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CONTRIBUTING.md

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Contributing to the eyeris R package

Welcome!

Thank you for considering contributing to the eyeris R package. We created this template to be community-driven, as we believe the best preprocessing practices emerge from collective expertise and rigorous discussion.

How Can I Contribute?

Scientific Contributions

  • Identify potential issues in preprocessing steps
  • Suggest improvements based on recent literature
  • Share knowledge about best practices
  • Question assumptions in our implementation
  • Propose new validation checks

Technical Contributions

  • Bug fixes
  • Code optimization
  • Documentation improvements
  • Example additions
  • Test cases

Contribution Process

  1. Start with an Issue

    • Search existing issues first
    • Create a new issue to discuss your proposed changes
    • Wait for maintainer feedback before significant work

  2. Fork & Create Branch

    • Fork the repository
    • Create a branch for your changes
    • Use clear branch names (e.g., fix-some-issue, improve-some-feature)

  3. Make Changes

    • Follow existing code style
    • Add comments explaining preprocessing decisions
    • Update documentation as needed
    • Add tests if applicable

  4. Submit Pull Request

    • Provide clear description of changes
    • Link related issues
    • Include scientific rationale for preprocessing changes
    • Add before/after examples if possible

Pull Request Guidelines

  1. Scientific Validity

    • Explain the scientific rationale for changes
    • Cite relevant literature
    • Describe impact on preprocessing quality

  2. Code Quality

    • Follow R script conventions
    • Include comments explaining preprocessing decisions
    • Maintain existing error checking patterns
    • Add appropriate logging

  3. Documentation

    • Update README.Rmd (only if needed; note: README.md is auto-generated from README.Rmd)
    • Add inline documentation
    • Update parameter descriptions
    • Include clear and generalizable examples

  4. Testing

    • Add validation checks
    • Test with different data types
    • Verify BIDS-like compliance
    • Check edge cases

Questions?

Feel free to:

  • Open an issue for discussion
  • Ask for clarification on existing issues
  • Request more detailed contribution guidelines

We appreciate your help in maintaining high-quality pupillometry preprocessing standards!

--shawn