R/sp_filtering.R

In mFD: Compute and Illustrate the Multiple Facets of Functional Diversity

#' Retrieve information about species in a given assemblage
#'
#' This function computes names of species present in an given assemblage, 
#' their coordinates in the functional space and their weights. It is used in 
#' the \code{alpha_FD_multidim} function to filter species and compute each
#' functional indices for each community.
#'
#' @param asb_nm a string object referring to the name of a given community.
#'
#' @param sp_faxes_coord a matrix of species coordinates in a chosen functional
#'   space. Species coordinates have been retrieved thanks to
#'   \code{\link{tr.cont.fspace}} or \code{\link{quality.fspaces}}.
#'
#' @param asb_sp_w a matrix linking weight of species (columns) and a
#'   set of assemblages (rows).
#'
#' @return A vector containing names of species present in a given assemblage
#'   \code{sp_name_asb_k}, a matrix containing coordinates of species present 
#'   in a given assemblage \code{sp_faxes_coord_k}, a matrix containing weight 
#'   of species present in a given assemblage \code{asb_sp_w_k}, a matrix
#'   containing relative weight of species present in a given assemblage
#'   \code{asb_sp_relatw_k}.
#'
#' @author Camille Magneville and Sebastien Villeger
#'
#' @export
#'
#' @examples
#' # Load Species*Traits dataframe:
#' data("fruits_traits", package = "mFD")
#' 
#' # Load Assemblages*Species dataframe:      
#' data("baskets_fruits_weights", package = "mFD")
#'  
#' # Load Traits categories dataframe:
#' data("fruits_traits_cat", package = "mFD")  
#' 
#' # Compute functional distance 
#' sp_dist_fruits <- mFD::funct.dist(
#'  sp_tr         = fruits_traits,
#'  tr_cat        = fruits_traits_cat,
#'  metric        = "gower",
#'  scale_euclid  = "scale_center",
#'  ordinal_var   = "classic",
#'  weight_type   = "equal",
#'  stop_if_NA    = TRUE)
#'  
#' # Compute functional spaces quality to retrieve species coordinates matrix:
#' fspaces_quality_fruits <- mFD::quality.fspaces(
#'  sp_dist             = sp_dist_fruits, 
#'  maxdim_pcoa         = 10,
#'  deviation_weighting = "absolute",
#'  fdist_scaling       = FALSE,
#'  fdendro             = "average")
#'  
#' # Retrieve species coordinates matrix:
#' sp_faxes_coord_fruits <- fspaces_quality_fruits$details_fspaces$sp_pc_coord
#' 
#' # Filter species of basket_1 assemblage:
#' sp.filter(asb_nm         = "basket_1", 
#'           sp_faxes_coord = sp_faxes_coord_fruits, 
#'           asb_sp_w       = baskets_fruits_weights)


sp.filter <- function(asb_nm, sp_faxes_coord, asb_sp_w) {
  
  asb_sp_w  <- as.data.frame(asb_sp_w)
  asb_sp_w2 <- asb_sp_w[asb_nm, ]
  
  sp_name_asb_k <- colnames(asb_sp_w2)[which(asb_sp_w2 != 0)]
  sp_faxes_coord_k <- sp_faxes_coord[sp_name_asb_k, , drop = FALSE]
  asb_sp_w_k <- asb_sp_w2[asb_nm, sp_name_asb_k, drop = FALSE]
  asb_sp_relatw_k <- asb_sp_w_k / sum(asb_sp_w_k)
  
  list("species names" = sp_name_asb_k, 
       "species coordinates" = sp_faxes_coord_k, "species weight" = asb_sp_w_k,
       "species relative weight" = asb_sp_relatw_k)
}