dev/claude-help.md

In friendly/heplots: Visualizing Hypothesis Tests in Multivariate Linear Models

I'd be happy to help you develop the heplots package! Based on your expertise in advanced visualization for multivariate data and statistical models, this sounds like a perfect collaboration.

What I can help with:

Package Development Tasks: - Writing new functions for multivariate statistical methods - Creating comprehensive documentation (roxygen2 comments, vignettes) - Developing unit tests and examples - Code review and optimization for performance - Ensuring consistent coding style and best practices - Creating visualization functions that integrate with your existing framework

Specific to Multivariate Methods: - Implementing statistical algorithms (MANOVA, canonical correlation, discriminant analysis extensions) - Creating specialized plotting functions for complex multivariate outputs - Developing helper functions for data preparation and transformation - Building methods for different object classes (S3/S4 methods)

Documentation and Examples: - Writing clear function documentation with mathematical details - Creating comprehensive vignettes showing real-world applications - Developing example datasets that demonstrate new functionality - Writing NEWS.md entries and updating DESCRIPTION files

Best ways to work together:

For New Functions: 1. Start with specifications - describe the statistical method, expected inputs/outputs, and desired visualization approach 2. Iterative development - I can draft functions, you review and refine 3. Integration focus - ensure new functions work seamlessly with existing heplots infrastructure

For Code Reviews: - Share function drafts and I can suggest improvements for efficiency, readability, and R best practices - Review mathematical implementations for accuracy - Check for edge cases and error handling

For Documentation: - I can help write comprehensive help files with proper mathematical notation - Create examples that demonstrate both basic usage and advanced applications - Develop vignettes that showcase new methods in context

Workflow Suggestions: - Use our conversation to brainstorm and prototype ideas - I can generate initial function skeletons based on your specifications - Share code snippets for review and iteration - Discuss integration points with existing package architecture

Since you have the anthropic package set up, you could even create specialized helper functions for package development tasks - like generating roxygen2 templates or creating test cases.

What specific multivariate methods or visualization approaches are you considering adding to heplots? I'd love to understand your vision for extending the package.

Follow-up

This is very helpful. I think I will take some time to develop specifications for some tasks. Just to be clear: in what forms can you give me your results? As text files for R functions or vignettes that I will incorporate into the GitHub repo or can you work on a branch in the repo itself?

Claude:

Great question! Here are the different ways I can deliver results to you:

What I CAN provide:

Code Artifacts (what I recommend): - Complete R function files that you can save directly to your repo - Full vignette .Rmd files ready for your vignettes/ folder - Documentation files, test files, example scripts - NAMESPACE updates, DESCRIPTION modifications - Complete file contents formatted properly for immediate use

Text-based deliverables: - Function code with proper roxygen2 documentation - Vignette content in R Markdown format - Test cases using testthat framework - Example datasets and usage demonstrations - Documentation improvements and additions

What I CANNOT do:

Direct GitHub integration: - I cannot directly commit to your GitHub repository - I cannot create or work on branches in your repo - I cannot push changes or make pull requests - I cannot directly access or modify files in your GitHub repository

Recommended workflow:

1. I create artifacts - Complete, properly formatted R files that you can copy directly into your repo structure
2. You save and integrate - Take the artifacts and save them to appropriate locations (R/, vignettes/, tests/, etc.)
3. Iterative refinement - You can share existing code for me to modify/improve, and I'll return updated versions
4. File-by-file development - I can create individual functions, then documentation, then tests as separate artifacts

For example, if you want a new function for canonical correlation plots, I could provide: - R/canoncor_plot.R - the main function file - man/canoncor_plot.Rd - the documentation (or roxygen2 comments) - tests/testthat/test-canoncor_plot.R - unit tests - Example code for vignettes

This approach gives you complete control over what gets added to your repo while maximizing the code I can generate for you. You'll be doing the git operations, but I can provide all the content ready to commit.

Does this workflow sound good for your development process?

friendly/heplots documentation built on June 12, 2025, 4:10 p.m.