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#' @title Create box or violin plots for a BenchmarkResult.
#'
#' @description
#' Plots box or violin plots for a selected `measure` across all iterations
#' of the resampling strategy, faceted by the `task.id`.
#'
#' @template arg_bmr
#' @template arg_measure
#' @param style (`character(1)`)\cr
#' Type of plot, can be \dQuote{box} for a boxplot or \dQuote{violin} for a violin plot.
#' Default is \dQuote{box}.
#' @param pretty.names (`logical(1)`)\cr
#' Whether to use the [Measure] name and the [Learner]
#' short name instead of the id. Default is `TRUE`.
#' @template arg_facet_nrow_ncol
#' @template arg_order_lrns
#' @template arg_order_tsks
#' @template ret_gg2
#' @family plot
#' @family benchmark
#' @export
#' @examples
#' # see benchmark
plotBMRBoxplots = function(bmr, measure = NULL, style = "box", order.lrns = NULL,
order.tsks = NULL, pretty.names = TRUE, facet.wrap.nrow = NULL, facet.wrap.ncol = NULL) {
assertClass(bmr, "BenchmarkResult")
measure = checkBMRMeasure(measure, bmr)
assertChoice(style, c("box", "violin"))
df = as.data.frame(bmr)
df = orderBMRLrns(bmr, df, order.lrns)
df = orderBMRTasks(bmr, df, order.tsks)
if (pretty.names) {
learner.short.names = getBMRLearnerShortNames(bmr)
checkDuplicatedLearnerNames(learner.short.names)
if (!is.null(order.lrns)) {
learner.ids = getBMRLearnerIds(bmr)
names(learner.short.names) = learner.ids
learner.short.names = learner.short.names[order.lrns]
}
levels(df$learner.id) = learner.short.names
}
p = ggplot(df, aes_string("learner.id", measure$id))
p = p + theme(axis.title.x = element_blank(), axis.text.x = element_text(angle = -45, hjust = 0))
p = p + facet_wrap(~task.id, nrow = facet.wrap.nrow, ncol = facet.wrap.ncol)
if (pretty.names) {
p = p + ylab(measure$name)
}
if (style == "box") {
p = p + geom_boxplot()
} else {
p = p + geom_violin() + stat_summary(fun.ymin = median, fun.ymax = median, fun.y = median, geom = "crossbar")
}
return(p)
}
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