40 lines
1.7 KiB
Python
Executable File
40 lines
1.7 KiB
Python
Executable File
"""Fig. 3 (SER gain vs relevance coefficient) regenerated with the SAME box
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aspect (0.8) as the Fig. 2 panels, from results/data/beta_sweep.csv."""
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import csv, numpy as np
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import matplotlib; matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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rows = list(csv.DictReader(open('results/data/beta_sweep.csv')))
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SNRS = [0.0, 5.0, 10.0]
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STY = {0.0: ('#C62828', 's--', 'SNR = 0 dB'),
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5.0: ('#E65100', '^-.', 'SNR = 5 dB'),
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10.0: ('#1565C0', 'o-', 'SNR = 10 dB')}
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FILL = {0.0: '#C62828', 5.0: '#E65100', 10.0: '#1565C0'}
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data = {s: {'b': [], 'g': []} for s in SNRS}
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for r in rows:
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s = float(r['snr_label'])
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if s in data:
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data[s]['b'].append(float(r['beta_sq'])); data[s]['g'].append(float(r['gain_maml']))
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for s in SNRS:
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o = np.argsort(data[s]['b'])
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data[s]['b'] = np.array(data[s]['b'])[o]; data[s]['g'] = np.array(data[s]['g'])[o]
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fig, ax = plt.subplots(figsize=(5.2, 4.6))
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for s in SNRS:
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c, mk, lbl = STY[s]
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ax.plot(data[s]['b'], data[s]['g'], mk, lw=2.0, color=c, label=lbl, markersize=5)
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ax.fill_between(data[s]['b'], 0, data[s]['g'], alpha=0.07, color=FILL[s])
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ax.axhline(0, color='gray', lw=0.8, ls=':')
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ax.set_xlabel(r'Semantic relevance coefficient $\beta_{u,v}=\beta_u\cdot\beta_v$', fontsize=13)
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ax.set_ylabel('SER gain over OFDMA', fontsize=13)
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ax.tick_params(labelsize=12)
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ax.legend(loc='upper left', fontsize=12)
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ax.grid(True, alpha=0.3)
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ax.set_xlim(-0.01, 0.82)
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ax.set_box_aspect(0.8) # match the Fig. 2 panel box aspect
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fig.tight_layout()
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fig.savefig('results/fig4_beta_sweep.pdf', bbox_inches='tight')
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fig.savefig('results/fig4_beta_sweep.png', dpi=150, bbox_inches='tight')
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print('saved results/fig4_beta_sweep.pdf (box_aspect=0.8)')
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