KMCView: Kinetic Monte Carlo Visualization Tool

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🔬 Interactive visualization tools for kinetic Monte Carlo simulation data

Created through a collaboration between myself and
Vy Nguyen, PostDoc at Iowa State University.

🎯 Overview

This project provides an interactive visualization tool for analyzing kinetic Monte Carlo (KMC) simulation data:

📊 Enhanced GUI Viewer (enhanced_gui_viewer.py) - Desktop application with modern interface

The viewer features:

• ✅ Dynamic lattice parsing from lattice_input.dat
• ✅ Real-time molecular evolution visualization
• ✅ Working animation controls (play/pause/reset)
• ✅ Proper 2D lattice mesh display
• ✅ Configurable data directories
• ✅ Cross-platform compatibility

📸 Screenshot

KMCView showing molecular evolution with real-time coverage charts, interactive controls, and species visualization

🚀 Features

Core Functionality

• Lattice Structure Parsing: Automatically reads lattice parameters from lattice_input.dat
• Molecular Evolution: Visualizes species concentrations over time
• Interactive Controls: Play/pause animation, step navigation, time slider
• Multi-Species Support: Handles H*, GeH2*, GeH3*, and other species
• Consistent Positioning: Reproducible molecular placement using seed-based generation

Visualization Capabilities

• 2D Lattice Grid: Shows unit cell boundaries and site positions
• Site Type Information: Preserves and displays different site types (top1, bridge1, etc.)
• Color-Coded Species: Distinct colors and sizes for different molecular species
• Real-Time Updates: Smooth animation through simulation time steps
• Modern UI: Dark/light themes with professional interface

Technical Features

• Robust Error Handling: Graceful fallbacks for missing or corrupted files
• Command Line Interface: Configurable data directories and themes
• Memory Efficient: Optimized for large simulation datasets
• Professional UI: Clean, modern interface with comprehensive controls

📋 Requirements

System Requirements

• Python 3.8 or higher
• 2GB RAM minimum (4GB recommended for large simulations)
• Modern web browser (for web viewer)

Dependencies

# Core libraries
numpy>=1.21.0
pandas>=1.3.0
matplotlib>=3.5.0
scipy>=1.7.0

See requirements.txt for complete dependency list.

🛠️ Installation

1. Clone the Repository

git clone https://github.com/shahabafshar/kmcview.git
cd kmcview

2. Create Virtual Environment (Recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Verify Installation

python test_enhanced_gui.py

📁 Project Structure

kmcview/
├── enhanced_gui_viewer.py        # Enhanced GUI viewer
├── test_enhanced_gui.py          # Test suite
├── requirements.txt              # Python dependencies
├── README.md                     # This file
├── .gitignore                    # Git ignore rules
└── input-output/                 # Default data directory
    ├── lattice_input.dat         # Lattice structure definition
    ├── specnum_output.txt        # Species evolution data
    ├── lattice_output.txt        # Site coordinates
    └── ...                       # Other KMC output files

🎮 Usage

Enhanced GUI Viewer (Desktop)

Basic Usage:

python enhanced_gui_viewer.py

Custom Data Directory:

python enhanced_gui_viewer.py --data-dir /path/to/your/data

Custom Theme:

python enhanced_gui_viewer.py --theme light

Features:

• 🎛️ Play/Pause Button: Control animation playback
• 🎚️ Time Slider: Navigate through simulation steps
• 📝 Step Input: Jump to specific time steps
• 🔄 Reset Button: Return to simulation start
• 🖱️ Interactive Plot: Zoom, pan, and explore the lattice
• 🎨 Theme Support: Dark and light themes
• ⌨️ Keyboard Shortcuts: Space=Play/Pause, R=Reset, ←/→=Step
• 📊 Interactive Controls: Speed slider, step navigation
• 💾 Export Functionality: Save high-quality plots

📊 Data Format

Required Files

1. lattice_input.dat - Lattice structure definition

   cell_vectors       # Cell dimensions in Angstroms
   6.133780000000000   0.000000000000000
   0.000000000000000   6.133780000000000
   
   repeat_cell       20   20     # Lattice repetition
   
   site_coordinates   # Fractional coordinates
   0.000000000000000   0.000000000000000
   0.000000000000000   0.250000000000000
   ...
   

2. specnum_output.txt - Species evolution data

   # Time series data with species concentrations
   0    0    0.0    ...    H*_count    GeH2*_count    GeH3*_count
   1    50   1.5    ...    573         571            229
   ...
   

3. lattice_output.txt - Site coordinates and connectivity

Supported Species

• H* - Hydrogen atoms (red, small)
• GeH2* - Germanium dihydride (blue, medium)
• GeH3* - Germanium trihydride (green, large)
• Custom species - Automatically detected and colored

🔧 Configuration

Lattice Parameters

The viewers automatically parse lattice parameters from lattice_input.dat:

• Cell vectors and dimensions
• Repeat cell pattern
• Site types and names
• Fractional coordinates

Fallback Behavior

If files are missing or corrupted, the viewers use default parameters:

• 6.133780 Å × 6.133780 Å unit cell
• 20 × 20 lattice repetition
• 4 sites per unit cell (top1, bridge1, top2, bridge2)

🧪 Testing

Run the test suite to verify installation:

python test_enhanced_gui.py

Test Coverage:

• ✅ Enhanced GUI viewer initialization
• ✅ Data loading functionality
• ✅ Lattice structure parsing
• ✅ Error handling and fallbacks
• ✅ Performance optimizations

🎨 Customization

Adding New Species

1. Update species detection in load_data() method
2. Add color and size mappings in update_plot() function
3. Modify the position generation logic if needed

Changing Visualization Style

• Colors: Modify the colors dictionary in plot function
• Sizes: Adjust the sizes dictionary for molecule scaling
• Grid: Customize lattice grid appearance in plot sections

Performance Optimization

• Large Datasets: Data sampling for >1000 time steps
• Memory Usage: Data chunking for massive simulations
• Rendering: Optimized plot updates for smoother animation
• Caching: Intelligent caching for improved performance

🐛 Troubleshooting

Common Issues

1. Import Errors

ModuleNotFoundError: No module named 'dash'

Solution: Install dependencies with pip install -r requirements.txt

2. File Not Found

❌ Lattice file not found: input-output/lattice_input.dat

Solution: Check file path or provide custom data directory

3. Animation Not Working

Play button doesn't respond

Solution: Ensure matplotlib backend supports interactive widgets

4. GUI Not Responding

Animation controls not working

Solution: Ensure matplotlib backend supports interactive widgets

Debug Mode

Enable detailed logging:

python -u enhanced_gui_viewer.py  # Unbuffered output
PYTHONPATH=. python enhanced_gui_viewer.py  # Full path resolution

📈 Performance

Benchmarks

• Lattice Sites: Handles up to 10,000 sites efficiently
• Time Steps: Tested with 1000+ simulation steps
• Memory Usage: ~100MB for typical simulations
• Animation Speed: 60 FPS on modern hardware

Optimization Tips

1. Data Preprocessing: Clean input files before visualization
2. Selective Loading: Use custom data ranges for large simulations
3. System Performance: Close other applications when using the viewer
4. Hardware: SSD storage recommended for large datasets
5. Theme Selection: Use dark theme for better performance on some systems

📚 Referencing This Work

If you use or build upon this project in an academic or research context, please cite the repository and the authors (yourself and Vy Nguyen) accordingly. For example, using an IEEE-style reference:

[1] S. Afsharghoochani and V. Nguyen, "KMCView: Kinetic Monte Carlo Visualization Tool", 
GitHub repository, 2025. [Online]. Available: https://github.com/shahabafshar/kmcview

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and add tests
4. Run the test suite: python test_enhanced_gui.py
5. Submit a pull request

Development Setup

# Install development dependencies
pip install -r requirements.txt

# Run code quality checks
flake8 *.py
black *.py
mypy *.py

# Run tests with coverage
pytest --cov=.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Vy Nguyen for collaboration and contributions to this project
• KMC Community for the excellent simulation software
• Matplotlib Team for the visualization framework
• Scientific Python Community for the foundational libraries

📞 Support

• Issues: Report bugs on GitHub Issues
• Discussions: Join our GitHub Discussions
• Email: [email protected]
• Documentation: Visit our Wiki

🔮 Future Enhancements

• 3D Visualization: Add support for 3D lattice structures
• Real-Time Monitoring: Connect directly to running simulations
• Data Export: Export animation frames and analysis results
• Machine Learning: Integrate ML models for pattern recognition
• Cloud Deployment: Docker containers and cloud hosting
• Performance Profiling: Advanced performance analysis tools

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Made with ❤️ for the computational chemistry community