code: def test_plot_edf_with_multiple_studies(
      plot_edf: Callable[..., Any], direction: str, num_studies: int
  ) -> None:
      studies = []
      for _ in range(num_studies):
          study = create_study(direction=direction)
          study.optimize(
              lambda t: t.suggest_float("x", 0, 5), n_trials=10
          )
          studies.append(study)
      figure = plot_edf(studies)
      save_static_image(figure)
  
imports: from __future__ import annotations
  from io import BytesIO
  from typing import Any
  from typing import Callable
  import numpy
  import pytest
  import optuna
  from optuna import Study
  from optuna.study import create_study
  from optuna.testing.visualization import prepare_study_with_trials
  from optuna.trial import create_trial
  from optuna.visualization import plot_edf
  from optuna.visualization._edf import _EDFInfo
  from optuna.visualization._edf import _get_edf_info
  from optuna.visualization._edf import NUM_SAMPLES_X_AXIS
  from optuna.visualization._plotly_imports import _imports
  from optuna.visualization.matplotlib import plot_edf
  from optuna.visualization.matplotlib._matplotlib_imports import _imports
label_desc: Use image node_id 6 for calling a global function with example usage: test_plot_edf_with_multiple_studies(plot_edf, direction, num_studies) without return types