GeoPyWeb

A powerful web-based platform for geochemical data analysis and visualization

Features • Installation • Usage • Documentation • Contributing

🌍 Overview

GeoPyWeb is a comprehensive web-based platform for geochemical data analysis and visualization. Built as a web version of the popular GeoPyTool, it provides geoscientists with an intuitive interface to upload, analyze, and visualize geochemical datasets using industry-standard diagrams and classification methods.

✨ Features

📊 Classification Diagrams

• TAS Diagram - Total Alkali-Silica classification for volcanic rocks (Wilson et al., 1989)
• QAPF Diagram - Modal classification for plutonic rocks with CIPW norm support

📈 Variation Diagrams

• Harker Diagrams - Multi-element variation plots against SiO2

🔬 Trace Element Analysis

• REE Patterns - Rare Earth Element spider diagrams with multiple normalization standards
  • C1 Chondrite (Sun & McDonough, 1989; Taylor & McLennan, 1985; Haskin et al., 1966; Nakamura, 1977)
  • MORB (Sun & McDonough, 1989)
  • UCC (Rudnick & Gao, 2003)
• Trace Element Spider Diagrams - Comprehensive incompatible element patterns
  • 6 normalization standards (PM, OIB, EMORB, C1, NMORB, UCC)
  • 2 element sequences (Cs-Lu 36 elements, Rb-Lu 26 elements)
  • Automatic K2O→K and TiO2→Ti conversions

🏔️ Tectonic Discrimination

• Pearce Diagrams - Granite tectonic setting discrimination (Pearce et al., 1984)
  • 4 sub-diagrams: Y+Nb vs Rb, Yb+Ta vs Rb, Y vs Nb, Yb vs Ta
  • Discriminates syn-COLG, VAG, WPG, and ORG granites

🧮 Norm Calculations

• CIPW Norm - Cross, Iddings, Pirsson, Washington normative mineral calculations
• Automatic integration with QAPF diagrams

🎨 Advanced Features

• Smart Column Recognition - Automatic standardization of geochemical column names
• Flexible Data Input - Support for CSV and Excel files
• Color-coded Samples - Intelligent sample grouping and visualization
• Multiple Export Formats - PNG and SVG output options
• Professional Styling - Publication-ready diagrams with proper referencing

🚀 Installation

Prerequisites

• Python 3.8 or higher
• pip package manager

Quick Start

1. Clone the repository

   git clone https://github.com/GeoPyTool/GeoPyWeb.git
   cd GeoPyWeb

2. Install dependencies

   pip install -r requirements.txt

3. Run the application

   python run.py

4. Access the web interface Open your browser and navigate to http://localhost:5000

Docker Installation (Optional)

# Build the Docker image
docker build -t geopyweb .

# Run the container
docker run -p 5000:5000 geopyweb

📖 Usage

1. Data Upload

• Upload your geochemical data in CSV or Excel format
• Supported file extensions: .csv, .xlsx, .xls
• Maximum file size: 16MB

2. Data Format Requirements

Major Elements (weight %)

• Required for TAS: SiO2, Na2O, K2O
• Required for CIPW/QAPF: SiO2, TiO2, Al2O3, Fe2O3, FeO, MnO, MgO, CaO, Na2O, K2O, P2O5
• Required for Harker: SiO2 + any other major elements

Trace Elements (ppm)

• REE Elements: La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu
• Pearce Elements: Rb, Y, Nb, Yb, Ta
• Full Trace Suite: Cs, Tl, Rb, Ba, W, Th, U, Nb, Ta, K, La, Ce, Pb, Pr, Mo, Sr, P, Nd, F, Sm, Zr, Hf, Eu, Sn, Sb, Ti, Gd, Tb, Dy, Li, Y, Ho, Er, Tm, Yb, Lu

Optional Columns

• Sample Grouping: Color, Type, Label, Group, Category, Class, Formation, Unit, Lithology
• Sample Information: Age, Location, Description

3. Column Name Recognition

GeoPyWeb automatically recognizes and standardizes various column naming conventions:

Examples of recognized formats:
- SiO2, SIO2, sio2, SiO2(wt%), SiO2_wt%, sio2_weight%
- La, LA, la, La(ppm), la_ppm, La_ppb
- K2O → K conversion, TiO2 → Ti conversion (automatic)

4. Analysis Workflow

1. Upload Data → Automatic column standardization and preview
2. Select Analysis Type → Choose from available diagram types
3. Configure Options → Set normalization standards, element sequences, output format
4. Generate Diagram → View results with professional styling
5. Download Results → Export as PNG or SVG

🔧 Technical Stack

• Backend: Flask 2.3.3 (Python web framework)
• Data Processing: Pandas 2.0.3, NumPy 1.24.3
• Visualization: Matplotlib 3.7.2
• File Handling: OpenPyXL 3.1.2 (Excel support)
• Frontend: Bootstrap 5.3, HTML5, JavaScript ES6
• Security: Werkzeug 2.3.7 (secure file uploads)

📁 Project Structure

GeoPyWeb/
├── run.py                 # Main Flask application
├── requirements.txt       # Python dependencies
├── templates/            
│   └── index.html        # Web interface template
├── uploads/              # Temporary file storage
├── Geochemistry.csv      # Sample dataset
├── README.md             # This file
└── LICENSE               # MIT License

🔬 Scientific References

The implemented methods are based on established geochemical literature:

• TAS Classification: Wilson, M. et al. (1989) Journal of Petrology
• Pearce Diagrams: Pearce, J.A. et al. (1984) Journal of Petrology, v.25, p.956-983
• REE Normalization: Sun, S.S. & McDonough, W.F. (1989); Rudnick, R.L. & Gao, S. (2003)
• QAPF Classification: Maitre, R.W.L. et al. (2004) Cambridge University Press

🤝 Contributing

We welcome contributions to GeoPyWeb! Here's how you can help:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Setup

# Install development dependencies
pip install -r requirements.txt

# Run in development mode
export FLASK_ENV=development
python run.py

📄 License

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

🙏 Acknowledgments

• Original GeoPyTool development team
• The global geochemical community for standardized methods
• Contributors and users who provide feedback and improvements

📞 Support

• Issues: GitHub Issues

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Made with ❤️ for the geoscience community