jrcjrcc/deepseek-nyamu/05-plotting

import matplotlib.pyplot as plt
plt.rcParams.update({
    "font.family": "serif", "font.size": 10,
    "axes.titlesize": 11, "axes.titleweight": "bold",
    "axes.labelsize": 10, "legend.fontsize": 8.5,
    "axes.spines.top": False, "axes.spines.right": False,
    "axes.grid": True, "grid.alpha": 0.15,
    "figure.dpi": 300, "savefig.dpi": 300,
})
COLORS = ["#264653", "#2A9D8F", "#E9C46A", "#F4A261", "#E76F51"]
OUR_COLOR = "#E76F51"

fig, ax = plt.subplots(figsize=(3.25, 2.5))
markers = ["o", "s", "^", "D", "v"]
for i, (method, (mean, std)) in enumerate(results.items()):
    color = OUR_COLOR if method == "Ours" else COLORS[i]
    ax.plot(steps, mean, label=method, color=color,
            marker=markers[i], markevery=max(1, len(steps)//8))
    ax.fill_between(steps, mean-std, mean+std, color=color, alpha=0.12)
ax.set_xlabel("Training Steps"); ax.set_ylabel("Accuracy (%)")
ax.legend(loc="lower right")
fig.savefig("figures/fig_training.pdf")

fig, ax = plt.subplots(figsize=(6.75, 2.8))
x = np.arange(len(categories)); width = 0.7 / len(methods)
for i, (method, scores) in enumerate(methods.items()):
    color = OUR_COLOR if method == "Ours" else COLORS[i]
    offset = (i - len(methods)/2 + 0.5) * width
    ax.bar(x + offset, scores, width*0.9, label=method, color=color)
ax.set_xticks(x); ax.set_xticklabels(categories)
ax.set_ylabel("Score"); ax.legend()
fig.savefig("figures/fig_ablation.pdf")

import seaborn as sns
fig, ax = plt.subplots(figsize=(4, 3.5))
sns.heatmap(matrix, annot=True, fmt=".2f", cmap="YlOrRd",
            linewidths=1.5, linecolor="white")
fig.savefig("figures/fig_heatmap.pdf")

figures/
├── gen_fig_<name>.py       # 生成脚本（必须保存以便复现）
├── fig_<name>.pdf          # 最终矢量输出（供LaTeX使用）
└── fig_<name>.png          # 光栅输出（300 DPI）