Galaxy-Dawn

Galaxy-Dawn / pubfig

Public

Publication-style scientific plotting for papers: common plot families, clean exports, and panel-first Figma assembly.

data-visualization matplotlib publication-figures python scientific-plotting
33
0
100% credibility
Found Mar 31, 2026 at 33 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

pubfig creates publication-ready scientific plots with journal themes and supports exporting panels for easy assembly in design tools.

How It Works

1
🔍 Discover pubfig

You find this handy tool for making professional charts for your research papers.

2
📦 Get it ready

Install it quickly so you can start creating charts right away.

3
📊 Make your first chart

Enter your data and watch a beautiful, paper-ready plot appear with perfect labels and colors.

4
🎨 Customize the look

Tweak titles, colors, and styles to match your favorite journals like Nature or Science.

5
💾 Save your figure

Export it in the exact size and format needed for your paper, like PDF or high-res images.

6
Build bigger figures
✅
Single chart ready

Your standalone figure is perfect for the paper.

🔗
Assemble panels

Export clean pieces and arrange them beautifully in your design app.

✨ Paper-ready artwork

Your charts look professional and are set to impress in your publication.

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Star Growth

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AI-Generated Review

What is pubfig?

Pubfig is a Python library built on Matplotlib for creating publication-style scientific plots tailored for research papers. It provides common plot families like bar-scatter, rainclouds, heatmaps, and evaluation curves (ROC, volcano) with paper-ready defaults for fonts, spacing, and legends, plus clean exports to PDF/SVG/PNG. The standout is its panel-first Figma assembly: export individual panels as SVGs, then use CLI commands like `pubfig figma push panels --figure-id figure-01` to sync and arrange multi-panel figures without manual redraws.

Why is it gaining traction?

Unlike blank-canvas Matplotlib or opinionated alternatives like seaborn, pubfig starts with journal specs (Nature, Science) and one consistent API across 40+ plot types, saving hours on tweaking. Journal-aware exports handle column widths and DPI automatically, and the Figma bridge enables live refreshes for iterative workflows. Recent additions like ECDF, QQ plots, and circular bars keep it fresh for evolving scientific needs.

Who should use this?

Academic researchers and data scientists plotting stats, distributions, or ML benchmarks for papers. ML engineers benchmarking models with grouped scatters or radar charts. Anyone in biology/ML doing panel-heavy figures who wants Python plotting plus Figma polish over full redesigns.

Verdict

Try it for prototyping paper figures—docs and examples are solid, CLI/Figma flow is intuitive despite 33 stars and 1.0% credibility signaling early maturity. Solid alpha for Python scientific plotting; pair with your analysis scripts now, watch for v1.0 stability.

(198 words)

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