code: def rogers_tanimoto(x, y):
      num_not_equal = 0.0
      for i in range(x.shape[0]):
          x_true = x[i] != 0
          y_true = y[i] != 0
          num_not_equal += x_true != y_true
  
      return (2.0 * num_not_equal) / (x.shape[0] + num_not_equal)
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 27 for calling a global function with example usage: rogers_tanimoto(x, y) and returns: unknown