Visual tests currently differ between R-release and R-devel. This is a known issue linked with a bug fix in upstream R (r-lib/vdiffr#86). This commit updates the test and skips them in R-release.
xrobin
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#' Returns the coords as a data.frame in the right ordering for ggplot2
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get.coords.for.ggplot <- function(roc) { |
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df <- coords(roc, "all", transpose = FALSE) |
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return(df[rev(seq(nrow(df))),]) |
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}
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get.aes.for.ggplot <- function(roc, legacy.axes, extra_aes = c()) { |
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# Prepare the aesthetics
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if(roc$percent) { |
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if (legacy.axes) { |
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aes_list <- list(x = "1-specificity", y = "sensitivity") |
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xlims <- ggplot2::scale_x_continuous(lim=c(0, 100)) |
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}
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else { |
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aes_list <- list(x = "specificity", y = "sensitivity") |
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xlims <- ggplot2::scale_x_reverse(lim=c(100, 0)) |
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}
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}
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else { |
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if (legacy.axes) { |
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aes_list <- list(x = "1-specificity", y = "sensitivity") |
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xlims <- ggplot2::scale_x_continuous(lim=c(0, 1)) |
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}
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else { |
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aes_list <- list(x = "specificity", y = "sensitivity") |
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xlims <- ggplot2::scale_x_reverse(lim=c(1, 0)) |
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}
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}
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# Add extra aes
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for (ae in extra_aes) { |
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aes_list[[ae]] <- "name" |
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}
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aes <- do.call(ggplot2::aes_string, aes_list) |
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return(list(aes=aes, xlims=xlims)) |
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}
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load.ggplot2 <- function() { |
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if (! isNamespaceLoaded("ggplot2")) { |
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message('You may need to call library(ggplot2) if you want to add layers, etc.') |
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}
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load.suggested.package("ggplot2") |
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}
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ggroc <- function(data, ...) { |
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UseMethod("ggroc") |
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}
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ggroc.roc <- function(data, legacy.axes = FALSE, ...) { |
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load.ggplot2()
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# Get the roc data with coords
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df <- get.coords.for.ggplot(data) |
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# Prepare the aesthetics
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aes <- get.aes.for.ggplot(data, legacy.axes) |
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# Do the plotting
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ggplot2::ggplot(df) + ggplot2::geom_line(aes$aes, ...) + aes$xlims |
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}
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ggroc.list <- function(data, aes = c("colour", "alpha", "linetype", "size", "group"), legacy.axes = FALSE, ...) { |
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load.ggplot2()
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if (missing(aes)) { |
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aes <- "colour" |
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}
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aes <- sub("color", "colour", aes) |
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aes <- match.arg(aes, several.ok = TRUE) |
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# Make sure data is a list and every element is a roc object
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if (! all(sapply(data, methods::is, "roc"))) { |
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stop("All elements in 'data' must be 'roc' objects.") |
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}
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# Make sure percent is consistent
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percents <- sapply(data, `[[`, "percent") |
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if (!(all(percents) || all(!percents))) { |
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stop("ROC curves use percent inconsistently and cannot be plotted together") |
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}
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# Make sure the data is a named list
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if (is.null(names(data))) { |
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names(data) <- seq(data) |
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}
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# Make sure names are unique:
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if (any(duplicated(names(data)))) { |
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stop("Names of 'data' must be unique") |
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}
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# Get the coords
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coord.dfs <- sapply(data, get.coords.for.ggplot, simplify = FALSE) |
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# Add a "name" colummn
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for (i in seq_along(coord.dfs)) { |
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coord.dfs[[i]]$name <- names(coord.dfs)[i] |
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}
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# Make a big data.frame
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coord.dfs <- do.call(rbind, coord.dfs) |
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coord.dfs$name <- factor(coord.dfs$name, as.vector(names(data))) |
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# Prepare the aesthetics
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aes.ggplot <- get.aes.for.ggplot(data[[1]], legacy.axes, aes) |
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# Do the plotting
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ggplot2::ggplot(coord.dfs, aes.ggplot$aes) + ggplot2::geom_line(...) + aes.ggplot$xlims |
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}
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