code: def parzen_estimation(x_samples, point_x, h):
      k_n = 0
      for row in x_samples:
          x_i = (point_x - row[:, np.newaxis]) / (h)
          for row in x_i:
              if np.abs(row) > (1 / 2):
                  break
          else:  # "completion-else"*
              k_n += 1
      return (h, (k_n / len(x_samples)) / (h ** point_x.shape[1]))
  
imports: from fiber import Pool
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: parzen_estimation(x_samples, point_x, h) and returns: h,  unknown