class_docstr: A FPA class, inherited from Optimizer.
  
  This is the designed class to define FPA-related
  variables and methods.
  
  References:
      X.-S. Yang. Flower pollination algorithm for global optimization.
      International conference on unconventional computing and natural computation (2012).
docstr: Updates the agent's position based on a global pollination (eq. 1).
  
  Args:
      agent_position: Agent's current position.
      best_position: Best agent's current position.
  
  Returns:
      (np.ndarray): A new position.
docstr_tok: ["Updates","the","agent","'s","position","based","on","a","global","pollination","(","eq",".","1",")",".","Args",":","agent_position",":","Agent","'s","current","position",".","best_position",":","Best","agent","'s","current","position",".","Returns",":","(","np.ndarray",")",":","A","new","position","."]
code: def _global_pollination(
      self, agent_position: np.ndarray, best_position: np.ndarray
  ) -> np.ndarray:
      """Updates the agent's position based on a global pollination (eq. 1).
  
      Args:
          agent_position: Agent's current position.
          best_position: Best agent's current position.
  
      Returns:
          (np.ndarray): A new position.
  
      """
  
      step = d.generate_levy_distribution(self.beta)
      global_pollination = (
          self.eta * step * (best_position - agent_position)
      )
      new_position = agent_position + global_pollination
  
      return new_position
  
imports: import copy
  from typing import Any, Dict, Optional
  import numpy
  import opytimizer.math.distribution
  import opytimizer.math.random
  import opytimizer.utils.exception
  from opytimizer.core import Optimizer
  from opytimizer.core.function import Function
  from opytimizer.core.space import Space
  from opytimizer.utils import logging
label_desc: Use image node_id 8 for calling the FPA obj's underlying member method code with example usage: obj._global_pollination(agent_position, best_position) and returns: new_position