Skip to content

Contributing

This section provides guidelines for contributing to the Ehokolo Fluxon Model repository.

Contribution Types

Research Contributions

  • New hypothesis papers: Theoretical developments and predictions
  • Computational studies: Numerical simulations and validation
  • Empirical analysis: Comparison with observational data
  • Method development: New computational and analytical methods

Documentation Contributions

  • Wiki improvements: Enhanced explanations and examples
  • Code documentation: Improved code comments and docstrings
  • Tutorial development: Step-by-step guides for new users
  • Translation: Multi-language documentation

Tool Development

  • Computational tools: New simulation and analysis tools
  • Organization utilities: Improved research organization
  • Validation methods: Enhanced testing and validation
  • Visualization tools: Better plotting and analysis tools

Getting Started

1. Fork the Repository

# Fork the repository on GitHub
# Clone your fork locally
git clone https://github.com/YOUR_USERNAME/eholoko-fluxon-model.git
cd eholoko-fluxon-model

# Add upstream remote
git remote add upstream https://github.com/BecomingPhill/eholoko-fluxon-model.git

2. Set Up Development Environment

# Create virtual environment
python3 -m venv efm-env
source efm-env/bin/activate

# Install dependencies
pip install -r requirements.txt

# Install development tools
pip install pytest black flake8 mypy

3. Choose Contribution Area

  • Theory: Mathematical framework and derivations
  • Densities: Specific density state research
  • Research: Computational studies and validation
  • Tools: Development and improvement of utilities

Contribution Guidelines

Code Contributions

Style Guidelines

  • Python: Follow PEP 8 style guide
  • LaTeX: Use consistent formatting and structure
  • Markdown: Follow standard markdown conventions
  • Comments: Provide clear, comprehensive documentation

Testing Requirements

  • Unit tests: Test individual functions and methods
  • Integration tests: Test complete workflows
  • Validation tests: Compare with known solutions
  • Documentation tests: Ensure examples work correctly

Code Review Process

  1. Self-review: Check your code before submitting
  2. Peer review: Request review from maintainers
  3. Testing: Ensure all tests pass
  4. Documentation: Update relevant documentation

Research Contributions

Paper Development

  1. Start with hypothesis: Clear theoretical foundation
  2. Develop simulations: Numerical validation
  3. Compare with data: Empirical validation
  4. Document results: Clear presentation and analysis

Research Organization

  • Follow density structure: Organize by N1-N8 density states
  • Include all components: Papers, notebooks, media, PDFs
  • Provide README: Document each research area
  • Cross-reference: Link related research areas

Documentation Contributions

Wiki Development

  • Clear structure: Logical organization and navigation
  • Comprehensive coverage: Complete topic coverage
  • Examples: Practical examples and tutorials
  • Cross-references: Link related sections

Code Documentation

  • Docstrings: Comprehensive function documentation
  • Comments: Explain complex algorithms
  • Examples: Provide usage examples
  • Type hints: Use Python type annotations

Submission Process

1. Create Feature Branch

# Create and switch to feature branch
git checkout -b feature/your-feature-name

# Make your changes
# ... edit files ...

# Stage changes
git add .

# Commit changes
git commit -m "Add feature: brief description"

2. Push and Create Pull Request

# Push to your fork
git push origin feature/your-feature-name

# Create pull request on GitHub
# Provide clear description of changes
# Link related issues if applicable

3. Address Feedback

  • Respond to comments: Address all review feedback
  • Make requested changes: Implement suggested improvements
  • Update documentation: Keep documentation current
  • Test changes: Ensure all tests pass

Research Workflow

1. Hypothesis Development

  • Start with theory: Clear theoretical foundation
  • Review literature: Understand current state of field
  • Identify gaps: Find areas for new research
  • Formulate predictions: Make testable predictions

2. Computational Validation

  • Develop simulations: Implement numerical methods
  • Test methods: Validate against known solutions
  • Analyze results: Extract meaningful insights
  • Document process: Record methodology and results

3. Empirical Testing

  • Compare with data: Test predictions against observations
  • Statistical analysis: Quantify agreement/disagreement
  • Uncertainty analysis: Assess confidence in results
  • Report findings: Clear presentation of results

4. Publication

  • Write papers: Document research findings
  • Generate figures: Create clear visualizations
  • Compile PDFs: Produce final documents
  • Update wiki: Document new findings

Quality Standards

Research Quality

  • Rigorous methodology: Sound scientific approach
  • Clear documentation: Well-documented process
  • Reproducible results: Others can reproduce findings
  • Open data: Share data and code when possible

Code Quality

  • Clean code: Readable and maintainable
  • Comprehensive testing: Thorough test coverage
  • Good documentation: Clear comments and docstrings
  • Performance: Efficient and scalable

Documentation Quality

  • Clear writing: Easy to understand
  • Complete coverage: Comprehensive topic coverage
  • Accurate information: Correct and up-to-date
  • Good organization: Logical structure and navigation

Community Guidelines

Communication

  • Be respectful: Treat others with respect
  • Be constructive: Provide helpful feedback
  • Be patient: Allow time for responses
  • Be collaborative: Work together toward common goals

Collaboration

  • Share knowledge: Help others learn and grow
  • Provide feedback: Constructive criticism and suggestions
  • Ask questions: Don't hesitate to ask for help
  • Give credit: Acknowledge contributions from others

Intellectual Property

  • Respect licenses: Follow licensing requirements
  • Give attribution: Credit original work
  • Respect privacy: Protect confidential information
  • Follow ethics: Maintain high ethical standards

Getting Help

Documentation

  • Wiki: Comprehensive documentation
  • README files: Project-specific information
  • Code comments: Inline documentation
  • Examples: Usage examples and tutorials

Community Support

  • GitHub Issues: Bug reports and feature requests
  • Discussions: General questions and discussions
  • Pull Requests: Code review and collaboration
  • Email: Direct contact for sensitive issues

Resources

  • Scientific literature: Relevant papers and references
  • Computational resources: Tools and utilities
  • Educational materials: Tutorials and guides
  • Community resources: External communities and forums