期刊级科研绘图库 — 基于 Matplotlib + SciencePlots,专为中文科研场景优化
Project description
SciPlot Academic
期刊级科研绘图库 — 基于 Matplotlib + SciencePlots,专为中文科研场景优化
安装
# pip
pip install sciplot-academic
# uv(推荐)
uv pip install sciplot-academic
# conda(需要先 pip 安装 scienceplots)
conda install -c conda-forge matplotlib numpy
pip install scienceplots sciplot-academic
三行代码画出期刊图
import sciplot as sp
import numpy as np
x = np.linspace(0, 10, 200)
# 单线图(中文 + Nature 样式)
fig, ax = sp.plot(x, np.sin(x), xlabel="时间 (s)", ylabel="电压 (V)")
sp.save(fig, "结果图") # → 结果图.pdf + 结果图.png(1200 DPI)
# 多线对比(2条线自动用 pastel-2 配色)
fig, ax = sp.plot_multi(
x, [np.sin(x), np.cos(x)],
labels=["方法 A", "方法 B"],
xlabel="迭代次数", ylabel="准确率 (%)"
)
sp.save(fig, "对比结果")
核心特性
期刊样式(venue)
| venue | 尺寸(英寸) | 适用场景 |
|---|---|---|
nature(默认) |
7.0 × 5.0 | Nature/Science 双栏全图 |
ieee |
3.5 × 3.0 | IEEE 单栏 |
aps |
3.4 × 2.8 | APS Physical Review |
springer |
6.0 × 4.5 | Springer 期刊 |
thesis |
6.1 × 4.3 | 学位论文(A4 版心 15.5cm) |
presentation |
8.0 × 5.5 | 幻灯片/演示 |
三大常驻配色系
| 配色 | 风格 | 子集 |
|---|---|---|
pastel(默认) |
柔和粉彩 | pastel-1/2/3/4 |
earth |
大地色系 | earth-1/2/3/4 |
ocean |
海洋蓝绿 | ocean-1/2/3/4 |
plot_multi() 根据线条数自动选择对应子集(N≤4)。
其他配色:rainbow-N(N=1-23)、bright、vibrant、muted、100yuan 等。
图表类型
sp.plot(x, y) # 单线图
sp.plot_multi(x, [y1, y2]) # 多线图(智能配色)
sp.plot_scatter(x, y) # 散点图
sp.plot_bar(categories, values) # 柱状图
sp.plot_box(data_list) # 箱线图
sp.plot_violin(data_list) # 小提琴图
sp.plot_errorbar(x, y, yerr) # 误差条图
sp.plot_confidence(x, mean, std) # 置信区间图
sp.plot_heatmap(data) # 热力图
sp.plot_histogram(data) # 直方图
Word 论文 vs LaTeX 论文
Word 中文论文 → 保存为 PNG
sp.setup_style("thesis", "pastel-2", lang="zh")
fig, ax = sp.new_figure("thesis") # 6.1in ≈ A4 Word 版心宽
ax.plot(x, y, label="结果")
ax.set_xlabel("时间 (s)"); ax.set_ylabel("幅度")
ax.legend()
sp.save(fig, "word图", formats=("png",), dpi=1200)
LaTeX IEEE 投稿 → 保存为 PDF
sp.setup_style("ieee", "pastel-2", lang="en")
fig, ax = sp.new_figure("ieee") # 3.5in = \columnwidth
ax.plot(x, y1, label="Method A")
ax.plot(x, y2, label="Method B")
ax.set_xlabel("Time (s)"); ax.set_ylabel("Accuracy")
ax.legend(frameon=False)
sp.save(fig, "fig1", formats=("pdf",))
# LaTeX: \includegraphics[width=\columnwidth]{fig1.pdf}
依赖
matplotlib >= 3.5.0numpy >= 1.20.0SciencePlots >= 2.0.0
License
MIT License
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