Method _factorize_dummy

xarray/groupers.py:307–340

(self)

        )

    def _factorize_dummy(self) -> EncodedGroups:
        size = self.group.size
        # no need to factorize
        # use slices to do views instead of fancy indexing
        # equivalent to: group_indices = group_indices.reshape(-1, 1)
        group_indices: GroupIndices = tuple(slice(i, i + 1) for i in range(size))
        size_range = np.arange(size)
        full_index: pd.Index
        unique_coord: _DummyGroup | Variable
        if isinstance(self.group, _DummyGroup):
            codes = self.group.to_dataarray().copy(data=size_range)
            unique_coord = self.group
            full_index = pd.RangeIndex(self.group.size)
            coords = Coordinates()
        else:
            codes = self.group.copy(data=size_range, deep=False)
            unique_coord = self.group.variable.to_base_variable()
            full_index = self.group_as_index
            if isinstance(full_index, pd.MultiIndex):
                coords = Coordinates.from_pandas_multiindex(
                    full_index, dim=self.group.name
                )
            else:
                if TYPE_CHECKING:
                    assert isinstance(unique_coord, Variable)
                coords = coordinates_from_variable(unique_coord)

        return EncodedGroups(
            codes=codes,
            group_indices=group_indices,
            full_index=full_index,
            unique_coord=unique_coord,
            coords=coords,
        )


@dataclass