gradient = np.linspace(0, 1, 256) gradient = np.vstack((gradient, gradient)) cmaps = ['turbo', 'jet', 'gist_rainbow_r', 'hsv_r'] fig, axs = plt.subplots(len(cmaps), constrained_layout=True) for name, ax in zip(cmaps, axs): ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name)) ax.set_title(name) ax.set_axis_off()