plot_lines_rmse.py

np.random.seed(42)
pixels = ['64-pixel', '96-pixel', '128-pixel', '160-pixel']
layers = ['1-layer', '2-layers', '3-layers', '4-layers', '5-layers']
rmse = np.random.uniform(1.5, 2.5, 20).reshape((4, 5))
rmse2 = np.random.uniform(0.5, .9, 20).reshape((4, 5))



dpi = 96
xmonitor = np.round(1366 * 80 / 100)/dpi
ymonitor = np.round(768 * 100 / 100)/dpi
fig = plt.figure(figsize=(xmonitor, ymonitor), dpi=dpi, facecolor='w')

ax1 = plt.subplot(2, 2, 1)
ax2 = plt.subplot(2, 2, 2)
ax3 = plt.subplot(2, 1, 2)
ax = [ax1, ax2, ax3]

                                                                        
for i in range(rmse.shape[1]):
    ax[0].plot(pixels, rmse[:, i], ls='-', marker='o', label=layers[i])
    
for i in range(rmse.shape[1]):
    ax[1].plot(pixels, rmse2[:, i], ls='-', marker='o', label=layers[i])
    ax[2].plot([], ls='-', marker='o', label=layers[i])

ax[0].set_title('Calibration wind velocity prediction model', fontdict=dict(weight='bold'))
ax[0].grid(ls='--')
ax[0].set_ylabel('RMSE (m/s)')
ax[0].set_xlabel('Image size')

ax[1].set_title('Calibration wave height prediction model', fontdict=dict(weight='bold'))
ax[1].grid(ls='--')
ax[1].set_ylabel('RMSE (m)')
ax[1].set_xlabel('Image size')

ax[2].legend(loc='upper center', ncol=5)
ax[2].axis('off')

plt.savefig('plot.png', rasterized=True, dpi=dpi*5)