class_docstr: Base class for Gaussian processes. 
class_docstr_tok: ["Base","class","for","Gaussian","processes","."]
docstr: Returns a string representation of the GP. 
docstr_tok: ["Returns","a","string","representation","of","the","GP","."]
code: def __str__(self):
      """Returns a string representation of the GP."""
      return "%s, noise-var=%0.3f (n=%d)" % (
          self._child_str(),
          self.noise_var,
          len(self.Y),
      )
  
imports: from __future__ import division
  from argparse import Namespace
  from itertools import product
  import sys
  import numpy
  from ..distributions.model import Model
  from ..distributions import continuous
  from ..distributions import discrete
  from ..utils.general_utils import stable_cholesky, draw_gaussian_samples, project_symmetric_to_psd_cone, solve_lower_triangular, solve_upper_triangular
  from ..utils.oper_utils import direct_ft_maximise, pdoo_maximise, random_maximise, random_sample_cts_dscr
  from ..utils.option_handler import get_option_specs, load_options
  from ..utils.reporters import get_reporter
label_desc: Use image node_id 13 for calling the GP obj's underlying member method code with example usage: obj.__str__() and returns: unknown