code: def test_binary_classification_without_display(
      iris_binary_string_split_dataset_and_model,
  ):
      # Arrange
      train, _, clf = iris_binary_string_split_dataset_and_model
      # Act
      result = RocReport().run(train, clf, with_display=False)
      # Assert
      assert_that(result.value, has_length(1))
      assert_that(result.value, has_entries(b=close_to(0.9, 0.1)))
      assert_that(result.display, has_length(0))
  
file_path: deepchecks/tests/tabular/checks/model_evaluation/roc_report_test.py
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, close_to, greater_than, has_entries, has_items, has_length, raises
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import train_test_split
  from deepchecks.core.errors import DeepchecksNotSupportedError, DeepchecksValueError, ModelValidationError
  from deepchecks.tabular.checks.model_evaluation import RocReport
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 5 for calling a global function with example usage: test_binary_classification_without_display(iris_binary_string_split_dataset_and_model) without return types