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bounded_niche = function(g_min, g_max){
#' @export
#'
#' @title define niche from boundaries
#'
#' @param g_min lowest value of the gradient the taxon can tolerate
#' @param g_max highest value of the gradient the taxon can tolerate
#'
#' @seealso
#' * [snd_niche()] for an alternative niche model
#' * [discrete_niche()] for defining niches based on discrete categories
#' * [apply_niche()] for the function that uses the function returned
#' * `vignette("advanced_functionality")` for details how to create user-defined niche models
#'
#' @returns a function describing the niche for usage with `apply_niche`. The function returns 1 if the taxon is within its niche (the gradient is between `g_min` and `g_max`), and 0 otherwise
#'
#' @description
#' Defines a simple niche model where the niche defined is given by a lower limit (`g_min`) and an upper limit (`g_max`) of a gradient the taxon can tolerate
#'
#' @examples
#'
#' x = seq(0, 10, by = 0.2)
#' f = bounded_niche(2,5)
#' plot(x, f(x), type = "l",
#' xlab = "Gradient", ylab = "Observation probability",
#' main = "Observation probability of taxon")
#'
#' # see also
#' #vignette("event_data")
#' # for details how to use this functionality
#'
#'
if (g_max <= g_min){
stop("inconsistent boundaries, inputs must be ordered.")
}
f = function(x){
y = rep(0, length(x))
y[x <= g_max & x >= g_min ] = 1
return(y)
}
return(f)
}
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