42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
"""Canonical replot of fig_bertvit_merged.pdf from data/bertvit_merged.csv.
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Curves: EDMA, EDMA + refinement (hybrid), ToDMA-adapted, OMA, genie bound.
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The attention columns remain in the CSV but are not plotted."""
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import csv
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from pathlib import Path
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import matplotlib
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matplotlib.use("Agg")
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import matplotlib.pyplot as plt
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ROOT = Path(__file__).resolve().parents[1]
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plt.rcParams.update({
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"font.family": "serif",
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"font.serif": ["DejaVu Serif", "Times New Roman"],
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"font.size": 9, "axes.labelsize": 9, "legend.fontsize": 6.6,
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"xtick.labelsize": 8, "ytick.labelsize": 8,
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"axes.grid": True, "grid.linestyle": "--", "grid.linewidth": 0.4,
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"grid.alpha": 0.6, "lines.linewidth": 1.4, "lines.markersize": 4.0,
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"figure.figsize": (3.15, 2.36), "pdf.fonttype": 42,
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})
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AXES_RECT = dict(left=0.205, right=0.965, top=0.955, bottom=0.185)
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rows = list(csv.DictReader(open(ROOT / "data" / "bertvit_merged.csv")))
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snr = [float(r["snr_db"]) for r in rows]
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col = lambda k: [float(r[k]) for r in rows]
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fig, ax = plt.subplots()
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ax.plot(snr, col("edma"), "o-", color="C3", label="EDMA (closed form)")
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ax.plot(snr, col("edma_ref"), "^-", color="C2",
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label="EDMA + refinement stage")
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ax.plot(snr, col("todma"), "d-.", color="C4", label="ToDMA-adapted")
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ax.plot(snr, col("oma"), "v:", color="C1", label="OMA")
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ax.plot(snr, col("genie"), "-", color="gray", lw=1.0,
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label="Genie-aided SIC bound")
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ax.set_xlabel("Per-block SNR $\\rho$ [dB]")
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ax.set_ylabel("Mean cosine similarity")
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ax.set_xlim(snr[0], snr[-1])
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ax.set_ylim(0, 0.85)
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ax.legend(loc="upper left")
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fig.subplots_adjust(**AXES_RECT)
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fig.savefig(ROOT / "fig" / "fig_bertvit_merged.pdf")
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print("[OK] wrote fig_bertvit_merged.pdf (no attention curve)")
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