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SciColor is a premium, minimalist web application designed for scientists and researchers to curate, visualize, and export high-fidelity color palettes for quantitative data. Optimized for publication standards, it bridges the gap between raw data and aesthetic clarity in scientific communication.

• Journal Standards: Access established color schemes from high-impact journals (e.g., Nature, Science, The Lancet).
• Sequential & Diverging: Optimized palettes for heatmaps, density plots, and gradient-based visualizations.
• Templates: Save your custom color configurations as localized templates for consistent cross-session usage.

• Contextual Previews: Instantly see how your colors perform across multiple chart types:
  • Bar Plots (Categorical contrast)
  • Line Graphs (Overlap & legibility)
  • Scatter Plots (Density & distribution)
  • Heatmaps (Gradient transition)
  • Pie Charts (Proportional clarity)

• Interactive Controls: Adjust palette resolution dynamically (from 2 up to 20 slots).
• Manual Refinement: Manually edit Hex codes or use the integrated Color Donor Pool to swap colors from existing presets.
• Print Safety Awareness: Real-time CMYK calculation with automatic density warnings for high-black concentrations (K > 85%) to ensure publication safety.

• Chromatographic Sampling: Upload any scientific figure or image to automatically extract its primary color signature, allowing you to replicate or adapt historical styles.

Production-ready code generation for major scientific environments:

• Python: Matplotlib plt.cycler integration.
• R: scale_fill_manual snippets for ggplot2.
• Matlab: defaultAxesColorOrder matrix.
• Web CSS: Standardized CSS variable injection.

SciColor follows an intentional design philosophy centered on functional clarity and "Laboratory instrument" aesthetics.

• Clean Geometry: Soft-rounded containers and consistent spacing to reduce cognitive load.
• Typography: A rigorous hierarchy using Inter for UI and JetBrains Mono for scientific data/code.
• Sophisticated Interaction: Subtle micro-animations and non-intrusive feedback (toasts) simulate the experience of a high-end physical research tool.

No installation needed — SciColor is available as a hosted web app:

👉 https://newtonsappletree.github.io/SciColor/

Simply open the link in your browser and start building palettes instantly.

This project was developed with Google AI Studio.

Install Node.js (LTS version recommended). To verify the installation, run:

node -v
npm -v

Both commands should print a version number.

1. Open the project root directory

Navigate to the folder containing package.json:

# Windows example
cd C:\Users\YourName\Desktop\SciColor

# macOS / Linux example
cd /Users/YourName/Desktop/SciColor

2. Install dependencies

Download all required libraries (creates the node_modules folder):

npm install

Wait for the command to finish before proceeding.

3. Start the development server

npm run dev

4. Open in your browser

After startup, the terminal will display a local address — copy it into your browser:

  ➜  Local:   http://localhost:5173/
  ➜  Network: use --host to expose