code: def haversine(x, y):
      if x.shape[0] != 2:
          raise ValueError(
              "haversine is only defined for 2 dimensional data"
          )
      sin_lat = np.sin(0.5 * (x[0] - y[0]))
      sin_long = np.sin(0.5 * (x[1] - y[1]))
      result = np.sqrt(
          sin_lat**2 + np.cos(x[0]) * np.cos(y[0]) * sin_long**2
      )
      return 2.0 * np.arcsin(result)
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 31 for calling a global function with example usage: haversine(x, y) and returns: unknown