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#' @rdname normalize
#' @export
unnormalize <- function(x, ...) {
UseMethod("unnormalize")
}
#' @export
unnormalize.default <- function(x, ...) {
insight::format_error(
"Variables of class '", class(x)[1], "' can't be unnormalized."
)
}
#' @rdname normalize
#' @export
unnormalize.numeric <- function(x, verbose = TRUE, ...) {
## TODO implement algorithm include_bounds = FALSE
# if function called from the "grouped_df" method, we use the dw_transformer
# attributes that were recovered in the "grouped_df" method
dots <- match.call(expand.dots = FALSE)[["..."]]
grp_attr_dw <- eval(dots$grp_attr_dw, envir = parent.frame(1L))
if (is.null(grp_attr_dw)) {
include_bounds <- attr(x, "include_bounds")
min_value <- attr(x, "min_value")
range_difference <- attr(x, "range_difference")
to_range <- attr(x, "to_range")
} else {
names(grp_attr_dw) <- gsub(".*\\.", "", names(grp_attr_dw))
include_bounds <- grp_attr_dw["include_bounds"]
min_value <- grp_attr_dw["min_value"]
range_difference <- grp_attr_dw["range_difference"]
to_range <- grp_attr_dw["to_range"]
if (is.na(to_range)) {
to_range <- NULL
}
}
if (is.null(min_value) || is.null(range_difference)) {
if (verbose) {
insight::format_error("Can't unnormalize variable. Information about range and/or minimum value is missing.")
}
return(x)
}
if (is.null(to_range)) {
x * range_difference + min_value
} else {
(x - to_range[1]) * (range_difference / diff(to_range)) + min_value
}
}
#' @rdname normalize
#' @export
unnormalize.data.frame <- function(x,
select = NULL,
exclude = NULL,
ignore_case = FALSE,
regex = FALSE,
verbose = TRUE,
...) {
# evaluate select/exclude, may be select-helpers
select <- .select_nse(select,
x,
exclude,
ignore_case,
regex = regex,
verbose = verbose
)
# if function called from the "grouped_df" method, we use the dw_transformer
# attributes that were recovered in the "grouped_df" method
dots <- match.call(expand.dots = FALSE)[["..."]]
if (is.null(dots$grp_attr_dw)) {
grp_attr_dw <- NULL
} else {
grp_attr_dw <- eval(dots$grp_attr_dw, envir = parent.frame(1L))
}
for (i in select) {
var_attr <- grep(paste0("^attr\\_", i, "\\."), names(grp_attr_dw))
attrs <- grp_attr_dw[var_attr]
x[[i]] <- unnormalize(x[[i]], verbose = verbose, grp_attr_dw = attrs)
}
x
}
#' @rdname normalize
#' @export
unnormalize.grouped_df <- function(x,
select = NULL,
exclude = NULL,
ignore_case = FALSE,
regex = FALSE,
verbose = TRUE,
...) {
# evaluate select/exclude, may be select-helpers
select <- .select_nse(select,
x,
exclude,
ignore_case,
regex = regex,
remove_group_var = TRUE,
verbose = verbose
)
info <- attributes(x)
grps <- attr(x, "groups", exact = TRUE)[[".rows"]]
x <- as.data.frame(x)
for (i in select) {
if (is.null(info$groups[[paste0("attr_", i)]])) {
insight::format_error(
paste(
"Couldn't retrieve the necessary information to unnormalize",
text_concatenate(i, enclose = "`")
)
)
}
}
for (rows in seq_along(grps)) {
# get the dw_transformer attributes for this group
raw_attrs <- unlist(info$groups[rows, startsWith(names(info$groups), "attr")])
if (length(select) == 1L) {
names(raw_attrs) <- paste0("attr_", select, ".", names(raw_attrs))
}
tmp <- unnormalize(
x[grps[[rows]], , drop = FALSE],
select = select,
exclude = exclude,
ignore_case = ignore_case,
regex = regex,
verbose = verbose,
grp_attr_dw = raw_attrs
)
x[grps[[rows]], ] <- tmp
}
# set back class, so data frame still works with dplyr
attributes(x) <- utils::modifyList(info, attributes(x))
class(x) <- c("grouped_df", class(x))
x
}
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