R/trainOcc-internal.R

In benmack/oneClass: One-class classification in the absence of test data

################################################################################
.constructtrainOcc <- function(x, u=u, mask=mask, time.train=time.train, 
                               funcCall=funcCall, funcCallUpdate=NULL, ...) {
  
  ### predict u
  dong <- proc.time()
  if (is.null(u)) {
    pred.un.new <- NULL
  } else{
    if (class(u)=="RasterBrick" |
        class(u)=="RasterStack" ) {
      pred.un.new <- predict(u, x, type='prob')
      #browser()
      if (!is.null(mask))
        pred.un.new <- extract(pred.un.new, which(!is.na(values(mask))))
      else
        pred.un.new <- pred.un.new[]
    } else {
      pred.un.new <- predict(x, u, type='prob')$pos
      #    browser()
      #    identical(pred.un.new, x$predUn)
    } 
  }
  time.pred <- proc.time()-dong
  
  ### create the trainOcc objct 
  newX <- structure( c ( x,
                         list(callOc = funcCall,
                              callUpdateOc = funcCallUpdate,
                              dotsOc = list(...), 
                              predUn = pred.un.new,
                              # raster = dummy$raster,
                              timeOc = list(train=time.train, pred=time.pred))),
                     class = c("trainOcc", "train") )
  
  # hist(pred.un)
  # hist(newX$predUn)
  
  
  # names(trainbject)
  #  [1] "method"       "modelInfo"    "modelType"    "results"      "pred"         "bestTune"    
  #  [7] "call"         "dots"         "metric"       "control"      "finalModel"   "preProcess"  
  # [13] "trainingData" "resample"     "resampledCM"  "perfNames"    "maximize"     "yLimits"     
  # [19] "times" 
  return(newX)
}

.Random.seed <-
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