code: def mean_identity(X=None, sample_weight=None, covmats=None):
      r"""Identity matrix corresponding to the matrices dimension.
  
      .. math::
          \mathbf{M} = \mathbf{I}_n
  
      Parameters
      ----------
      X : ndarray, shape (n_matrices, n, n)
          Set of square matrices.
      sample_weight : None
          Not used, here for compatibility with other means.
  
      Returns
      -------
      M : ndarray, shape (n, n)
          Identity matrix.
  
      See Also
      --------
      mean_covariance
      """
      X = _deprecate_covmats(covmats, X)
      M = np.eye(X.shape[-1])
      return M
  
imports: from copy import deepcopy
  import numpy
  import warnings
  from .ajd import ajd_pham
  from .base import sqrtm, invsqrtm, logm, expm, powm
  from .distance import distance_riemann
  from .geodesic import geodesic_riemann
  from .utils import check_weights
label_desc: Use image node_id 6 for calling a global function with example usage: mean_identity(X, sample_weight, covmats) and returns: M