code: def approx_log_Gamma(x):
      if x == 1:
          return 0
      # x2= 1/(x*x);
      return (
          x * np.log(x)
          - x
          + 0.5 * np.log(2.0 * np.pi / x)
          + 1.0 / (x * 12.0)
      )
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 39 for calling a global function with example usage: approx_log_Gamma(x) and returns: unknown, int