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#' Calculate Oscillations for Ceteris Paribus Explainer
#'
#' @param x a ceteris_paribus explainer produced with the `ceteris_paribus()` function
#' @param sort a logical value. If TRUE then rows are sorted along the oscillations
#' @param ... other arguments
#'
#' @export
#'
#' @examples
#' library("DALEX")
#' \dontrun{
#' library("randomForest")
#' set.seed(59)
#'
#' apartments_rf_model <- randomForest(m2.price ~ construction.year + surface + floor +
#' no.rooms + district, data = apartments)
#'
#' explainer_rf <- explain(apartments_rf_model,
#' data = apartmentsTest, y = apartmentsTest$m2.price)
#'
#' apartment <- apartmentsTest[1,]
#'
#' cp_rf <- ceteris_paribus(explainer_rf, apartment)
#' calculate_oscillations(cp_rf)
#' }
calculate_oscillations <- function(x, sort = TRUE, ...) {
stopifnot("ceteris_paribus_explainer" %in% class(x))
observations <- attr(x, "observations")
variables <- unique(as.character(x$`_vname_`))
ids <- unique(as.character(x$`_ids_`))
lapply(variables, function(variable) {
lapply(ids, function(id) {
diffs <- x[x$`_vname_` == variable & x$`_ids_` == id,"_yhat_"] - observations[id,"_yhat_"]
data.frame(`_vname_` = variable, `_ids_` = id, oscillations = mean(abs(diffs)))
}) -> tmp
do.call(rbind, tmp)
}) -> tmp
res <- do.call(rbind, tmp)
colnames(res) <- c("_vname_", "_ids_", "oscillations")
if (sort) {
res <- res[order(res$oscillations, decreasing = TRUE),]
}
class(res) = c("ceteris_paribus_oscillations", "data.frame")
res
}
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