code: def __call__(self, x_test):
      distances = x_test[None, :] - self.data[:, None]
  
      idx = (
          np.abs(distances) < 0.1
      )  # distances smaller than that are considered zero
  
      pdfs = np.zeros_like(distances, dtype=np.float)
      pdfs[idx] = 1 - self.bw
      pdfs[~idx] = (
          0.5
          * (1 - self.bw)
          * np.power(self.bw, np.abs(distances[~idx]))
      )
      # reweigh to compensate for boundaries
      pdfs *= self.weights
  
      return pdfs
  
imports: import numpy
  import scipy.optimize
  import ConfigSpace
  from scipy.special import erf
  from pdb import set_trace
label_desc: Use image node_id 2 for calling the WangRyzinOrdinal obj's underlying member method code with example usage: obj.__call__(x_test) and returns: pdfs