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HolobiomicsLab
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scientific-visualization

Generate publication-ready scientific figures with Matplotlib, Seaborn, and Plotly.

4|1|Updated Jun 18, 2025
Search Tags:#typography#visualization#plotly#matplotlib#seaborn#publication#colorblind
One-click install
npx skills add https://github.com/HolobiomicsLab/Toolomics --skill scientific-visualization-holobiomicslab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/HolobiomicsLab/Toolomics/tree/main/mcp_host/skills/scientific-skills/scientific-skills/scientific-visualization
Command: npx skills add https://github.com/HolobiomicsLab/Toolomics --skill scientific-visualization-holobiomicslab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Generate publication-ready visualizations that meet journal guidelines, colorblind-safe palettes, and publication-quality typography using a coordinated set of libraries and reference materials.

Core Features & Use Cases

  • Publication-style templates and presets via scripts/style_presets.py and assets palettes for consistent visuals across journals.
  • Colorblind-friendly palettes and accessible color mappings via assets/color_palettes.py and references/color_palettes.md.
  • Export utilities for DPI, fonts, and vector formats via scripts/figure_export.py to produce publication-ready PDFs, EPS, TIFFs, and PNGs.
  • Use Case: A researcher rapidly generates a multi-panel figure that adheres to Nature-style constraints and exports print-ready files.

Quick Start

Generate a publication-ready figure by configuring a journal style, creating the figure with Matplotlib/Seaborn, and exporting to PDF/PNG with the provided utilities.

Frequently Asked Questions about scientific-visualization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create publication-ready figures with Matplotlib that meet journal guidelines?▼

To create publication-ready figures with Matplotlib, apply journal-specific style presets for multi-panel layouts and export print-ready files. This ensures your visualizations meet DPI, font embedding, and formatting requirements for high-profile scientific journals.

What is the best way to make colorblind-safe scientific plots in Python?▼

The best way to make colorblind-safe scientific plots is by applying accessible color palettes and mappings. Using predefined colorblind-friendly palettes ensures your data visualizations remain readable and accessible for all audiences in published research.

How do I export Matplotlib or Plotly figures to vector formats like PDF and TIFF?▼

You export Matplotlib or Plotly figures to vector formats like PDF and TIFF using dedicated export utilities. These utilities handle DPI configuration, font embedding, and vector output to produce print-ready files that satisfy journal submission standards.

Does this visualization approach work for multi-panel layouts in Seaborn?▼

Yes, this approach works for multi-panel layouts in Seaborn. It supports generating coordinated multi-panel figures using Seaborn, Matplotlib, and Plotly, allowing you to apply consistent typography and journal-specific styling across all subplots.

Why do my exported figures have missing fonts when submitted to a journal?▼

Exported figures have missing fonts when font embedding is not applied during the output process. Proper export utilities ensure fonts are correctly embedded in vector formats like PDF and EPS, meeting strict publication guidelines for high-profile journals.

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