also known as point selection, and is a form of vectorized
        or inner indexing.

        Slices are not supported. Coordinate arrays must be provided for all dimensions
        of the array.

        See Also
        --------
        get_basic_selection, set_basic_selection, get_mask_selection, set_mask_selection,
        get_orthogonal_selection, set_orthogonal_selection, get_coordinate_selection,
        vindex, oindex, __getitem__, __setitem__

def set_coordinate_selection(self, selection, value, fields=None):
        """Modify a selection of individual items, by providing the indices (coordinates)
        for each item to be modified.

        Parameters
        ----------
        selection : tuple
            An integer (coordinate) array for each dimension of the array.
        value : scalar or array-like
            Value to be stored into the array.
        fields : str or sequence of str, optional
            For arrays with a structured dtype, one or more fields can be specified to set
            data for.

        Examples
        --------
        Setup a 2-dimensional array::

            >>> import zarr
            >>> import numpy as np
            >>> z = zarr.zeros((5, 5), dtype=int)

        Set data for a selection of items::

            >>> z.set_coordinate_selection(([1, 4], [1, 4]), 1)
            >>> z[...]
            array([[0, 0, 0, 0, 0],
                   [0, 1, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 1]])

        For convenience, this functionality is also available via the `vindex` property.
        E.g.::

            >>> z.vindex[[1, 4], [1, 4]] = 2
            >>> z[...]
            array([[0, 0, 0, 0, 0],
                   [0, 2, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 0],
                   [0, 0, 0, 0, 2]])

        Notes
        -----
        Coordinate indexing is also known as point selection, and is a form of vectorized
        or inner indexing.

        Slices are not supported. Coordinate arrays must be provided for all dimensions
        of the array.

        See Also
        --------
        get_basic_selection, set_basic_selection, get_mask_selection, set_mask_selection,
        get_orthogonal_selection, set_orthogonal_selection, get_coordinate_selection,
        vindex, oindex, __getitem__, __setitem__

        """

        # guard conditions
        if self._read_only:
            err_read_only()

        # refresh metadata
        if not self._cache_metadata:
            self._load_metadata_nosync()

        # setup indexer
        indexer = CoordinateIndexer(selection, self)

        # handle value - need to flatten
        if not is_scalar(value, self._dtype):
            value = np.asanyarray(value)
        if hasattr(value, 'shape') and len(value.shape) > 1:
            value = value.reshape(-1)

        self._set_selection(indexer, value, fields=fields)