code: def plotAccuracy(suite, name):
    
    path = suite.cfgparser.get(name, "path")
    path = os.path.join(path, name)
  
    accuracy = defaultdict(list)
    sensations = defaultdict(list)
  
    for exp in suite.get_exps(path=path):
      params = suite.get_params(exp)
      maxTouches = params["num_sensations"]
      cells = params["cells_per_axis"]
  
      res = suite.get_history(exp, 0, "Correct classification")
      classified = [any(x) for x in res]
      accuracy[cells] = float(sum(classified)) / float(len(classified))
      touches = [np.argmax(x) or maxTouches for x in res]
      sensations[cells] = [np.mean(touches), np.max(touches)]
  
    plt.title("Classification Accuracy")
  
    accuracy = OrderedDict(sorted(accuracy.items(), key=lambda t: t[0]))
    fig, ax1 = plt.subplots()
    ax1.plot(accuracy.keys(), accuracy.values(), "b")
    ax1.set_xlabel("Cells per axis")
    ax1.set_ylabel("Accuracy", color="b")
    ax1.tick_params("y", colors="b")
  
    sensations = OrderedDict(sorted(sensations.items(), key=lambda t: t[0]))
    ax2 = ax1.twinx()
    ax2.set_prop_cycle(linestyle=["-", "--"])
    ax2.plot(sensations.keys(), sensations.values(), "r")
    ax2.set_ylabel("Sensations", color="r")
    ax2.tick_params("y", colors="r")
    ax2.legend(("Mean", "Max"))
  
    # save
    path = suite.cfgparser.get(name, "path")
    plotPath = os.path.join(path, "{}.pdf".format(name))
    plt.savefig(plotPath)
    plt.close()
docs: Plots classification accuracy