code: def test_multiple_calls():
      ax = plot_model_comparison(
          x_axis_metric=accuracy_score,
          y_axis_metric=make_derived_metric(
              metric=selection_rate, transform="difference"
          ),
          y_true=y_t,
          y_preds=[y_t],
          sensitive_features=g_1,
          point_labels=False,
          show_plot=False,
          c="red",
          label="True",
      )
  
      plot_model_comparison(
          ax=ax,
          x_axis_metric=accuracy_score,
          y_axis_metric=make_derived_metric(
              metric=selection_rate, transform="difference"
          ),
          y_true=y_t,
          y_preds=[y_p],
          sensitive_features=g_1,
          point_labels=False,
          show_plot=False,
          c="blue",
          label="Pred",
          legend=True,
      )
  
      assert ax.get_xlabel() == "accuracy score"
      assert ax.get_ylabel() == "selection rate, difference"
      assert ax.get_legend_handles_labels()[1] == ["True", "Pred"]
  
imports: from fairlearn.metrics import plot_model_comparison, make_derived_metric, selection_rate
  from sklearn.metrics import accuracy_score
  import numpy
  from .data_for_test import g_1, y_p, y_t
  import pytest
label_desc: Use image node_id 19 for calling a global function with example usage: test_multiple_calls() without return types