code: def correlation(x, y):
      mu_x = 0.0
      mu_y = 0.0
      norm_x = 0.0
      norm_y = 0.0
      dot_product = 0.0
  
      for i in range(x.shape[0]):
          mu_x += x[i]
          mu_y += y[i]
  
      mu_x /= x.shape[0]
      mu_y /= x.shape[0]
  
      for i in range(x.shape[0]):
          shifted_x = x[i] - mu_x
          shifted_y = y[i] - mu_y
          norm_x += shifted_x**2
          norm_y += shifted_y**2
          dot_product += shifted_x * shifted_y
  
      if norm_x == 0.0 and norm_y == 0.0:
          return 0.0
      elif dot_product == 0.0:
          return 1.0
      else:
          return 1.0 - (dot_product / np.sqrt(norm_x * norm_y))
  
imports: import numpy
  import numba
  from pynndescent.optimal_transport import allocate_graph_structures, initialize_graph_structures, initialize_supply, initialize_cost, network_simplex_core, total_cost, ProblemStatus, sinkhorn_transport_plan
label_desc: Use image node_id 32 for calling a global function with example usage: correlation(x, y) and returns: int, int, unknown