code: def _sample_ls(self, comp, vals):
      def logprob(ls):
          if np.any(ls < 0) or np.any(ls > self.max_ls):
              return -np.inf
  
          cov = self.amp2 * (
              self.cov_func(ls, comp, None)
              + 1e-6 * np.eye(comp.shape[0])
          ) + self.noise * np.eye(comp.shape[0])
          chol = spla.cholesky(cov, lower=True)
          solve = spla.cho_solve((chol, True), vals - self.mean)
          lp = -np.sum(np.log(np.diag(chol))) - 0.5 * np.dot(
              vals - self.mean, solve
          )
          return lp
  
      self.ls = util.slice_sample(self.ls, logprob, compwise=True)
  
imports: import os
  from ..None import gp
  import sys
  from ..None import util
  import tempfile
  import numpy
  import numpy.random
  import scipy.linalg
  import scipy.stats
  import scipy.optimize
  import pickle
  from ..Locker import *
  from ..helpers import *
  import logging
label_desc: Use image node_id 8 for calling the GPEIChooser obj's underlying member method code with example usage: obj._sample_ls(comp, vals) and returns: lp, unknown