code: def test_flipped_bounds(sample_metric_frame):
      """Tests handling of flipped bounds for confidence intervals.
  
      Flipped bounds are when upper_bound is lower than lower_bound.
      """
      with pytest.raises(ValueError) as exc:
          plot_metric_frame(
              sample_metric_frame,
              metrics=["Recall"],
              conf_intervals=["Recall Bounds Flipped"],
          )
      assert str(exc.value) == _CONF_INTERVALS_FLIPPED_BOUNDS_ERROR
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import pytest
  from sklearn.metrics import accuracy_score, confusion_matrix, recall_score
  from sklearn.utils import check_consistent_length
  from fairlearn.experimental.enable_metric_frame_plotting import plot_metric_frame
  from fairlearn.metrics import MetricFrame
  from fairlearn.metrics._plotter import _CONF_INTERVALS_FLIPPED_BOUNDS_ERROR, _CONF_INTERVALS_MUST_BE_ARRAY, _METRIC_FRAME_INVALID_ERROR
  from .data_for_test import g_1, y_p, y_t
label_desc: Use image node_id 9 for calling a global function with example usage: test_flipped_bounds(sample_metric_frame) without return types