code: def russellrao(x, y):
      num_true_true = 0.0
      for i in range(x.shape[0]):
          x_true = x[i] != 0
          y_true = y[i] != 0
          num_true_true += x_true and y_true
  
      if num_true_true == np.sum(x != 0) and num_true_true == np.sum(
          y != 0
      ):
          return 0.0
      else:
          return float(x.shape[0] - num_true_true) / (x.shape[0])
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 28 for calling a global function with example usage: russellrao(x, y) and returns: int, unknown