plotting-library

What problem does it solve?

Standardizes and accelerates scientific plotting by providing a library of runnable plot templates and a shared matplotlib style, so researchers can generate publication-quality figures without rewriting boilerplate code.

Core Features & Use Cases

• Self-contained templates: each chart template includes generate_mock_data(), plot(), and a main entry, enabling quick demos and reproducible figures.
• Catalog-driven discovery: the /plotting-library/catalog.yaml exposes charts and metadata, allowing dynamic gallery generation without code changes.
• Style consistency: a centralized matplotlibrc style file ensures plots follow Nature-inspired aesthetics across templates.
• Use Case: quickly generate a volcano plot from differential expression data, or a heatmap from an expression matrix, by selecting a template and pointing to your data.

Quick Start

Run a demo template, for example python templates/volcano.py to generate a sample volcano plot.