R/plot.predict.downscale.R

In downscale: Downscaling Species Occupancy

################################################################################
# 
# plot.predict.downscale.R
# Version 2.0
# 22/05/2023
#
# Updates:
#   16/05/2023: Simple reformatting
#               inherits for checking class conditions
#   13/03/2015: if 0's predicted don't plot them
#
# Plot the observed and predicted area of occupancy against grain size on
# log-log axes.
#
# Args:
#   x:   an object of class 'predict.downscale' containing observed
#        and predicted data 
#   ...: arguments, including graphical parameters, passed to other methods.
#
# Returns:
#   no object returned.
#
################################################################################

plot.predict.downscale <- function(x,
                                   xlim = NULL,
                                   ylim  = NULL,
                                   xlab = NULL,
                                   ylab = NULL,
                                   main = NULL,
                                   lwd.obs = NULL,
                                   lwd.pred = NULL,
                                   col.obs = NULL,
                                   col.pred = NULL,
                                   ...) {
  predict.object <- x
  
  ### error checking
  if (!inherits(predict.object, "predict.downscale")) {
    stop("Input data not of class 'predict.downscale'")
  }
  
  model.run <- predict.object$model
  observed <- predict.object$observed
  predicted <- predict.object$predicted
  predicted[predicted == 0] <- NA

  ### plotting pars
  if(is.null(xlim)) {
    xlim <- c(min(c(observed$Cell.area, predicted$Cell.area), na.rm = TRUE),
              max(c(observed$Cell.area, predicted$Cell.area), na.rm = TRUE))
  }
  if(is.null(ylim)) {
    ylim <- c(min(c(observed$Occupancy, predicted$Occupancy), na.rm = TRUE), 1)
  }
  if(is.null(xlab)) {
    xlab <- "Log cell area"
  }
  if(is.null(ylab)) {
    ylab <- "Log occupancy"
  }
  if(is.null(main)) {
    main <- paste(model.run, "model")
  }
  if(is.null(col.obs)) {
    col.obs <- "black"
  }
  if(is.null(col.pred)) {
    col.pred <- "red"
  }
  if(is.null(lwd.obs)) {
    lwd.obs <- 2
  }
  if(is.null(lwd.pred)) {
    lwd.pred <- 2
  }

  plot(observed$Occupancy ~ observed$Cell.area,
       type = "n",
       log  = "xy",
       xlim = xlim,
       ylim = ylim,
       xlab = xlab,
       ylab = ylab,
       main = main,
       ...)
  
  points(observed$Occupancy ~ observed$Cell.area,
         type = "b",
         col  = col.obs,
         lwd  = lwd.obs,
         ...)
  
  points(predicted$Occupancy ~ predicted$Cell.area,
         type = "b",
         col  = col.pred,
         lwd  = lwd.pred,
         ...)
}