R/QuickGRaF.R

In zoonproject/modules: Species Distribution Modelling Code Modules for the ZOON Package

#' @title Model module: QuickGRaF
#'
#' @description Model module to fit a quick GRaF model, without parameter optimisation.
#'
#' @param .df \strong{Internal parameter, do not use in the workflow function}. \code{.df} is data frame that combines the occurrence data and covariate data. \code{.df} is passed automatically in workflow from the process module(s) to the model module(s) and should not be passed by the user.
#'
#' @param l lengthscale parameter, a positive number controlling the complexity
#' of the fitted model with respect to each covariate.
#' Can either be a single number (in which case it is used for all covariates),
#' a vector of numbers of the same length as the number of covariates,
#' or \code{NULL} in which case GRaF will calculate a fixed approximation to
#' a sensible lengthscale.
#' 
#' @author ZOON Developers, \email{zoonproject@@gmail.com}
#' @section Version: 1.0
#' @section Date submitted: 2015-11-13
#' @section Data type: presence/absence
#' @name QuickGRaF
#' @family model
QuickGRaF <-
function (.df, l = NULL) {
  
  zoon:::GetPackage('GRaF')
  
  if (!all(.df$type %in% c('presence', 'absence', 'background'))) {
    stop ('only for presence/absence or presence/background data')
  }
  
  # get the covariates
  covs <- as.data.frame(.df[, attr(.df, 'covCols')])
  names(covs) <- attr(.df, 'covCols')
  
  # set up l
  if (!is.null(l)) {
    
    # duplicate if necessary
    if (length(l) == 1) {
      l <- rep(l, ncol(covs))
    }

    # check l has the correct length
    if (length(l) != ncol(covs)) {
      stop (sprintf('l has %i elements, but there are %i covariates', length(l), ncol(covs)))
    }
  
    # check l is of the correct value
    if (any(l <= 0)) {
      stop(sprintf('l must be positive, but the values provided were: %s',
                   paste(format(l, digits = 3), collapse = ', ')))
    }
  }
  # fit the model
  m <- graf(.df$value,
            covs,
            l = l)
  
  ZoonModel(model = m,
            code = {
              GRaF::predict.graf(model,
                                newdata,
                                type = 'response')[, 1]
            },
            packages = 'GRaF')
}