bioclim_UI <- function(id) {
ns <- NS(id)
tagList(
)
}
bioclim_MOD <- function(input, output, session, rvs) {
reactive({
if (is.null(rvs$occsGrp)) {
rvs %>% writeLog(type = 'error', "Before building a model, partition
occurrences in component 5.")
return()
}
occs.xy <- rvs$occs %>% dplyr::select(longitude, latitude)
e <- BioClim_eval(occs.xy, rvs$bgPts, rvs$occsGrp, rvs$bgGrp, rvs$bgMsk)
# occVals <- raster::extract(e$predictions, values$modParams$occ.pts)
#
# values$mtps <- min(occVals) # apply minimum training presence threshold
#
# # Define 10% training presence threshold
# if (length(occVals) < 10) { # if less than 10 occ values, find 90% of total and round down
# n90 <- floor(length(occVals) * 0.9)
# } else { # if greater than or equal to 10 occ values, round up
# n90 <- ceiling(length(occVals) * 0.9)
# }
#
# values$p10s <- rev(sort(occVals))[n90] # apply 10% training presence threshold
rvs %>% writeLog("BIOCLIM ran successfully and output evaluation results.")
return(e)
})
}
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