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scientific-figure-making

scientific-figure-making

github.com/chenliu-1996Data & databases9.3k340 installsUpdated 1w ago
Repository

About scientific-figure-making

A skill for creating publication-oriented Matplotlib figures in the visual style of the current repository. It guides users to relevant references for figure patterns, API details, and design choices.

Key features

  1. 01Repository-matched publication styling
  2. 02Guidance for common scientific plots
  3. 03PDF, SVG, and high-DPI export guidance
  4. 04Reference-based, on-demand documentation

Use cases

  1. 01Preparing figures for papers, slides, or reports
  2. 02Building grouped bars, trend lines, heatmaps, or multi-panel layouts

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/chenliu-1996/figures4papers --skill scientific-figure-making

After installing, type/scientific-figure-makingin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
api.md
common-patterns.md
demos.md
design-theory.md
tutorials.md

Details

From the project README

Scientific figure making

Open references/ only as needed; do not preload every file. Start from the table below, then follow links inside the document you opened (and into figure_* code via references/demos.md) instead of loading the full reference set up front.

When to load this skill

  • Matplotlib figures for papers, slides, or reports that must match this repo’s publication look (fonts, palette, spines, legends, export).
  • Requests involving grouped bars, trend lines, heatmaps, multi-panel grids, or PDF/SVG/high-DPI output in a scientific-figure context.
  • References to figures4papers figure_* projects or “same style as the repo figures.”

When not to load

  • Plotly, Altair, Bokeh, or other interactive / web-first plotting.
  • EDA-only plots where seaborn or pandas is enough until there is a publication target.
  • Primary workflow is 3D, GIS, or non-matplotlib tooling.
  • Illustrator / Figma–first layout or infographic (not matplotlib data plots).

Related files

FileOpen when
references/tutorials.mdEnd-to-end walkthroughs (bar, trends, heatmap)
references/api.mdFunction signatures, PALETTE, validation rules
references/common-patterns.mdLayout patterns, legend panel, print-safe bars
references/design-theory.mdTypography, export policy, palette rationale
references/demos.mdCanonical figure_* demo links in figures4papers

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