code: def sample_metric_frame():
      return MetricFrame(
          metrics=metrics_dict,
          y_true=y_t,
          y_pred=y_p,
          sensitive_features=g_1,
      )
  
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 6 for calling a global function with example usage: sample_metric_frame() and returns: MetricFrame