code: def _onenormest_matrix_power(
      A,
      p,
      t=2,
      itmax=5,
      compute_v=False,
      compute_w=False,
      structure=None,
  ):
      """
      Efficiently estimate the 1-norm of A^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 scipy.sparse.linalg.onenormest(
          MatrixPowerOperator(A, p, structure=structure)
      )
  
imports: from __future__ import division, print_function, absolute_import
  import math
  import numpy
  import scipy.special
  from scipy.linalg.basic import solve, solve_triangular
  from scipy.sparse.base import isspmatrix
  from scipy.sparse.construct import eye
  from scipy.sparse.linalg import spsolve
  import scipy.sparse
  import scipy.sparse.linalg
  from scipy.sparse.linalg.interface import LinearOperator
label_desc: Use image node_id 7 for calling a global function with example usage: _onenormest_matrix_power(A, p, t, itmax, compute_v, compute_w, structure) and returns: scipy