Feat: Post-processing functions to normalize parameters #451
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@billdenney let me know if this matches your idea for the normalization functions |
| if (!col %in% obj_conc_cols) { | ||
| stop("Column ", col, " not found in the PKNCAconc of the PKNCAresults object") | ||
| } | ||
| conc_groups <- dplyr::group_vars(object$data$conc) |
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Please make group_vars() work on PKNCAresults objects, and use that. It is likely as simple as
#' @export
group_vars.PKNCAresults <- function(x) {
group_vars(as_PKNCAconc(x))
}
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This already exists but I must admit I am actually pro-considering as group_vars for PKNCAresults also start, end and perhaps in the future PPANMETH to differentiate any parameter that may not be calculated in the same way (e.g, different impute)
So in my opinion should be that group_vars(PKNCAconc) != group_vars(PKNCAresults)
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That makes sense (see the new issue). Can you please switch this to dplyr::group_vars(as_PKNCAconc(object)), then?
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I'm going to move this on through without the minor style change I requested. Thanks for the work @Gero1999 ! |
2 participants
Closes #445
Changes involve:
Added functions to normalize PK parameters based on a column in PKNCAconc (
normalize_by_col) or using custom normalization tables (normalize).Tests added to validate the behavior of normalization functions, including handling of missing groups, duplicate groups, and mismatched lengths
New vignette entry in post-processing to explain how to use these functions