def select_mask(cls, dataset, selection):
        """
        Given a Dataset object and a dictionary with dimension keys and
        selection keys (i.e. tuple ranges, slices, sets, lists, or literals)
        return a boolean mask over the rows in the Dataset object that
        have been selected.
        """
        mask = None
        for dim, sel in selection.items():
            if isinstance(sel, tuple):
                sel = slice(*sel)
            arr = cls.values(dataset, dim, keep_index=True)
            if util.isdatetime(arr) and util.pd:
                try:
                    sel = util.parse_datetime_selection(sel)
                except:
                    pass

            new_masks = []
            if isinstance(sel, slice):
                with warnings.catch_warnings():
                    warnings.filterwarnings('ignore', r'invalid value encountered')
                    if sel.start is not None:
                        new_masks.append(sel.start <= arr)
                    if sel.stop is not None:
                        new_masks.append(arr < sel.stop)
                if not new_masks:
                    continue
                new_mask = new_masks[0]
                for imask in new_masks[1:]:
                    new_mask &= imask
            elif isinstance(sel, (set, list)):
                for v in sel:
                    new_masks.append(arr==v)
                if not new_masks:
                    continue
                new_mask = new_masks[0]
                for imask in new_masks[1:]:
                    new_mask |= imask
            elif callable(sel):
                new_mask = sel(arr)
            else:
                new_mask = arr == sel

            if mask is None:
                mask = new_mask
            else:
                mask &= new_mask
        return mask