code: def log_single_beta(x):
      return (
          np.log(2.0) * (-2.0 * x + 0.5)
          + 0.5 * np.log(2.0 * np.pi / x)
          + 0.125 / x
      )
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 41 for calling a global function with example usage: log_single_beta(x) and returns: unknown