code: def test_pareto_frontier_raise_error_when_missing_data(self) -> None:
      with self.assertRaises(ValueError):
          pareto_frontier_evaluator(
              model=self.model,
              objective_thresholds=self.objective_thresholds,
              objective_weights=self.objective_weights,
              Yvar=self.Yvar,
          )
  
imports: from contextlib import ExitStack
  from typing import Any, cast, Dict, Tuple
  from unittest import mock
  import numpy
  import torch
  from ax.core.search_space import SearchSpaceDigest
  from ax.models.torch.botorch_moo import MultiObjectiveBotorchModel
  from ax.models.torch.botorch_moo_defaults import get_outcome_constraint_transforms, get_qLogEHVI, get_qLogNEHVI, get_weighted_mc_objective_and_objective_thresholds, infer_objective_thresholds, pareto_frontier_evaluator
  from ax.models.torch.utils import _get_X_pending_and_observed
  from ax.utils.common.testutils import TestCase
  from botorch.utils.datasets import SupervisedDataset
  from botorch.utils.multi_objective.hypervolume import infer_reference_point
  from botorch.utils.sampling import manual_seed
  from botorch.utils.testing import MockModel, MockPosterior
  from torch._tensor import Tensor
label_desc: Use image node_id 2 for calling the FrontierEvaluatorTest obj's underlying member method code with example usage: obj.test_pareto_frontier_raise_error_when_missing_data() without return types