# -----------------   to be used to  prepare summary table for publication -----------
# ---------  load libraries to  be used -----------------------------------
libs <- c('tidyverse','lubridate','purrr','here','SSDM','raster','parallel',
          'rworldmap','rworldxtra','sf','raster');
lapply(libs, library,character.only=TRUE)

# ------- search and  saved SSDM object for each species ------------------
list_no_thin <- list.files('analysis/out_ssdm_no_thin/',pattern = '.RData')
list_thin <- list.files('analysis/out_ssdm_thin/',pattern = '.RData')

# ------- prepare list of species and season ------------------------------
species_season_no_thin <- str_remove_all(list_no_thin,pattern = '.RData')
species_season_thin  <-str_remove_all(list_thin,pattern = '.RData')

# ------ load actual objects ----------------------------------------------
mod_obj_no_thin <-sapply(here::here('analysis/out_ssdm_no_thin',list_no_thin), 
                         function(x) mget(load(x)),simplify = TRUE)
mod_obj_thin <- sapply(here::here('analysis/out_ssdm_thin',list_thin),
                       function(x) mget(load(x)),simplify = TRUE)
names(mod_obj_no_thin) =  species_season_no_thin
names(mod_obj_thin) = species_season_thin

# --------- list of models considered -------------------------------------
models_sel <- c('CTA', 'SVM','GLM','MARS','GBM','RF','ANN')

# --------------------- get source file for  data processing --------------
source('R/000_custom_utility_functions.R')

# ---------- get occurrence and background data ---------------------------
system.time(all_occ_bkgnd_thin <- purrr::map(mod_obj_thin,.f = function(x = .x) get_occ_background(model_object = x)))
system.time(all_occ_bkgnd_noThin <- purrr::map(mod_obj_no_thin,.f = function(x = .x) get_occ_background(model_object = x)))


# ------ select part of the data to be used for visualization -------------
tmp_sel_fun  =  function(dat){
  lapply(X = dat, function(x = X) {
    if(nrow(x)==0){
      x
    }
    else{
      x%>%dplyr::rename(lon = X, lat =Y,reps = model_index)%>%
        dplyr::select(c(reps,lon,lat,Presence,train))%>%as_tibble()
    }})
  
}


# --- subset the  occurrence data -----------------------------------------
sub_occ_thin <-  purrr::map(.x = all_occ_bkgnd_thin, 
                            .f = ~tmp_sel_fun(dat = .x)%>%purrr::map_df(.f = rbind,.id = 'Model'))
sub_occ_noThin <-  purrr::map(.x = all_occ_bkgnd_noThin, 
                              .f = ~tmp_sel_fun(dat = .x)%>%purrr::map_df(.f = rbind,.id = 'Model'))

# ------ process background and occurrence data ---------------------------
occAbs_noThin = tibble(species_season = species_season_no_thin,
                                occBkg = sub_occ_noThin)
occAbs_thin = tibble(species_season = species_season_thin,
                              occBkg = sub_occ_thin)


# ------------ process species and season label ---------------------------
occAbs_thin <- occAbs_thin%>%
  mutate(species_season =  species_season%>%str_remove_all(pattern = ".Ensemble.SDM"))%>%
  separate(col = species_season,into = c('species','season'),sep = '_',remove = FALSE)
occAbs_noThin <- occAbs_noThin%>%
  mutate(species_season =  species_season%>%str_remove_all(pattern = ".Ensemble.SDM"))%>%
  separate(col = species_season,into = c('species','season'),sep = '_',remove = FALSE)


# ------  prepare tables of occurrence and background data ----------------
occAbs_thin_df  = occAbs_thin%>%unnest(cols = occBkg)
occAbs_no_thin_df = occAbs_noThin%>%unnest(cols = occBkg)


# ------------- get summary tables ----------------------------------------
summ_occBkgd_thin = occAbs_thin_df%>%
  group_by(species,season,Model,reps)%>%
  summarise(Occurrence =  sum(Presence==1,na.rm = TRUE),
            Background = sum(Presence==0,na.rm = TRUE))%>%
  ungroup()

summ_occBkgd_noThin = occAbs_no_thin_df%>%
  group_by(species,season,Model,reps)%>%
  summarise(Occurrence =  sum(Presence==1,na.rm = TRUE),
            Background = sum(Presence==0,na.rm = TRUE))%>%
  ungroup()


# --------  combined tables (thinned-unthinned data) ----------------------
comb_sum_table = summ_occBkgd_noThin%>%filter(reps == 1)%>%
  left_join(summ_occBkgd_thin%>%filter(reps ==1)%>%
              dplyr::rename(Occurrence_thin = Occurrence,Background_thin = Background))%>%
  dplyr::select(-reps)

# ------- write  model table to  file -------------------------------------
write_csv(x = comb_sum_table,path = 'analysis/occ-background_table.csv')