Issue 788: Add S3 dispatch for model sample processing

[SamuelBrand1]

Summary

This PR adds an extensible interface for processing location forecasts to support multiple model types and make easier to do future expansion, which unblocks #783 .

Details

I've added a new model_name argument to process_loc_forecast function, if this is not NA then it lowers to process_forecast function and if it is NA (as default) then current logic is untouched.

process_forecast function can either be supplied a model_type to dispatch on a process_model_samples method or it detects from model name with the detect_model_type helper func. The functions then gathers the same data as process_loc_forecast and then dispatches the appropriate processing on the raw model output.

• Added process_model_samples methods for "pyrenew" and "timeseries" model types, so this should work with eg model_name = "pyrenew_e" but I've also kept legacy interface for backwards compat.

[codecov]

Codecov Report

❌ Patch coverage is 39.62264% with 64 lines in your changes missing coverage. Please review.
✅ Project coverage is 41.71%. Comparing base (06c3a48) to head (7a6a426).
⚠️ Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
hewr/R/process_loc_forecast.R	39.62%	64 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #790      +/-   ##
==========================================
+ Coverage   39.43%   41.71%   +2.27%     
==========================================
  Files          30       30              
  Lines        2713     2817     +104     
==========================================
+ Hits         1070     1175     +105     
+ Misses       1643     1642       -1     

Flag	Coverage Δ
hewr	37.97% <39.62%> (+8.03%)	⬆️
pipelines	35.87% <ø> (ø)
pyrenew_hew	62.29% <ø> (ø)

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[Copilot]

Pull request overview

This PR introduces an extensible S3 dispatch system for processing location forecasts, enabling support for multiple model types and simplifying future model additions. The implementation adds a new model_name parameter to process_loc_forecast that leverages S3 method dispatch via process_model_samples, while maintaining backward compatibility with the existing interface.

Key changes:

• Added S3 generic process_model_samples with methods for "pyrenew" and "timeseries" model types
• Implemented detect_model_type helper to auto-detect model type from naming conventions
• Created new process_forecast function as simplified interface using the S3 dispatch system

Reviewed changes

Copilot reviewed 11 out of 11 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
hewr/R/process_loc_forecast.R	Core implementation of S3 dispatch system, including process_model_samples generic/methods, detect_model_type helper, and new process_forecast function with updated process_loc_forecast routing logic
hewr/tests/testthat/test_process_loc_forecast.R	Tests for S3 dispatch functionality, model type detection, and validation of both new and legacy interfaces
hewr/tests/testthat/test_timeseries_utils.R	Comprehensive test suite for timeseries utility functions including formatting, aggregation, and proportion calculations
hewr/man/*.Rd	Documentation files for new exported functions and S3 methods
hewr/NAMESPACE	Updated exports to include new S3 methods and functions
hewr/DESCRIPTION	RoxygenNote version bump from 7.3.2 to 7.3.3

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[damonbayer]

I think there is probably room to make some better abstractions, but I'm in favor of unblocking #783, so I have approved this PR and will work on some parallel changes in another PR.

[damonbayer]

This broke the pipeline. Missed it due to insufficient testing (#791)