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644 refactor nll cleanup #655

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What is the feature?

  • clean-up nll refactor

How have you implemented the solution?

Refactor nll to lpdf

  • rename nll to lpdf throughout FIMS
  • in density functions, change -= to +=
  • update documentation in density functions to reflect that functions return the positive log-likelihoods
  • in model.hpp, change nll += to -=

Only apply log(y) correction to dlnorm when input_type == data

  • Add conditional flag to LNorm_LPDF

Remove do_log argument from distribution_base evaluate - OR - Add error to catch if do_log == FALSE & obs are vectors

  • hard code do_log = true

Rename observed and expected values?

  • rename observed_values to x

Does the PR impact any other area of the project, maybe another repo?

  • no

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Instructions for code reviewer

Hello reviewer, thanks for taking the time to review this PR!

  • Please use this checklist during your review, checking off items that you have verified are complete!
  • For PRs that don't make changes to code (e.g., changes to README.md or Github actions workflows), feel free to skip over items on the checklist that are not relevant. Remember it is still important to do a thorough review.
  • Then, comment on the pull request with your review indicating where you have questions or changes need to be made before merging.
  • Remember to review every line of code you’ve been asked to review, look at the context, make sure you’re improving code health, and compliment developers on good things that they do.
  • PR reviews are a great way to learn, so feel free to share your tips and tricks. However, for optional changes (i.e., not required for merging), please include nit: (for nitpicking) before making the suggestion. For example, nit: I prefer using a data.frame() instead of a matrix because...
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Checklist

  • The PR is requested to be merged into the appropriate branch (typically main)
  • The code is well-designed.
  • The functionality is good for the users of the code.
  • Any User Interface changes are sensible and look good.
  • The code isn’t more complex than it needs to be.
  • Code coverage remains high, indicating the new code is tested.
  • The developer used clear names for everything.
  • Comments are clear and useful, and mostly explain why instead of what.
  • Code is appropriately documented (doxygen and roxygen).

@Andrea-Havron-NOAA Andrea-Havron-NOAA deleted the 644-refactor-nll-cleanup branch July 26, 2024 14:48
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