class_docstr: AbstractSolver base class for mystic optimizers.
      
class_docstr_tok: ["AbstractSolver","base","class","for","mystic","optimizers","."]
docstr: decorate the cost function with bounds, penalties, monitors, etc
code: def _update_objective(self):
      """decorate the cost function with bounds, penalties, monitors, etc"""
      # rewrap the cost if the solver has been run
      if False:  # trigger immediately
          self._decorate_objective(*self._cost[1:])
      else:  # delay update until _bootstrap
          self.Finalize()
      return
  
imports: import random
  import numpy
  from numpy import inf, shape, asarray, absolute, asfarray, seterr
  from mystic.tools import wrap_function, wrap_nested, wrap_reducer
  from mystic.tools import wrap_bounds, wrap_penalty, reduced
  from klepto import isvalid, validate
  from collections.abc import Callable
label_desc: Use image node_id 38 for calling the AbstractSolver obj's underlying member method code with example usage: obj._update_objective() without return types