class_docstr: A fitter for GPs in multi-fidelity optimisation. 
class_docstr_tok: ["A","fitter","for","GPs","in","multi-fidelity","optimisation","."]
docstr: Wrapper to pack the domain kernel hyper-parameters into a dictionary. 
code: def _prep_init_domain_kernel_hyperparams(self):
      """Wrapper to pack the domain kernel hyper-parameters into a dictionary."""
      options = self.options
      return self._prep_init_fidel_domain_kernel_hyperparams(
          options.domain_kernel_type,
          self.domain_dim,
          options.domain_matern_nu,
          options.domain_poly_order,
          options.domain_esp_order,
          options.domain_esp_matern_nu,
      )
  
imports: from __future__ import division
  from argparse import Namespace
  import numpy
  from .None import gp_core, mf_gp
  from .None import kernel
  from ..utils.ancillary_utils import get_list_of_floats_as_str
  from ..utils.general_utils import get_sublist_from_indices, map_to_bounds
  from ..utils.option_handler import get_option_specs, load_options
  from ..utils.oper_utils import random_sample_from_discrete_domain
  from ..utils.reporters import get_reporter
label_desc: Use image node_id 20 for calling the EuclideanMFGPFitter obj's underlying member method code with example usage: obj._prep_init_domain_kernel_hyperparams() and returns: self