def get_locs(self, seq):
        """
        Get location for a given label/slice/list/mask or a sequence of such as
        an array of integers.

        Parameters
        ----------
        seq : label/slice/list/mask or a sequence of such
           You should use one of the above for each level.
           If a level should not be used, set it to ``slice(None)``.

        Returns
        -------
        locs : array of integers suitable for passing to iloc

        Examples
        ---------
        >>> mi = pd.MultiIndex.from_arrays([list('abb'), list('def')])

        >>> mi.get_locs('b')
        array([1, 2], dtype=int64)

        >>> mi.get_locs([slice(None), ['e', 'f']])
        array([1, 2], dtype=int64)

        >>> mi.get_locs([[True, False, True], slice('e', 'f')])
        array([2], dtype=int64)

        See Also
        --------
        MultiIndex.get_loc : Get location for a label or a tuple of labels.
        MultiIndex.slice_locs : Get slice location given start label(s) and
                                end label(s).
        """
        from .numeric import Int64Index

        # must be lexsorted to at least as many levels
        true_slices = [i for (i, s) in enumerate(com.is_true_slices(seq)) if s]
        if true_slices and true_slices[-1] >= self.lexsort_depth:
            raise UnsortedIndexError('MultiIndex slicing requires the index '
                                     'to be lexsorted: slicing on levels {0}, '
                                     'lexsort depth {1}'
                                     .format(true_slices, self.lexsort_depth))
        # indexer
        # this is the list of all values that we want to select
        n = len(self)
        indexer = None

        def _convert_to_indexer(r):
            # return an indexer
            if isinstance(r, slice):
                m = np.zeros(n, dtype=bool)
                m[r] = True
                r = m.nonzero()[0]
            elif com.is_bool_indexer(r):
                if len(r) != n:
                    raise ValueError("cannot index with a boolean indexer "
                                     "that is not the same length as the "
                                     "index")
                r = r.nonzero()[0]
            return Int64Index(r)

        def _update_indexer(idxr, indexer=indexer):
            if indexer is None:
                indexer = Index(np.arange(n))
            if idxr is None:
                return indexer
            return indexer & idxr

        for i, k in enumerate(seq):

            if com.is_bool_indexer(k):
                # a boolean indexer, must be the same length!
                k = np.asarray(k)
                indexer = _update_indexer(_convert_to_indexer(k),
                                          indexer=indexer)

            elif is_list_like(k):
                # a collection of labels to include from this level (these
                # are or'd)
                indexers = None
                for x in k:
                    try:
                        idxrs = _convert_to_indexer(
                            self._get_level_indexer(x, level=i,
                                                    indexer=indexer))
                        indexers = (idxrs if indexers is None
                                    else indexers | idxrs)
                    except KeyError:

                        # ignore not founds
                        continue

                if indexers is not None:
                    indexer = _update_indexer(indexers, indexer=indexer)
                else:
                    # no matches we are done
                    return Int64Index([])._ndarray_values

            elif com.is_null_slice(k):
                # empty slice
                indexer = _update_indexer(None, indexer=indexer)

            elif isinstance(k, slice):

                # a slice, include BOTH of the labels
                indexer = _update_indexer(_convert_to_indexer(
                    self._get_level_indexer(k, level=i, indexer=indexer)),
                    indexer=indexer)
            else:
                # a single label
                indexer = _update_indexer(_convert_to_indexer(
                    self.get_loc_level(k, level=i, drop_level=False)[0]),
                    indexer=indexer)

        # empty indexer
        if indexer is None:
            return Int64Index([])._ndarray_values
        return indexer._ndarray_values
Get location for a given label/slice/list/mask or a sequence of such as
        an array of integers.

        Parameters
        ----------
        seq : label/slice/list/mask or a sequence of such
           You should use one of the above for each level.
           If a level should not be used, set it to ``slice(None)``.

        Returns
        -------
        locs : array of integers suitable for passing to iloc

        Examples
        ---------
        >>> mi = pd.MultiIndex.from_arrays([list('abb'), list('def')])

        >>> mi.get_locs('b')
        array([1, 2], dtype=int64)

        >>> mi.get_locs([slice(None), ['e', 'f']])
        array([1, 2], dtype=int64)

        >>> mi.get_locs([[True, False, True], slice('e', 'f')])
        array([2], dtype=int64)

        See Also
        --------
        MultiIndex.get_loc : Get location for a label or a tuple of labels.
        MultiIndex.slice_locs : Get slice location given start label(s) and
                                end label(s).