docstr: Stop the algorithm if the final function value is known
  
  Specify in options (with ``self.f_min_true = options['f_min']``)
  and the tolerance with ``f_tol = options['f_tol']``
code: def finite_precision(self):
      """
      Stop the algorithm if the final function value is known
  
      Specify in options (with ``self.f_min_true = options['f_min']``)
      and the tolerance with ``f_tol = options['f_tol']``
      """
      # If no minimizer has been found use the lowest sampling value
      self.find_lowest_vertex()
      if self.disp:
          logging.info(f"Lowest function evaluation = {self.f_lowest}")
          logging.info(f"Specified minimum = {self.f_min_true}")
      # If no feasible point was return from test
      if self.f_lowest is None:
          return self.stop_global
  
      # Function to stop algorithm at specified percentage error:
      if self.f_min_true == 0.0:
          if self.f_lowest <= self.f_tol:
              self.stop_global = True
      else:
          pe = (self.f_lowest - self.f_min_true) / abs(self.f_min_true)
          if self.f_lowest <= self.f_min_true:
              self.stop_global = True
              # 2if (pe - self.f_tol) <= abs(1.0 / abs(self.f_min_true)):
              if abs(pe) >= 2 * self.f_tol:
                  warnings.warn(
                      f"A much lower value than expected f* = {self.f_min_true} "
                      f"was found f_lowest = {self.f_lowest}",
                      stacklevel=3,
                  )
          if pe <= self.f_tol:
              self.stop_global = True
  
      return self.stop_global
  
imports: from collections import namedtuple
  import time
  import logging
  import warnings
  import sys
  import numpy
  from scipy import spatial
  from scipy.optimize import OptimizeResult, minimize, Bounds
  from scipy.optimize._optimize import MemoizeJac
  from scipy.optimize._constraints import new_bounds_to_old
  from scipy.optimize._minimize import standardize_constraints
  from scipy._lib._util import _FunctionWrapper
  from scipy.optimize._shgo_lib._complex import Complex
label_desc: Use image node_id 12 for calling the SHGO obj's underlying member method code with example usage: obj.finite_precision() and returns: self, self