code: def plot_forecast(
      final_year, companies, noise, show_legend, point_style
  ):
      start_year = 2020
      x = np.arange(start_year, final_year + 1)
      year_count = x.shape[0]
      plt_format = ({"cross": "X", "line": "-", "circle": "o--"})[
          point_style
      ]
      fig = plt.figure()
      ax = fig.add_subplot(111)
      for i, company in enumerate(companies):
          series = np.arange(0, year_count, dtype=float)
          series = series**2 * (i + 1)
          series += np.random.rand(year_count) * noise
          ax.plot(x, series, plt_format)
      if show_legend:
          plt.legend(companies)
      return fig
  
label_desc: Use image node_id 1 for calling a global function with example usage: plot_forecast(final_year, companies, noise, show_legend, point_style) and returns: fig