class_docstr: A WCA class, inherited from Optimizer.
  
  This is the designed class to define WCA-related
  variables and methods.
  
  References:
      H. Eskandar.
      Water cycle algorithm – A novel metaheuristic optimization method for
      solving constrained engineering optimization problems.
      Computers & Structures (2012).
class_docstr_tok: ["A","WCA","class",",","inherited","from","Optimizer",".","This","is","the","designed","class","to","define","WCA-related","variables","and","methods",".","References",":","H.","Eskandar",".","Water","cycle","algorithm","\u2013","A","novel","metaheuristic","optimization","method","for","solving","constrained","engineering","optimization","problems",".","Computers","&","Structures","(","2012",")","."]
docstr: Initialization method.
  
  Args:
      params: Contains key-value parameters to the meta-heuristics.
docstr_tok: ["Initialization","method",".","Args",":","params",":","Contains","key-value","parameters","to","the","meta-heuristics","."]
code: def __init__(self, params: Optional[Dict[str, Any]] = None) -> None:
      """Initialization method.
  
      Args:
          params: Contains key-value parameters to the meta-heuristics.
  
      """
  
      logger.info("Overriding class: Optimizer -> WCA.")
  
      super(WCA, self).__init__()
  
      self.nsr = 2
      self.d_max = 0.1
  
      self.build(params)
  
      logger.info("Class overrided.")
  
imports: 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 1 to create a new WCA object from inherited base classes: Optimizer with example: obj = WCA(params)