R/fortify.cca.R

Defines functions `fortify.cca`

#' @title Fortify a \code{"cca"} object.
#'
#' @description
#' Fortifies an object of class \code{"cca"} to produce a
#' data frame of the selected axis scores in long format, suitable for
#' plotting with \code{\link[ggplot2]{ggplot}}.
#'
#' @details
#' TODO
#'
#' @param model an object of class \code{"cca"}, the result of a call to
#' \code{\link[vegan]{cca}}, \code{\link[vegan]{rda}}, or
#' \code{\link[vegan]{capscale}}.
#' @param data currently ignored.
#' @param axes numeric; which axes to extract scores for.
#' @param display numeric; the scores to extract in the fortified object.
#' @param ... additional arguments passed to \code{\link[vegan]{scores.cca}},
#'   and \code{\link[vegan]{scores.rda}}.
#' @return A data frame in long format containing the ordination scores.
#' The first two components are the axis scores.
#' @author Gavin L. Simpson
#'
#' @export
#'
#' @importFrom ggplot2 fortify
#' @importFrom vegan scores
#'
#' @examples
#' data(dune)
#' data(dune.env)
#'
#' sol <- cca(dune ~ A1 + Management, data = dune.env)
#' head(fortify(sol))
`fortify.cca` <- function(model, data, axes = 1:6,
                          display = c("sp", "wa", "lc", "bp", "cn"), ...) {
    ## extract scores
    scrs <- scores(model, choices = axes, display = display, ...)
    ## handle case of only 1 set of scores
    if (length(display) == 1L) {
        scrs <- list(scrs)
        nam <- switch(display,
                      sp = "species",
                      species = "species",
                      wa = "sites",
                      sites = "sites",
                      lc = "constraints",
                      bp = "biplot",
                      cn = "centroids",
                      stop("Unknown value for 'display'"))
        names(scrs) <- nam
    }
    miss <- vapply(scrs, function(x ) all(is.na(x)), logical(1L))
    scrs <- scrs[!miss]
    nams <- names(scrs)
    nr <- vapply(scrs, FUN = NROW, FUN.VALUE = integer(1))
    df <- do.call('rbind', scrs)
    rownames(df) <- NULL
    df <- as.data.frame(df)
    df <- cbind(score = factor(rep(nams, times = nr)),
                label = unlist(lapply(scrs, rownames), use.names = FALSE),
                df)
    df
}
gavinsimpson/ggvegan documentation built on July 28, 2023, 9:24 a.m.