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import matplotlib.pyplot as plt |
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def compute_sample_scores(results, prompt): |
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return { |
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"sd_v1_5": {"G": 4, "R": 4, "A": 4, "E": 3}, |
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"openjourney_v4": {"G": 3, "R": 4, "A": 5, "E": 3}, |
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"ldm_256": {"G": 2, "R": 3, "A": 3, "E": 5} |
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} |
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def plot_radar(scores_dict, out_path="radar.png"): |
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categories = list(scores_dict.values())[0].keys() |
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N = len(categories) |
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fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True)) |
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for model, scores in scores_dict.items(): |
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values = list(scores.values()) |
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values += values[:1] |
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angles = [n / float(N) * 2 * 3.14159 for n in range(N)] |
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angles += angles[:1] |
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ax.plot(angles, values, linewidth=1, linestyle='solid', label=model) |
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ax.fill(angles, values, alpha=0.1) |
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ax.set_xticks(angles[:-1]) |
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ax.set_xticklabels(categories) |
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ax.set_title("GRACE 评估雷达图 (CPU模式)", size=12, y=1.1) |
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ax.legend(loc='upper right') |
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plt.savefig(out_path, bbox_inches='tight') |
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plt.close() |
