code: def plot_certified_accuracy_one_sigma_best_model_multiple_methods(
      outfile: str,
      title: str,
      max_radius: float,
      methods_labels_colors_dashes: List,
      radius_step: float = 0.01,
      upper_bounds=False,
      sigma=0.25,
  ) -> None:
      for it, (methods, label, color, dashes) in enumerate(
          methods_labels_colors_dashes
      ):
          methods_sigma = [
              method
              for method in methods
              if "{:.2f}".format(sigma)
              in method.quantity.data_file_path
          ]
          accuracies_cert_ours, radii = _get_accuracies_at_radii(
              methods_sigma, 0, max_radius, radius_step
          )
          accuracies_cert_ours = np.nan_to_num(accuracies_cert_ours, -1)
          plt.plot(
              radii,
              accuracies_cert_ours[
                  accuracies_cert_ours[:, 0].argmax(), :
              ],
              color,
              dashes=dashes,
              linewidth=2,
              label=label,
          )
  
      plt.ylim((0, 1))
      plt.xlim((0, max_radius))
      plt.tick_params(labelsize=14)
      plt.xlabel("$\ell_2$ radius", fontsize=16)
      plt.ylabel("Certified Accuracy", fontsize=16)
      plt.gca().xaxis.set_major_locator(plt.MultipleLocator(0.5))
      plt.legend(loc="upper right", fontsize=16)
      plt.tight_layout()
      plt.savefig(outfile + ".pdf")
      plt.title(title, fontsize=20)
      plt.tight_layout()
      plt.savefig(outfile + ".png", dpi=300)
      plt.close()
  
imports: from easydict import EasyDict
  from typing import *
  import math
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import os
  import pandas
  import seaborn
label_desc: Use image node_id 4 for calling a global function with example usage: plot_certified_accuracy_one_sigma_best_model_multiple_methods(outfile, title, max_radius, methods_labels_colors_dashes, radius_step, upper_bounds, sigma) without return types