"""Fig. 3 (SER gain vs relevance coefficient) regenerated with the SAME box
aspect (0.8) as the Fig. 2 panels, from results/data/beta_sweep.csv."""
import csv, numpy as np
import matplotlib; matplotlib.use('Agg')
import matplotlib.pyplot as plt

rows = list(csv.DictReader(open('results/data/beta_sweep.csv')))
SNRS = [0.0, 5.0, 10.0]
STY  = {0.0: ('#C62828', 's--', 'SNR = 0 dB'),
        5.0: ('#E65100', '^-.', 'SNR = 5 dB'),
        10.0: ('#1565C0', 'o-', 'SNR = 10 dB')}
FILL = {0.0: '#C62828', 5.0: '#E65100', 10.0: '#1565C0'}

data = {s: {'b': [], 'g': []} for s in SNRS}
for r in rows:
    s = float(r['snr_label'])
    if s in data:
        data[s]['b'].append(float(r['beta_sq'])); data[s]['g'].append(float(r['gain_maml']))
for s in SNRS:
    o = np.argsort(data[s]['b'])
    data[s]['b'] = np.array(data[s]['b'])[o]; data[s]['g'] = np.array(data[s]['g'])[o]

fig, ax = plt.subplots(figsize=(5.2, 4.6))
for s in SNRS:
    c, mk, lbl = STY[s]
    ax.plot(data[s]['b'], data[s]['g'], mk, lw=2.0, color=c, label=lbl, markersize=5)
    ax.fill_between(data[s]['b'], 0, data[s]['g'], alpha=0.07, color=FILL[s])
ax.axhline(0, color='gray', lw=0.8, ls=':')
ax.set_xlabel(r'Semantic relevance coefficient  $\beta_{u,v}=\beta_u\cdot\beta_v$', fontsize=13)
ax.set_ylabel('SER gain over OFDMA', fontsize=13)
ax.tick_params(labelsize=12)
ax.legend(loc='upper left', fontsize=12)
ax.grid(True, alpha=0.3)
ax.set_xlim(-0.01, 0.82)
ax.set_box_aspect(0.8)              # match the Fig. 2 panel box aspect
fig.tight_layout()
fig.savefig('results/fig4_beta_sweep.pdf', bbox_inches='tight')
fig.savefig('results/fig4_beta_sweep.png', dpi=150, bbox_inches='tight')
print('saved results/fig4_beta_sweep.pdf (box_aspect=0.8)')