code: def logprob(self, comp, vals):
      mean = self.mean
      amp2 = self.amp2
      noise = self.noise
  
      cov = amp2 * (
          self.cov_func(self.ls, comp, None)
          + 1e-6 * np.eye(comp.shape[0])
      ) + noise * np.eye(comp.shape[0])
      chol = spla.cholesky(cov, lower=True)
      solve = spla.cho_solve((chol, True), vals - mean)
      lp = -np.sum(np.log(np.diag(chol))) - 0.5 * np.dot(
          vals - mean, solve
      )
      return lp
  
file_path: auptimizer/src/aup/Proposer/spearmint/gp.py
imports: import numpy
  import scipy.linalg
  import scipy.optimize
  import scipy.io
label_desc: Use image node_id 4 for calling the GP obj's underlying member method code with example usage: obj.logprob(comp, vals) and returns: lp