code: def x2y(self):
      self.Y_raw = self.func(self.X)
      if not self.has_constraint:
          self.Y = self.Y_raw
      else:
          # constraint
          penalty_eq = np.array(
              [
                  np.sum(np.abs([c_i(x) for c_i in self.constraint_eq]))
                  for x in self.X
              ]
          )
          penalty_ueq = np.array(
              [
                  np.sum(
                      np.abs(
                          [
                              max(0, c_i(x))
                              for c_i in self.constraint_ueq
                          ]
                      )
                  )
                  for x in self.X
              ]
          )
          self.Y = self.Y_raw + 1e5 * penalty_eq + 1e5 * penalty_ueq
      return self.Y
  
imports: import numpy
  from .base import SkoBase
  from sko.tools import func_transformer
  from abc import ABCMeta, abstractmethod
  from .operators import crossover, mutation, ranking, selection
label_desc: Use image node_id 3 for calling the GeneticAlgorithmBase obj's underlying member method code with example usage: obj.x2y() and returns: self