AV Sensor Detection ANOVA

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats

np.random.seed(999)

# Detection accuracy percentage
lidar = np.random.normal(96.5, 2.0, 100)
radar = np.random.normal(89.2, 3.5, 100)
camera = np.random.normal(92.8, 2.8, 100)
ultrasonic = np.random.normal(78.5, 5.0, 100)

lidar = np.clip(lidar, 88, 100)
radar = np.clip(radar, 75, 98)
camera = np.clip(camera, 82, 99)
ultrasonic = np.clip(ultrasonic, 60, 92)

F_stat, p_value = stats.f_oneway(lidar, radar, camera, ultrasonic)

fig, ax = plt.subplots(figsize=(12, 7), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#6CF527', '#F5B027', '#27D3F5', '#F5276C']
data = [lidar, radar, camera, ultrasonic]

bp = ax.boxplot(data, positions=[1, 2, 3, 4], widths=0.6, patch_artist=True,
                medianprops={'color': 'white', 'linewidth': 2},
                whiskerprops={'color': '#555555', 'linewidth': 1.5},
                capprops={'color': '#555555', 'linewidth': 1.5},
                flierprops={'marker': 'o', 'markerfacecolor': '#444444', 'markersize': 4})

for patch, color in zip(bp['boxes'], colors):
    patch.set_facecolor(color)
    patch.set_alpha(0.7)
    patch.set_edgecolor('white')
    patch.set_linewidth(1.5)

labels = ['LiDAR', 'Radar', 'Camera', 'Ultrasonic']

# Safety threshold
ax.axhline(y=95, color='#22c55e', linestyle='--', alpha=0.7, linewidth=1.5)
ax.text(4.45, 95, 'L4 Req', fontsize=8, color='#22c55e', va='center')

# Range and cost
ranges = ['200m', '250m', '150m', '5m']
costs = ['$10K', '$500', '$200', '$50']
for i, (d, rng, cost, color) in enumerate(zip(data, ranges, costs, colors)):
    ax.text(i+1, 55, f'Range:{rng} | {cost}', ha='center', fontsize=8, color=color)

# Stats header
stats_text = f"ANOVA: F={F_stat:.1f}, p<0.001 | Best Accuracy: LiDAR (μ={lidar.mean():.1f}%)"
bbox = dict(boxstyle="round,pad=0.3", facecolor='#020B14', edgecolor='#6CF527', lw=2)
ax.text(0.5, 1.02, stats_text, transform=ax.transAxes, fontsize=9, color='white',
        ha='center', va='bottom', fontfamily='monospace', bbox=bbox)

ax.set_xticks([1, 2, 3, 4])
ax.set_xticklabels(labels, fontsize=11, color='white')
ax.set_ylabel('Detection Accuracy (%)', fontsize=12, color='white', fontweight='500')
ax.set_title('Autonomous Vehicle Sensor Performance\nObject Detection in Urban Environment', 
             fontsize=14, color='white', fontweight='bold', pad=25)

ax.tick_params(colors='#888888')
for spine in ax.spines.values():
    spine.set_color('#333333')
ax.yaxis.grid(True, color='#1a1a2e', linewidth=0.5)
ax.set_axisbelow(True)
ax.set_ylim(52, 102)

plt.tight_layout()
plt.show()