# DIVERSITY
#' @include AllGenerics.R
NULL
# Index ========================================================================
index_observed <- function(x, ...) {
sum(x > 0, ...) # Number of observed species
}
get_index <- function(x) {
match.fun(sprintf("index_%s", x))
}
do_index <- function(x, method, ...) {
f <- get_index(method)
f(x, ...)
}
#' Compute a Diversity Index
#'
#' @param x A [`numeric`] [`matrix`].
#' @param method A [`character`] string specifying the measure to be computed.
#' @param by_row A [`logical`] scalar: should `method` be computed for each row?
#' @param ... Further parameters to be passed to `method`.
#' @return A [DiversityIndex-class] object.
#' @author N. Frerebeau
#' @keywords internal
#' @noRd
index_diversity <- function(x, method, ..., by_row = TRUE) {
fun <- get_index(method)
if (by_row) {
idx <- apply(X = x, MARGIN = 1, FUN = fun, ...)
} else {
idx <- fun(x, ...)
}
## Fix names
row_names <- rownames(x) %||% paste0("S", seq_along(idx))
.DiversityIndex(
idx,
labels = row_names,
size = as.integer(rowSums(x)),
data = x,
method = method
)
}
# Heterogeneity ================================================================
#' @export
#' @rdname heterogeneity
#' @aliases heterogeneity,matrix-method
setMethod(
f = "heterogeneity",
signature = c(object = "matrix"),
definition = function(object, ...,
method = c("berger", "boone", "brillouin",
"mcintosh", "shannon", "simpson")) {
method <- match.arg(method, several.ok = FALSE)
by_row <- method != "boone"
index <- index_diversity(object, method, ..., evenness = FALSE,
by_row = by_row)
.HeterogeneityIndex(index)
}
)
#' @export
#' @rdname heterogeneity
#' @aliases heterogeneity,data.frame-method
setMethod(
f = "heterogeneity",
signature = c(object = "data.frame"),
definition = function(object, ...,
method = c("berger", "boone", "brillouin",
"mcintosh", "shannon", "simpson")) {
object <- data.matrix(object)
methods::callGeneric(object, ..., method = method)
}
)
# Evenness =====================================================================
#' @export
#' @rdname heterogeneity
#' @aliases evenness,matrix-method
setMethod(
f = "evenness",
signature = c(object = "matrix"),
definition = function(object, ...,
method = c("shannon", "brillouin",
"mcintosh", "simpson")) {
method <- match.arg(method, several.ok = FALSE)
index <- index_diversity(object, method, ..., evenness = TRUE)
.EvennessIndex(index)
}
)
#' @export
#' @rdname heterogeneity
#' @aliases evenness,data.frame-method
setMethod(
f = "evenness",
signature = c(object = "data.frame"),
definition = function(object, ...,
method = c("shannon", "brillouin",
"mcintosh", "simpson")) {
object <- data.matrix(object)
methods::callGeneric(object, ..., method = method)
}
)
# Richness =====================================================================
#' @export
#' @rdname richness
#' @aliases richness,matrix-method
setMethod(
f = "richness",
signature = c(object = "matrix"),
definition = function(object, ..., method = c("observed", "margalef", "menhinick")) {
## Backward compatibility
if (method == "count") method <- "observed"
method <- match.arg(method, several.ok = FALSE)
index <- index_diversity(object, method, ...)
.RichnessIndex(index)
}
)
#' @export
#' @rdname richness
#' @aliases richness,data.frame-method
setMethod(
f = "richness",
signature = c(object = "data.frame"),
definition = function(object, ..., method = c("observed", "margalef", "menhinick")) {
object <- data.matrix(object)
methods::callGeneric(object, ..., method = method)
}
)
# Composition ==================================================================
#' @export
#' @rdname richness
#' @aliases composition,matrix-method
setMethod(
f = "composition",
signature = c(object = "matrix"),
definition = function(object, ...,
method = c("chao1", "ace", "squares", "chao2", "ice")) {
method <- match.arg(method, several.ok = FALSE)
by_row <- any(method == c("chao1", "ace", "squares"))
index <- index_diversity(object, method, ..., by_row = by_row)
.CompositionIndex(index)
}
)
#' @export
#' @rdname richness
#' @aliases composition,data.frame-method
setMethod(
f = "composition",
signature = c(object = "data.frame"),
definition = function(object, ...,
method = c("chao1", "ace", "squares", "chao2", "ice")) {
object <- data.matrix(object)
methods::callGeneric(object, ..., method = method)
}
)
# Turnover =====================================================================
#' @export
#' @rdname turnover
#' @aliases turnover,matrix-method
setMethod(
f = "turnover",
signature = c(object = "matrix"),
definition = function(object, ...,
method = c("whittaker", "cody", "routledge1",
"routledge2", "routledge3", "wilson")) {
method <- match.arg(method, several.ok = FALSE)
fun <- get_index(method)
fun(object)
}
)
#' @export
#' @rdname turnover
#' @aliases turnover,data.frame-method
setMethod(
f = "turnover",
signature = c(object = "data.frame"),
definition = function(object, ...,
method = c("whittaker", "cody", "routledge1",
"routledge2", "routledge3", "wilson")) {
object <- data.matrix(object)
methods::callGeneric(object, ..., method = method)
}
)
# Resample =====================================================================
## Bootstrap -------------------------------------------------------------------
#' @export
#' @rdname bootstrap
#' @aliases bootstrap,DiversityIndex-method
setMethod(
f = "bootstrap",
signature = c(object = "DiversityIndex"),
definition = function(object, n = 1000, f = NULL) {
w <- object@data
m <- nrow(w)
method <- object@method
results <- vector(mode = "list", length = m)
for (i in seq_len(m)) {
results[[i]] <- arkhe::bootstrap(
object = w[i, ],
do = do_index,
n = n,
method = method,
evenness = methods::is(object, "EvennessIndex"),
f = f
)
}
results <- do.call(rbind, results)
rownames(results) <- rownames(w)
as.data.frame(results)
}
)
## Jackknife -------------------------------------------------------------------
#' @export
#' @rdname jackknife
#' @aliases jackknife,DiversityIndex-method
setMethod(
f = "jackknife",
signature = c(object = "DiversityIndex"),
definition = function(object, f = NULL) {
w <- object@data
m <- nrow(w)
method <- object@method
results <- vector(mode = "list", length = m)
for (i in seq_len(m)) {
results[[i]] <- arkhe::jackknife(
object = w[i, ],
do = do_index,
method = method,
evenness = methods::is(object, "EvennessIndex"),
f = f
)
}
results <- do.call(rbind, results)
rownames(results) <- rownames(w)
as.data.frame(results)
}
)
## Simulate --------------------------------------------------------------------
#' @export
#' @rdname simulate
#' @aliases simulate,DiversityIndex-method
setMethod(
f = "simulate",
signature = c(object = "DiversityIndex"),
definition = function(object, n = 1000, step = 1,
interval = c("percentiles", "student", "normal"),
level = 0.80, progress = getOption("tabula.progress")) {
## Simulate
## Specify the probability for the classes
data <- object@data
method <- object@method # Select method
## Sample size
size <- max(rowSums(data))
sample_sizes <- seq(from = 1, to = size * 1.05, by = step)
m <- length(sample_sizes)
k <- seq_len(m)
simulated <- vector(mode = "list", length = m)
fun <- function(x) conf(x, level = level, type = interval)
progress_bar <- interactive() && progress
if (progress_bar) pbar <- utils::txtProgressBar(max = m, style = 3)
for (i in k) {
simulated[[i]] <- resample(
object = colSums(data),
do = do_index,
method = method,
evenness = methods::is(object, "EvennessIndex"),
n = n,
size = sample_sizes[[i]],
f = fun
)
if (progress_bar) utils::setTxtProgressBar(pbar, i)
}
if (progress_bar) close(pbar)
simulated <- do.call(rbind, simulated)
simulated <- cbind(size = sample_sizes, simulated)
methods::initialize(object, simulation = simulated)
}
)
conf <- function(x, type = c("percentiles", "student", "normal"),
level = 0.80) {
type <- match.arg(type, several.ok = FALSE)
if (type == "percentiles") {
## Confidence interval as described in Kintigh 1989
k <- (1 - level) / 2
conf <- stats::quantile(x, probs = c(k, 1 - k), names = FALSE)
} else {
## Confidence interval
conf <- arkhe::confidence_mean(x, level = level, type = type)
}
result <- c(mean(x), conf)
names(result) <- c("mean", "lower", "upper")
result
}
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