code: def test_is_compatible(
      search_space: Dict[str, BaseDistribution], x0: Dict[str, Any]
  ) -> None:
      optimizer = optuna.integration.cma._Optimizer(
          search_space, x0, 0.1, None, {}
      )
  
      # Compatible.
      trial = _create_frozen_trial(
          params=x0, param_distributions=search_space
      )
      assert optimizer._is_compatible(trial)
  
      # Compatible.
      trial = _create_frozen_trial(
          params=x0,
          param_distributions=dict(
              search_space, u=FloatDistribution(-10, 10)
          ),
      )
      assert optimizer._is_compatible(trial)
  
      # Compatible.
      trial = _create_frozen_trial(
          params=dict(x0, unknown=7),
          param_distributions=dict(
              search_space, unknown=FloatDistribution(0, 10)
          ),
      )
      assert optimizer._is_compatible(trial)
  
      # Incompatible ('u' doesn't exist).
      param = dict(x0)
      del param["u"]
      dist = dict(search_space)
      del dist["u"]
      trial = _create_frozen_trial(
          params=param, param_distributions=dist
      )
      assert not optimizer._is_compatible(trial)
  
      # Incompatible (the value of 'u' is out of range).
      trial = _create_frozen_trial(
          params=dict(x0, u=20),
          param_distributions=dict(
              search_space, u=FloatDistribution(-100, 100)
          ),
      )
      assert not optimizer._is_compatible(trial)
  
      # Error (different distribution class).
      trial = _create_frozen_trial(
          params=x0,
          param_distributions=dict(
              search_space, u=IntDistribution(-2, 2)
          ),
      )
      with pytest.raises(ValueError):
          optimizer._is_compatible(trial)
  
imports: import math
  from typing import Any
  from typing import Dict
  from unittest.mock import call
  from unittest.mock import patch
  import warnings
  import _pytest.capture
  import pytest
  import optuna
  from optuna._imports import try_import
  from optuna.distributions import BaseDistribution
  from optuna.distributions import CategoricalDistribution
  from optuna.distributions import FloatDistribution
  from optuna.distributions import IntDistribution
  from optuna.integration.cma import _Optimizer
  from optuna.study._study_direction import StudyDirection
  from optuna.testing.distributions import UnsupportedDistribution
  from optuna.testing.trials import _create_frozen_trial
  from optuna.trial import Trial
  from optuna.trial import TrialState
label_desc: Use image node_id 9 for calling the TestOptimizer obj's underlying member method code with example usage: obj.test_is_compatible(search_space, x0) without return types