Academic Figures
Publication-ready scientific figures from data — one command, verified output. 从数据一键生成投稿级论文图表:期刊合规、统计正确、中文零配置、纯本地运行。
38 chart types (bar/slope/volcano/upset set-intersections/oncology waterfall/raincloud/clinical swimmer/ridgeline joyplot/dumbbell gap chart/model calibration curve/decision curve analysis/clinical nomogram/restricted cubic spline/subgroup forest/competing-risk CIF/box/violin/ scatter/line/heatmap/clustered-heatmap/forest/KM/ROC/venn 4-set ellipse/Bland-Altman/PCA/ funnel/Galbraith radial/paired/dual-axis/stacked/composite/diagram/PRISMA 2020 …) · 9 journal presets (Nature/Lancet/Science/Cell/NEJM/JAMA/IEEE/CMA/ 中文核心) · 9 color themes incl. colorblind-safe Okabe-Ito · 600dpi TIFF/PDF/SVG/EPS · fully local, zero telemetry.
Quick Start
# one-command figure (auto-picks the chart type)
python3 scripts/gen_figure.py --quick -d data.csv
# Nature double-column submission (width/font/DPI per author guidelines)
python3 scripts/gen_figure.py -t bar -d data.json -o fig.pdf --journal nature --column double --verify
# Cox multi-variable regression forest (raw per-subject data; Efron + PH test)
python3 scripts/gen_figure.py -t forest -d patient.csv --stats cox --cox-time time --cox-event event --cox-cols "age,sex,treat"
# Chinese zero-config (auto CJK font detection)
python3 scripts/gen_figure.py -t km -d survival.json -o km.png --cjk
Why academic-figures
- Journal compliance built-in: column widths, font sizes and DPI from official author
guidelines;
--verifypixel-level text-overlap gate;audit_pdf.pyfont-size gate — the hard desk-reject reasons are guarded mechanically. - Statistical correctness: Cox (Efron ties + PH test), KM (risk table, log-rank, median survival 95% CI), ROC (DeLong), metafunnel (Egger) — all validated against reference implementations (lifelines) to machine precision.
- Chinese zero-config: CJK font auto-detection, CMA/中文核心 presets, Chinese diagnostics for every error (graded exit codes 0-6).
- Safe by construction: fully local rendering, no network requests, no telemetry. See SKILL.md "Safety & Data" statement.
Docs
- Full docs:
SKILL.md(EN) · 中文文档见 SkillHub 页面 - Getting started:
references/quickstart.md· One-page cheatsheet:references/cheatsheet.md· Limits & flag interactions:references/limits.md - Scenario templates:
templates/(38, each with a ready-to-run command) - Regression suite:
tests/run_tests.py(430 tests)
Install
国内网络优先(无需访问 GitHub):
- SkillHub(中文,一条命令安装):skillhub.cn/skill/academic-figures — 搜索
academic-figures - ModelScope 魔搭镜像:https://modelscope.cn/skills/Docsor/academic-figures — 与 GitHub 版本对齐;喜欢请点个赞
- 依赖安装走国内镜像:
python3 scripts/setup_env.py(pip 失败自动切清华→阿里源,仅装 matplotlib/numpy/pymupdf/scipy) uvx/pip工具链同样走上述镜像;skill 本体与文档全部本地运行,无需访问 GitHub
GitHub 源码(国际网络):
git clone https://github.com/docsor1212/academic-figures.git
cd academic-figures
python3 scripts/setup_env.py # optional: install deps + self-check
Related tools · 相关工具
- pubmed-verifier —— 批量核验 PMID/DOI 引用真实性
- cite-holmes —— 引用与上下文一致性核查(幻觉引用检测)
- paper-polisher-pro —— 论文润色 · AI 率检测
- paper-rewriter —— AI 痕迹风格改写
- doc-holmes —— PDF 精确翻译/全文提取
- cn-med-oa —— 中文 OA 医学文献检索与引用核验
- MedWiki —— 医学维基参考站(药品说明书/医学术语)
License
MIT
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