21.3D surface

3D surface

"""
@File    : 05-decoding-Major
@Name    : 3d_surface.py
@Author  : lyq
@Date    : 2024/11/16 23:10
@Envi    : PyCharm 
@Description:  files details
"""import numpy as np
import matplotlib.pyplot as plt

# 设置全局默认字体为Times New Roman
plt.rcParams['font.family']='Times New Roman'deftest_dynamic_performance(alpha, beta, gamma, T, N, scenario_fluctuation=0.2):
    q_n_t = np.random.uniform(1,5,(N, T))# Simulated quality levels
    dynamic_fluctuations = np.random.uniform(1- scenario_fluctuation,1+ scenario_fluctuation,(N, T))

    QoE =0
    variances =[]for t inrange(T):
        quality = np.mean(q_n_t[:, t]* dynamic_fluctuations[:, t])# Add dynamic fluctuation to quality
        delay = np.mean([0.1* q *(1+0.1* np.sin(10* gamma))for q in q_n_t[:, t]])
        variance = np.var(q_n_t[:, t]* dynamic_fluctuations[:, t])
        decoding = np.mean([0.05* q *(1+0.05* np.cos(7* gamma))for q in q_n_t[:, t]])

        variances.append(variance)
        QoE +=(quality - alpha * delay - beta * variance - gamma * decoding)

    QoE_normalized =(QoE /(T *5))*10# Normalize QoE to 0-10 range
    variance_scaled =(np.mean(variances)/(5**2))*1# Scale Variance to target ~1return QoE_normalized, variance_scaled

# Generate a grid of alpha, beta, and gamma values for the QoE surface
alpha_range = np.linspace(0.08,0.12,10)# Around fixed alpha = 0.1
beta_range = np.linspace(0.45,0.55,10)# Around fixed beta = 0.5
gamma_range = np.linspace(0.045,0.055,10)# Around target gamma range# Create meshgrid for alpha, beta, and gamma
alpha_grid, beta_grid, gamma_grid = np.meshgrid(alpha_range, beta_range, gamma_range)# Compute QoE for each combination of alpha, beta, and gamma
qoe_surface = np.zeros_like(alpha_grid)
T =100# Time steps
N =5# Number of usersfor i inrange(alpha_grid.shape[0]):for j inrange(alpha_grid.shape[1]):for k inrange(alpha_grid.shape[2]):
            alpha = alpha_grid[i, j, k]
            beta = beta_grid[i, j, k]
            gamma = gamma_grid[i, j, k]
            qoe, _ = test_dynamic_performance(alpha, beta, gamma, T, N)
            qoe_surface[i, j, k]= qoe

# Plot 3D QoE surface for fixed gamma slice
fig = plt.figure(figsize=(12,8))
ax = fig.add_subplot(111, projection='3d')# Select a slice of gamma for visualization
gamma_index =len(gamma_range)//2# Middle gamma value
qoe_slice = qoe_surface[:,:, gamma_index]

alpha_slice = alpha_grid[:,:, gamma_index]
beta_slice = beta_grid[:,:, gamma_index]

surf = ax.plot_surface(alpha_slice, beta_slice, qoe_slice, cmap='viridis')
ax.set_title(f"3D QoE Surface (Gamma = {gamma_range[gamma_index]:.3f})")
ax.set_xlabel("Alpha (X-axis)")
ax.set_ylabel("Beta (Y-axis)")
ax.set_zlabel("QoE")
fig.colorbar(surf, shrink=0.5, aspect=10, label='QoE')
plt.autoscale(tight=True)
plt.savefig('3D_QoE_Surface.pdf')
plt.show()