code: def _burkardt_13_power(n, p):
      """
      A helper function for testing matrix functions.
  
      Parameters
      ----------
      n : integer greater than 1
          Order of the square matrix to be returned.
      p : non-negative integer
          Power of the matrix.
  
      Returns
      -------
      out : ndarray representing a square matrix
          A Forsythe matrix of order n, raised to the power p.
  
      """
      # Input validation.
      if n != int(n) or n < 2:
          raise ValueError("n must be an integer greater than 1")
      n = int(n)
      if p != int(p) or p < 0:
          raise ValueError("p must be a non-negative integer")
      p = int(p)
  
      # Construct the matrix explicitly.
      a, b = divmod(p, n)
      large = np.power(10.0, -n * a)
      small = large * np.power(10.0, -n)
      return np.diag([large] * (n - b), b) + np.diag([small] * b, b - n)
  
imports: from __future__ import division, print_function, absolute_import
  import math
  import numpy
  from numpy import array, eye, exp, random
  from numpy.linalg import matrix_power
  from numpy.testing import assert_allclose, assert_, assert_array_almost_equal, assert_equal, assert_array_almost_equal_nulp
  from scipy._lib._numpy_compat import suppress_warnings
  from scipy.sparse import csc_matrix, SparseEfficiencyWarning
  from scipy.sparse.construct import eye
  from scipy.sparse.linalg.matfuncs import expm, _expm, ProductOperator, MatrixPowerOperator, _onenorm_matrix_power_nnm
  from scipy.sparse.sputils import matrix
  from scipy.linalg import logm
  from scipy.special import factorial, binom
  import scipy.sparse
  import scipy.sparse.linalg
label_desc: Use image node_id 1 for calling a global function with example usage: _burkardt_13_power(n, p) and returns: unknown