import matplotlib.pyplot as plt
# import seaborn as sns  # For professional styling

# Set seaborn style for scientific aesthetics
plt.style.use('seaborn-v0_8')  # Use seaborn for clean, professional look
plt.rcParams['font.family'] = 'Arial'  # Set font to Arial for publication
plt.rcParams['font.size'] = 14  # Larger font size for readability
plt.rcParams['axes.linewidth'] = 1.2  # Thicker axes for clarity
plt.rcParams['lines.linewidth'] = 2  # Thicker plot lines
plt.rcParams['legend.fontsize'] = 12  # Legend font size
plt.rcParams['xtick.labelsize'] = 12  # X-axis tick label size
plt.rcParams['ytick.labelsize'] = 12  # Y-axis tick label size

# Data from the table
K = [2, 4, 6, 8, 12]
L = [3.21, 3.89, 4.57, 4.96, 5.38]
SR = [2.73, 3.01, 3.44, 3.30, 2.89]

# Plot K vs L
plt.figure(figsize=(8, 6))
plt.scatter(K, L, color='#1f77b4', s=100, alpha=0.8, edgecolors='w')  # Tableau blue, larger markers
plt.plot(K, L, color='#1f77b4', linestyle='--', alpha=0.6)  # Dashed line, slightly transparent
plt.xlabel('K', fontsize=16, weight='bold')
plt.ylabel(r'$\tau$', fontsize=16, weight='bold')
# plt.title('K vs L', fontsize=18, weight='bold')
plt.grid(True, linestyle='--', alpha=0.7)
plt.legend()
plt.tight_layout()
plt.savefig('K_vs_L.png', dpi=600, bbox_inches='tight')  # High DPI for publication
# plt.show()

# Plot K vs SR
plt.figure(figsize=(8, 6))
plt.scatter(K, SR, color='#ff7f0e', s=100, alpha=0.8, edgecolors='w')  # Tableau orange
plt.plot(K, SR, color='#ff7f0e', linestyle='--', alpha=0.6)  # Dashed line, slightly transparent
plt.xlabel('K', fontsize=16, weight='bold')
plt.ylabel('SR', fontsize=16, weight='bold')
# plt.title('K vs SR', fontsize=18, weight='bold')
plt.grid(True, linestyle='--', alpha=0.7)
plt.legend()
plt.tight_layout()
plt.savefig('K_vs_SR.png', dpi=600, bbox_inches='tight')  # High DPI for publication
# plt.show()