class_docstr: A COA class, inherited from Optimizer.
  
  This is the designed class to define COA-related
  variables and methods.
  
  References:
      J. Pierezan and L. Coelho. Coyote Optimization Algorithm: A New Metaheuristic for Global Optimization Problems.
      IEEE Congress on Evolutionary Computation (2018).
class_docstr_tok: ["A","COA","class",",","inherited","from","Optimizer",".","This","is","the","designed","class","to","define","COA-related","variables","and","methods",".","References",":","J.","Pierezan","and","L.","Coelho",".","Coyote","Optimization","Algorithm",":","A","New","Metaheuristic","for","Global","Optimization","Problems",".","IEEE","Congress","on","Evolutionary","Computation","(","2018",")","."]
docstr: Number of packs.
docstr_tok: ["Number","of","packs","."]
code: def n_p(self) -> int:
      """Number of packs."""
  
      return self._n_p
  
imports: import copy
  from typing import Any, Dict, List, Optional
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.exception
  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 2 for calling the COA obj's underlying member method code with example usage: obj.n_p() and returns: self