scientific-visualization

Publication-ready figures require styled templates, high-resolution exports, and journal-compliant formatting. This Skill provides pre-configured matplotlib and seaborn templates with multi-panel layouts, error bars, significance markers, and PDF/EPS/TIFF/PNG export options that meet typography and resolution standards for manuscript submission.

Yes. This Skill applies colorblind-safe palettes and includes grayscale compatibility checks to ensure figures remain legible across color vision deficiencies. Multi-panel layouts and significance markers work independently of color alone.

Export formats matter for print and digital publication. This Skill handles multi-format export to PDF, EPS, TIFF, and PNG with configurable resolution and typography settings, so your figures meet journal-specific submission requirements without manual post-processing.

This Skill integrates matplotlib, seaborn, and plotly. While matplotlib and seaborn handle static publication figures, plotly support enables interactive web-based visualization workflows alongside your print-ready exports.

Multi-panel layouts require consistent panel labeling, spacing, and alignment. This Skill provides helper scripts and workflows for arranging panels, applying labels, and exporting as single publication-ready figures with configurable styles.

The Skill provides templates and helper scripts that abstract common matplotlib patterns. Working knowledge of matplotlib, seaborn, or plotting concepts accelerates adoption, but templates guide figure generation from data to export without deep library expertise.