@classmethod
def make_empty_like(cls, sparsemap, nside_coverage=None, nside_sparse=None,
    dtype=None, primary=None, sentinel=None, wide_mask_maxbits=None,
    metadata=None):
    """
        Make an empty map with the same parameters as an existing map.

        Parameters
        ----------
        sparsemap : `HealSparseMap`
           Sparse map to use as basis for new empty map.
        nside_coverage : `int`, optional
           Coverage nside, default to sparsemap.nside_coverage
        nside_sparse : `int`, optional
           Sparse map nside, default to sparsemap.nside_sparse
        dtype : `str` or `list` or `np.dtype`, optional
           Datatype, any format accepted by numpy.  Default is sparsemap.dtype
        primary : `str`, optional
           Primary key for recarray.  Default is sparsemap.primary
        sentinel : `int` or `float`, optional
           Sentinel value.  Default is sparsemap._sentinel
        wide_mask_maxbits : `int`, optional
           Create a "wide bit mask" map, with this many bits.
        metadata : `dict`-like, optional
           Map metadata that can be stored in FITS header format.

        Returns
        -------
        healSparseMap : `HealSparseMap`
           HealSparseMap filled with sentinel values.
        """
    if nside_coverage is None:
        nside_coverage = sparsemap.nside_coverage
    if nside_sparse is None:
        nside_sparse = sparsemap.nside_sparse
    if dtype is None:
        dtype = sparsemap.dtype
    if primary is None:
        primary = sparsemap.primary
    if sentinel is None:
        sentinel = sparsemap._sentinel
    if wide_mask_maxbits is None:
        if sparsemap._is_wide_mask:
            wide_mask_maxbits = sparsemap._wide_mask_maxbits
    if metadata is None:
        metadata = sparsemap._metadata
    return cls.make_empty(nside_coverage, nside_sparse, dtype, primary=
        primary, sentinel=sentinel, wide_mask_maxbits=wide_mask_maxbits,
        metadata=metadata)
