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To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.

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content badge Iframe embedding
swh:1:cnt:8a5d8ce22331b5af9c0b3dccae7855530d2eb3f7
Citations

This interface enables to generate software citations, provided that the root directory of browsed objects contains a citation.cff or codemeta.json file.
Select below a type of object currently browsed in order to generate citations for them.

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Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
#' Plot a metric over all possible cutoffs from a cutpointr object
#'
#' If \code{maximize_metric} is used as \code{method} function in cutpointr the computed
#' metric values over all possible cutoffs can be plotted. Generally, this
#' works for method functions that return a ROC-curve including the metric
#' value for every cutpoint along with the optimal cutpoint.
#'
#' @param x A cutpointr object.
#' @param conf_lvl The confidence level of the bootstrap confidence interval.
#' Set to 0 to draw no bootstrap confidence interval.
#' @examples
#' opt_cut <- cutpointr(suicide, dsi, suicide)
#' plot_metric(opt_cut)
#' @importFrom dplyr %>%
#' @family cutpointr plotting functions
#' @family cutpointr plotting functions
#' @export
plot_metric <- function(x, conf_lvl = 0.95) {
    stopifnot("cutpointr" %in% class(x))
    if (!(has_column(x$roc_curve[[1]], "m"))) {
        stop(paste("The cutpointr object does not include a metric column in",
                   "roc_curve - maybe because a method other than",
                   "maximize_metric or minimize_metric was used"))
    }

    if (has_boot_results(x) & conf_lvl != 0) {
        if (has_column(x, "subgroup")) {
            roc_b_unnested <- x %>%
                dplyr::select_(.dots = c("boot", "subgroup")) %>%
                dplyr::mutate_(boot = ~ prepare_bind_rows(boot)) %>%
                tidyr::unnest_(unnest_cols = "boot") %>%
                dplyr::select_(.dots = c("subgroup", "roc_curve_b")) %>%
                tidyr::unnest_(unnest_cols = "roc_curve_b")
            roc_b_unnested <- roc_b_unnested[is.finite(roc_b_unnested$x.sorted), ]
            roc_b_unnested <- roc_b_unnested %>%
                dplyr::select_(.dots = c("x.sorted", "m", "subgroup")) %>%
                dplyr::group_by_(.dots = c("x.sorted", "subgroup")) %>%
                dplyr::summarise_(ymin = ~ stats::quantile(m, (1 - conf_lvl) / 2, na.rm = TRUE),
                                  ymax = ~ stats::quantile(m, 1 - (1 - conf_lvl) / 2, na.rm = TRUE))
        } else {
            roc_b_unnested <- x[["boot"]][[1]] %>%
                tidyr::unnest_(unnest_cols = "roc_curve_b")
            roc_b_unnested <- roc_b_unnested[is.finite(roc_b_unnested$x.sorted), ]
            roc_b_unnested <- roc_b_unnested %>%
                dplyr::select_(.dots = c("x.sorted", "m")) %>%
                dplyr::group_by_(.dots = "x.sorted") %>%
                dplyr::summarise_(ymin = ~ stats::quantile(m, (1 - conf_lvl) / 2, na.rm = TRUE),
                                  ymax = ~ stats::quantile(m, 1 - (1 - conf_lvl) / 2, na.rm = TRUE))
        }
    }
    metric_name <- find_metric_name(x)
    if ("subgroup" %in% colnames(x)) {
        res_unnested <- x %>%
            dplyr::select_(.dots = c("roc_curve", "subgroup")) %>%
            tidyr::unnest_(unnest_cols = "roc_curve")
        res_unnested <- res_unnested[is.finite(res_unnested$x.sorted),
                                     c("x.sorted", "m", "subgroup")]
        if (has_boot_results(x) & conf_lvl != 0) {
            res_unnested <- merge(res_unnested,
                                  roc_b_unnested[, c("subgroup", "x.sorted", "ymin", "ymax")],
                                  by = c("x.sorted", "subgroup"))
            p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted,
                                                             y = ~ m,
                                                             ymin = ~ ymin,
                                                             ymax = ~ ymax,
                                                             color = ~ subgroup,
                                                             fill = ~ subgroup)) +
                ggplot2::geom_line() +
                ggplot2::geom_point() +
                ggplot2::ggtitle("Metric values by cutpoint value",
                                 "in-sample results") +
                ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint") +
                ggplot2::geom_ribbon(alpha = 0.2, size = 0)
        } else {
            p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted,
                                                             y = ~ m,
                                                             color = ~ subgroup)) +
                ggplot2::geom_line() + ggplot2::geom_point() +
                ggplot2::ggtitle("Metric values by cutpoint value",
                                 "in-sample results") +
                ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint")
        }
    } else {
        res_unnested <- x %>%
            dplyr::select_(.dots = "roc_curve") %>%
            tidyr::unnest_(unnest_cols = "roc_curve")
        res_unnested <- res_unnested[is.finite(res_unnested$x.sorted),
                                     (c("x.sorted", "m"))]
        if (has_boot_results(x) & conf_lvl != 0) {
            res_unnested <- merge(res_unnested,
                                  roc_b_unnested[, c("x.sorted", "ymin", "ymax")],
                                  by = "x.sorted")
            p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted,
                                                             y = ~ m,
                                                             ymax = ~ ymax,
                                                             ymin = ~ ymin)) +
                ggplot2::geom_line() + ggplot2::geom_point() +
                ggplot2::ggtitle("Metric values by cutpoint value",
                                 "in-sample results") +
                ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint") +
                ggplot2::geom_ribbon(alpha = 0.2, size = 0)
        } else {
            p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted,
                                                             y = ~ m)) +
                ggplot2::geom_line() + ggplot2::geom_point() +
                ggplot2::ggtitle("Metric values by cutpoint value",
                                 "in-sample results") +
                ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint")
        }
    }
    return(p)
}

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The source code of Software Heritage itself is available on our development forge.
The source code files archived by Software Heritage are available under their own copyright and licenses.
Terms of use: Archive access, API— Contact— JavaScript license information— Web API

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