class_docstr: ParEGO implementation based on https://www.cs.bham.ac.uk/~jdk/UKCI-2015.pdf.
  
  Parameters
  ----------
  scenario : Scenario
  rho : float, defaults to 0.05
      A small positive value.
  seed : int | None, defaults to None
class_docstr_tok: ["ParEGO","implementation","based","on","https",":","\/\/www.cs.bham.ac.uk\/~jdk\/UKCI-2015.pdf",".","Parameters","--","--","--","--","--","scenario",":","Scenario","rho",":","float",",","defaults","to","0.05","A","small","positive","value",".","seed",":","int","|","None",",","defaults","to","None"]
code: def __init__(
      self,
      scenario: Scenario,
      rho: float = 0.05,
      seed: int | None = None,
  ):
      super(ParEGO, self).__init__()
  
      if seed is None:
          seed = scenario.seed
  
      self._n_objectives = scenario.count_objectives()
      self._seed = seed
      self._rng = np.random.RandomState(seed)
  
      self._rho = rho
      # Will be set on starting an SMBO iteration
      self._theta: np.ndarray | None = None
  
file_path: SMAC3/smac/multi_objective/parego.py
imports: from __future__ import annotations
  from typing import Any
  import numpy
  from smac.multi_objective.abstract_multi_objective_algorithm import AbstractMultiObjectiveAlgorithm
  from smac.scenario import Scenario
label_desc: Use image node_id 1 to create a new ParEGO object from inherited base classes: AbstractMultiObjectiveAlgorithm with example: obj = ParEGO(scenario, rho, seed)