class_docstr: Testing the best point utilities functionality that is not tested in
  main `AxClient` testing suite (`TestServiceAPI`).
class_docstr_tok: ["Testing","the","best","point","utilities","functionality","that","is","not","tested","in","main","`","AxClient","`","testing","suite","(","`","TestServiceAPI","`",")","."]
code: def test_best_raw_objective_point_scalarized(self) -> None:
      exp = get_branin_experiment()
      exp.optimization_config = OptimizationConfig(
          ScalarizedObjective(
              metrics=[get_branin_metric()], minimize=True
          )
      )
      with self.assertRaisesRegex(ValueError, "Cannot identify best "):
          get_best_raw_objective_point(exp)
      self.assertEqual(get_best_parameters(exp, Models), None)
      exp.new_trial(
          generator_run=GeneratorRun(
              arms=[Arm(parameters={"x1": 5.0, "x2": 5.0})]
          )
      ).run().complete()
      exp.fetch_data()
      self.assertEqual(
          get_best_raw_objective_point(exp)[0], {"x1": 5.0, "x2": 5.0}
      )
  
imports: import random
  from typing import List
  from unittest.mock import MagicMock, patch
  import pandas
  import torch
  from ax.core.arm import Arm
  from ax.core.batch_trial import BatchTrial
  from ax.core.data import Data
  from ax.core.generator_run import GeneratorRun
  from ax.core.objective import ScalarizedObjective
  from ax.core.optimization_config import OptimizationConfig
  from ax.core.outcome_constraint import OutcomeConstraint
  from ax.core.types import ComparisonOp
  from ax.exceptions.core import UserInputError
  from ax.modelbridge.cross_validation import AssessModelFitResult
  from ax.modelbridge.registry import Models
  from ax.modelbridge.torch import TorchModelBridge
  from ax.plot.pareto_utils import get_tensor_converter_model
  from ax.service.utils.best_point import _derel_opt_config_wrapper, _is_row_feasible, extract_Y_from_data, get_best_parameters, get_best_raw_objective_point, logger
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import not_none
  from ax.utils.testing.core_stubs import get_branin_experiment, get_branin_metric, get_experiment_with_observations, get_sobol
  from ax.utils.testing.mock import fast_botorch_optimize
label_desc: Use image node_id 5 for calling the TestBestPointUtils obj's underlying member method code with example usage: obj.test_best_raw_objective_point_scalarized() without return types