R/summary.trophicSDMfit.R

In webSDM: Including Known Interactions in Species Distribution Models

#' Summary of a fitted trophicSDM model
#' 
#' @param object A trophicSDMfit object obtained with trophicSDM()
#' @param ... 	additional arguments
#' @return Prints a summary of the fitted trophic SDM
#' @author Giovanni Poggiato
#' @examples
#' data(Y, X, G)
#' # define abiotic part of the model
#' env.formula = "~ X_1 + X_2"
#' # Run the model with bottom-up control using stan_glm as fitting method and no penalisation
#' # (set iter = 1000 to obtain reliable results)
#' m = trophicSDM(Y, X, G, env.formula, iter = 100,
#'                family = binomial(link = "logit"), penal = NULL, 
#'                mode = "prey", method = "stan_glm")
#' summary(m)
#' @method summary trophicSDMfit
#' @export

summary.trophicSDMfit = function(object,  ...){
  
  tSDM = object

  if(!inherits(tSDM, "trophicSDMfit")) stop("tSDM is not an object of class trophicSDMfit" )

    model = paste0("A trophicSDM fit with ", ifelse(is.null(tSDM$model.call$penal), "no", tSDM$model.call$penal)," penalty, ",
    "fitted using ", tSDM$model.call$method,
    " \n with a ", ifelse(tSDM$model.call$mode == "prey", "bottom-up", "top-down"), " approach \n",
    " \n Number of species : ", tSDM$data$S,
    " \n Number of links : ", length(igraph::E(tSDM$data$G)),
    " \n")
    cat("==================================================================\n")
    cat(model)
    cat("==================================================================\n")
    cat("* Useful fields\n")
    cat("    $coef \n")
    cat("* Useful S3 methods\n")
    cat("    print(), coef(), plot(), predict(), evaluateModelFit() \n")
    cat("    predictPotential(), plotG(), plotG_inferred(), computeVariableImportance() \n")
    cat("* Local models (i.e. single species SDM) can be accessed through \n")
    cat("    $model\n")
    
    #Just to fix pkgdown
    invisible(object)
}