def generate_roc_curve(rocs, output_file):
    grey = (0.7, 0.7, 0.7, 0.7)
    figure = pyplot.figure()
    titles = ["Euclidean", "City Block", "Correlation"]
    legends = []
    plots = []
    index = 0

    # Draw ROC line
    subplot = pyplot.subplot(1, 1, 1)
    subplot.plot([0, 1], [1, 0], color=grey)

    # Plot each line
    for roc, eer in rocs:
        plots.extend(subplot.plot(roc[0], roc[1]))
        subplot.plot(eer, 1 / eer, 'x', color='r')

        # Include EER in legend
        legends.append("%s (EER=%.2f%%)" % (titles[index], eer * 100))
        index = index + 1

    # Axis and legend
    subplot.set_xlabel('False positives rate')
    subplot.set_ylabel('True positives rate')
    subplot.legend(plots, legends, loc=4)

    # Save figure
    figure.savefig(output_file, format='pdf', dpi=600, orientation='landscape', bbox_inches="tight")
dataset/ETHPy150Open basilfx/Course-Face3D/face3d/utils.py/generate_roc_curve/operator `-` -> `/`