code: def _CO_HistogramAMI_even_2_5(X, smin, smax):
      # Automutual information, m = 2, τ = 5.
      new_min = smin - 0.1
      new_max = smax + 0.1
      bin_width = (new_max - new_min) / 5
  
      histogram = np.zeros((5, 5))
      sumx = np.zeros(5)
      sumy = np.zeros(5)
      v = 1.0 / (len(X) - 2)
      for i in range(len(X) - 2):
          idx1 = int((X[i] - new_min) / bin_width)
          idx2 = int((X[i + 2] - new_min) / bin_width)
  
          histogram[idx1][idx2] += v
          sumx[idx1] += v
          sumy[idx2] += v
  
      nsum = 0
      for i in range(5):
          for n in range(5):
              if histogram[i][n] > 0:
                  nsum += histogram[i][n] * np.log(
                      histogram[i][n] / sumx[i] / sumy[n]
                  )
  
      return nsum
  
imports: import math
  import numpy
  from sktime.utils.numba.njit import njit
label_desc: Use image node_id 26 for calling a global function with example usage: _CO_HistogramAMI_even_2_5(X, smin, smax) and returns: nsum