code: def test_plotting_output(sample_metric_frame):
      """Tests for the correct output shape and output type."""
      axs = plot_metric_frame(sample_metric_frame).flatten()
      assert len(axs) == 3  # 3 is number of metrics that aren't arrays
      assert isinstance(axs[0], matplotlib.axes.Axes)
  
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 7 for calling a global function with example usage: test_plotting_output(sample_metric_frame) without return types