code: def test_segment_performance_diabetes(
      diabetes_split_dataset_and_model,
  ):
      # Arrange
      _, val, model = diabetes_split_dataset_and_model
  
      # Act
      result = WeakSegmentsPerformance(n_top_features=5).run(val, model)
      segments = result.value["weak_segments_list"]
  
      # Assert
      assert_that(segments, has_length(8))
      assert_that(max(segments.iloc[:, 0]), result.value["avg_score"])
      assert_that(segments.iloc[0, 0], close_to(-95, 1))
      assert_that(segments.iloc[0, 1], equal_to("s2"))
  
file_path: deepchecks/tests/tabular/checks/model_evaluation/weak_segments_performance_test.py
imports: import numpy
  import pandas
  from hamcrest import any_of, assert_that, calling, close_to, equal_to, has_items, has_length, raises
  from sklearn.metrics import f1_score, make_scorer
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.checks import WeakSegmentsPerformance
  from deepchecks.tabular.datasets.classification.phishing import load_data, load_fitted_model
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 1 for calling a global function with example usage: test_segment_performance_diabetes(diabetes_split_dataset_and_model) without return types