R/map_estimates.R

In modelsummary: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready

#' rename and reorder estimates from a *single* model
#' (before merging to collapse)
#'
#' @keywords internal
map_estimates <- function(estimates,
                          coef_rename,
                          coef_map,
                          coef_omit,
                          group_map) {


    # ambiguous rename
    check_dups <- function(dict) {
        dups <- unique(dict[duplicated(dict)])
        for (d in dups) {
            tmp <- names(dict)[which(d == dict)]
            tmp <- intersect(tmp, estimates$term)
            if (length(tmp) > 1) {
                msg <- sprintf("These variables have been assigned the same label in `coef_map` or `coef_rename`, but they are all part of the same model: %s", paste(tmp, collapse = ", "))
                stop(msg, call. = FALSE)
            }
        }
    }

    # coef_omit
    if (is.character(coef_omit)) {
        idx <- !grepl(coef_omit, estimates$term, perl = TRUE)
        if (sum(idx) > 0) {
            estimates <- estimates[idx, , drop = FALSE]
        } else {
            msg <- 'The regular expression supplied to `coef_omit` matched and omitted all the coefficients of (at least) one model, but `modelsummary` requires at least one coefficient to produce a table. Here are some examples of valid regular expressions for different use-cases:

library(modelsummary)
data(trees)
mod <- lm(Girth ~ Height + Volume, data = trees)

# coef_omit: omit coefficients matching one substring
modelsummary(mod, coef_omit = "ei")

# coef_omit: omit a specific coefficient
modelsummary(mod, coef_omit = "^Volume$")

# coef_omit: omit coefficients matching either one of two substring
modelsummary(mod, coef_omit = "ei|rc")

# coef_omit: keep coefficients starting with a substring (using a negative lookahead)
modelsummary(mod, coef_omit = "^(?!Vol)")

# coef_omit: keep coefficients matching either one of two substring
modelsummary(mod, coef_omit = "^(?!.*ei|.*pt)")
'
            stop(msg, call. = FALSE)
        }
    }

    # coef_rename
    # TRUE: done in `get_estimates()` straight from the parameters() attribute
    # FALSE: do nothing
    if (!is.null(coef_rename) && !is.logical(coef_rename) && !isTRUE(checkmate::check_character(coef_rename, names = "unnamed"))) {
        # unnamed vectors are processed in `modelsummary` directly because we rely on the order in the final table
        if (isTRUE(checkmate::check_character(coef_rename, names = "unique"))) {
            dict <- coef_rename
        } else if (is.function(coef_rename)) {
            dict <- stats::setNames(coef_rename(estimates$term), estimates$term)
        }
        check_dups(dict)
        # if coef_rename is a function, then we trust the user to do interaction
        # replacement. Otherwise, we can get duplicate replacements: "Height (in feet) (in feet)".
        estimates$term <- replace_dict(
            estimates$term,
            dict,
            interaction = !isTRUE(is.function(coef_rename)))
    }

    # coef_map
    if (!is.null(coef_map)) {
        check_dups(coef_map)
        if (is.null(names(coef_map))) {
            coef_map <- stats::setNames(coef_map, coef_map)
        }
        idx <- estimates$term %in% names(coef_map)
        if (!any(idx)) {
            stop("At least one of the term names in each model must appear in `coef_map`.")
        }
        estimates <- estimates[idx, , drop = FALSE]
        estimates$term <- replace_dict(
            estimates$term,
            coef_map,
            interaction = !isTRUE(is.function(coef_rename)))
    }

    # group_map
    group_name <- setdiff(colnames(estimates), c("part", "term"))[1] # HACK!
    if (!is.null(group_map)) {
        if (is.null(names(group_map))) {
            group_map <- stats::setNames(group_map, group_map)
        }
        # subset
        estimates <- estimates[estimates[[group_name]] %in% names(group_map), , drop = FALSE]
        # reorder
        tmp <- split(estimates, estimates[[group_name]])
        tmp <- tmp[match(names(group_map), names(tmp))]
        estimates <- data.table::rbindlist(tmp)
        # rename
        estimates[[group_name]] <- replace_dict(
            estimates[[group_name]],
            group_map)
    }

    ## escape if needed
    ## (must be done after rename/map, otherwise all rows are dropped)
    cols <- intersect(
        colnames(estimates),
        c("group", "term", "model", group_name))
    for (col in cols) {
        estimates[[col]] <- escape_string(estimates[[col]])
    }

    return(estimates)
}