code: def test_image_property_drift_check_not_enough_samples(
      coco_visiondata_train, coco_visiondata_test
  ):
      # Arrange
      properties = [
          {
              "name": "with_non_values",
              "method": lambda x: list(
                  np.random.choice([1, None], size=len(x))
              ),
              "output_type": "numerical",
          }
      ]
      check = ImagePropertyDrift(
          numerical_drift_method="EMD",
          min_samples=60,
          image_properties=properties,
      )
  
      # Assert
      assert_that(
          calling(check.run).with_args(
              coco_visiondata_train, coco_visiondata_test
          ),
          raises(NotEnoughSamplesError),
      )
  
file_path: deepchecks/tests/vision/checks/train_test_validation/image_property_drift_test.py
imports: import numpy
  from hamcrest import all_of, assert_that, calling, close_to, equal_to, greater_than, has_entries, has_key, has_length, has_properties, instance_of, raises
  from deepchecks.core import CheckResult
  from deepchecks.core.errors import NotEnoughSamplesError
  from deepchecks.vision.checks import ImagePropertyDrift
  from deepchecks.vision.utils.image_properties import default_image_properties
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 2 for calling a global function with example usage: test_image_property_drift_check_not_enough_samples(coco_visiondata_train, coco_visiondata_test) without return types