class_docstr: An HHO class, inherited from Optimizer.
  
  This is the designed class to define HHO-related
  variables and methods.
  
  References:
      A. Heidari et al. Harris hawks optimization: Algorithm and applications.
      Future Generation Computer Systems (2019).
docstr: Wraps Harris Hawks Optimization over all agents and variables.
  
  Args:
      space: Space containing agents and update-related information.
      function: A Function object that will be used as the objective function.
      iteration: Current iteration.
      n_iterations: Maximum number of iterations.
docstr_tok: ["Wraps","Harris","Hawks","Optimization","over","all","agents","and","variables",".","Args",":","space",":","Space","containing","agents","and","update-related","information",".","function",":","A","Function","object","that","will","be","used","as","the","objective","function",".","iteration",":","Current","iteration",".","n_iterations",":","Maximum","number","of","iterations","."]
code: def update(
      self,
      space: Space,
      function: Function,
      iteration: int,
      n_iterations: int,
  ) -> None:
      """Wraps Harris Hawks Optimization over all agents and variables.
  
      Args:
          space: Space containing agents and update-related information.
          function: A Function object that will be used as the objective function.
          iteration: Current iteration.
          n_iterations: Maximum number of iterations.
  
      """
  
      for agent in space.agents:
          E, J = self._calculate_initial_coefficients(
              iteration, n_iterations
          )
          if E >= 1:
              agent.position = self._exploration_phase(
                  space.agents, agent, space.best_agent
              )
          else:
              agent.position = self._exploitation_phase(
                  E, J, space.agents, agent, space.best_agent, function
              )
  
file_path: opytimizer/opytimizer/optimizers/population/hho.py
imports: from typing import Any, Dict, List, Optional, Tuple
  import numpy
  import opytimizer.math.distribution
  import opytimizer.math.random
  from opytimizer.core import Optimizer
  from opytimizer.core.agent import Agent
  from opytimizer.core.function import Function
  from opytimizer.core.space import Space
  from opytimizer.utils import logging
label_desc: Use image node_id 5 for calling the HHO obj's underlying member method code with example usage: obj.update(space, function, iteration, n_iterations) without return types