Multi-panel Figure Assembler

A Python-based tool for assembling multi-panel scientific figures. Automatically arranges 6 sub-figures (A-F) into a composite image with consistent styling, labels, and high-resolution output.

Features

• Automatic Layout: Supports 2×3 or 3×2 grid arrangements
• Edge Alignment: Intelligently crops/pads images to match dimensions
• Unified Typography: Consistent font sizing across all panels
• Auto Labeling: Adds panel labels (A-F) with customizable position
• High Resolution: Output at 300+ DPI for publication quality

Installation

Requires Python 3.8+ and the following packages:

pip install Pillow numpy

Optional for advanced features:

pip install opencv-python-headless

Usage

python scripts/main.py --input A.png B.png C.png D.png E.png F.png --output figure.png [OPTIONS]

Command Line Arguments

Parameters

Examples

Basic usage:

python scripts/main.py -i A.png B.png C.png D.png E.png F.png -o figure.png

3×2 layout with custom DPI:

python scripts/main.py -i A.png B.png C.png D.png E.png F.png -o figure.png --layout 3x2 --dpi 600

Custom styling:

python scripts/main.py -i A.png B.png C.png D.png E.png F.png -o figure.png \
  --label-size 32 --label-position topright --padding 20 --border 4

Programmatic usage:

from scripts.main import FigureAssembler

assembler = FigureAssembler(
    layout="2x3",
    dpi=300,
    label_size=24,
    padding=10
)

assembler.assemble(
    inputs=["A.png", "B.png", "C.png", "D.png", "E.png", "F.png"],
    output="figure.png",
    labels=["A", "B", "C", "D", "E", "F"]
)

Output

The script generates a high-resolution composite figure with:

• All panels resized to uniform dimensions
• Panel labels (A-F) in specified positions
• Consistent padding and borders
• DPI metadata embedded in output file

Supported Formats

Input: PNG, JPG, JPEG, BMP, TIFF, GIF Output: PNG (recommended), JPG, TIFF

Notes

• Input images are automatically resized to match the largest dimension while maintaining aspect ratio
• For best results, use input images with similar aspect ratios
• Label fonts require the font to be available on your system
• PNG output preserves transparency if any input images have alpha channels

Risk Assessment

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support