code: def _onenormest_m1_power(
      A, p, t=2, itmax=5, compute_v=False, compute_w=False
  ):
      """
      Efficiently estimate the 1-norm of (A - I)^p.
  
      Parameters
      ----------
      A : ndarray
          Matrix whose 1-norm of a power is to be computed.
      p : int
          Non-negative integer power.
      t : int, optional
          A positive parameter controlling the tradeoff between
          accuracy versus time and memory usage.
          Larger values take longer and use more memory
          but give more accurate output.
      itmax : int, optional
          Use at most this many iterations.
      compute_v : bool, optional
          Request a norm-maximizing linear operator input vector if True.
      compute_w : bool, optional
          Request a norm-maximizing linear operator output vector if True.
  
      Returns
      -------
      est : float
          An underestimate of the 1-norm of the sparse matrix.
      v : ndarray, optional
          The vector such that ||Av||_1 == est*||v||_1.
          It can be thought of as an input to the linear operator
          that gives an output with particularly large norm.
      w : ndarray, optional
          The vector Av which has relatively large 1-norm.
          It can be thought of as an output of the linear operator
          that is relatively large in norm compared to the input.
  
      """
      return onenormest(
          _MatrixM1PowerOperator(A, p),
          t=t,
          itmax=itmax,
          compute_v=compute_v,
          compute_w=compute_w,
      )
  
imports: import warnings
  import numpy
  from scipy.linalg._matfuncs_sqrtm import SqrtmError, _sqrtm_triu
  from scipy.linalg._decomp_schur import schur, rsf2csf
  from scipy.linalg._matfuncs import funm
  from scipy.linalg import svdvals, solve_triangular
  from scipy.sparse.linalg._interface import LinearOperator
  from scipy.sparse.linalg import onenormest
  import scipy.special
label_desc: Use image node_id 1 for calling a global function with example usage: _onenormest_m1_power(A, p, t, itmax, compute_v, compute_w) and returns: onenormest