code: def test_sharp_drop_outliers_range():
      data_counts = np.array(
          [0.6, 0.37, 0.02, 0.005, 0.003, 0.002]
      )  # sharp drop is between 0.37 and 0.02
  
      assert_that(
          sharp_drop_outliers_range(data_counts), equal_to(0.02)
      )
      assert_that(
          sharp_drop_outliers_range(data_counts, 0.99), equal_to(None)
      )
      assert_that(
          sharp_drop_outliers_range(data_counts, 0.4), equal_to(0.02)
      )
      assert_that(
          sharp_drop_outliers_range(
              data_counts, 0.3, max_outlier_percentage=0.05
          ),
          equal_to(0.02),
      )
      assert_that(
          sharp_drop_outliers_range(
              data_counts, 0.3, max_outlier_percentage=0.5
          ),
          equal_to(0.37),
      )
  
      assert_that(
          calling(sharp_drop_outliers_range).with_args([0.1, 0.3]),
          raises(DeepchecksValueError, "Data percents must sum to 1"),
      )
  
imports: import numpy
  from hamcrest import assert_that, calling, close_to, equal_to, raises
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.utils.outliers import EPS, iqr_outliers_range, sharp_drop_outliers_range
label_desc: Use image node_id 3 for calling a global function with example usage: test_sharp_drop_outliers_range() without return types