code: def test_not_enough_samples(drifted_data):
      # Arrange
      train, test = drifted_data
      check = FeatureDrift(min_samples=1001)
  
      # Assert
      assert_that(
          calling(check.run).with_args(train, test),
          raises(NotEnoughSamplesError),
      )
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_item, has_length, is_not, raises
  from deepchecks.core.errors import NotEnoughSamplesError
  from deepchecks.tabular.checks import FeatureDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 5 for calling a global function with example usage: test_not_enough_samples(drifted_data) without return types