# activeer de renv omgeving;

# renv::activate('~/smartCane/r_app')
# renv::restore()



library(here)
library(sf)
library(terra)
library(tidyverse)
library(lubridate)
# library(exactextractr)
library(readxl)
#funcion CI_prep package


# Vang alle command line argumenten op
args <- commandArgs(trailingOnly = TRUE)

# Controleer of er ten minste één argument is doorgegeven
if (length(args) == 0) {
  stop("Geen argumenten doorgegeven aan het script")
}

# Converteer het eerste argument naar een numerieke waarde
end_date <- as.Date(args[1])


offset <- as.numeric(args[2])
# Controleer of weeks_ago een geldig getal is
if (is.na(offset)) {
  # stop("Het argument is geen geldig getal")
  offset <- 7
}

# Converteer het tweede argument naar een string waarde
project_dir <- as.character(args[3])

# Controleer of data_dir een geldige waarde is
if (!is.character(project_dir)) {
  project_dir <- "chemba"
}


laravel_storage_dir <- here("laravel_app/storage/app", project_dir)
#preparing directories
reports_dir <- here(laravel_storage_dir, "reports")
planet_tif_folder <- here(laravel_storage_dir, "merged_tif")
merged_final <- here(laravel_storage_dir, "merged_final_tif")

new_project_question = FALSE
planet_tif_folder <- here(laravel_storage_dir, "merged_tif")
merged_final <- here(laravel_storage_dir, "merged_final_tif")

data_dir <- here(laravel_storage_dir, "Data")
extracted_CI_dir <- here(data_dir, "extracted_ci")
daily_CI_vals_dir <- here(extracted_CI_dir, "daily_vals")
cumulative_CI_vals_dir <- here(extracted_CI_dir, "cumulative_vals")

weekly_CI_mosaic <- here(laravel_storage_dir, "weekly_mosaic")
daily_vrt <- here(data_dir, "vrt")
harvest_dir <-  here(data_dir, "HarvestData")

source("parameters_project.R")
source("mosaic_creation_utils.R")

dir.create(here(laravel_storage_dir))
dir.create(here(reports_dir))
dir.create(here(data_dir))
dir.create(here(extracted_CI_dir))
dir.create(here(daily_CI_vals_dir))
dir.create(here(cumulative_CI_vals_dir))
dir.create(here(weekly_CI_mosaic))
dir.create(here(daily_vrt))
dir.create(merged_final)
dir.create(harvest_dir)

# end_date <- lubridate::dmy("20-6-2024")
week <- week(end_date)


#weeks_ago = 0

# Creating weekly mosaic
#dates <- date_list(weeks_ago)
dates <- date_list(end_date, offset)

file_name_tif <- as.character(args[4])
if (is.na(file_name_tif)) {
  file_name_tif <- paste0("week_", sprintf("%02d", dates$week), "_", dates$year, ".tif")
}

print(dates)
print(file_name_tif)
#load pivot geojson
# pivot_sf_q <- st_read(here(data_dir, "pivot.geojson")) %>% dplyr::select(pivot, pivot_quadrant) %>% vect()

vrt_files <- list.files(here(daily_vrt),full.names = T)
vrt_list  <- map(dates$days_filter, ~ vrt_files[grepl(pattern = .x, x = vrt_files)]) %>%
  compact() %>%
  flatten_chr()

total_pix_area <- rast(vrt_list[1]) %>% terra::subset(1) %>% setValues(1) %>%
  crop(field_boundaries, mask = TRUE) %>%
  global(., fun="notNA") #%>%

layer_5_list <- purrr::map(vrt_list, function(vrt_list) {
  rast(vrt_list[1]) %>% terra::subset(1)
}) %>% rast()

missing_pixels_count <- layer_5_list %>% global(., fun="notNA") %>%
  mutate(
    total_pixels = total_pix_area$notNA,
    missing_pixels_percentage = round(100 -((notNA/total_pix_area$notNA)*100)),
    thres_5perc = as.integer(missing_pixels_percentage < 5),
    thres_40perc = as.integer(missing_pixels_percentage < 45)
  )

index_5perc <- which(missing_pixels_count$thres_5perc == max(missing_pixels_count$thres_5perc)  )
index_40perc <- which(missing_pixels_count$thres_40perc == max(missing_pixels_count$thres_40perc))

## Create mosaic

if(sum(missing_pixels_count$thres_5perc)>1){
  message("More than 1 raster without clouds (<5%), max composite made")
  
  cloudy_rasters_list <- vrt_list[index_5perc]
  
  rsrc <- sprc(cloudy_rasters_list)
  x <- mosaic(rsrc, fun = "max")
  
  # names(x) <-  "CI"
  names(x) <-  c("Red", "Green", "Blue", "NIR", "CI")
}else if(sum(missing_pixels_count$thres_5perc)==1){
  message("Only 1 raster without clouds (<5%)")
  
  x <- rast(vrt_list[index_5perc[1]])
  # names(x) <-  c("CI")
  names(x) <-  c("Red", "Green", "Blue", "NIR", "CI")
}else if(sum(missing_pixels_count$thres_40perc)>1){
  message("More than 1 image contains clouds, composite made of <40% cloud cover images")
  
  cloudy_rasters_list <- vrt_list[index_40perc]
  
  rsrc <- sprc(cloudy_rasters_list)
  x <- mosaic(rsrc, fun = "max")
  # names(x) <-  "CI"
  names(x) <-  c("Red", "Green", "Blue", "NIR", "CI")
}else if(sum(missing_pixels_count$thres_40perc)==1){
  message("Only 1 image available but contains clouds")
  
  x <- rast(vrt_list[index_40perc[1]])
  # names(x) <-  c("CI")
  names(x) <-  c("Red", "Green", "Blue", "NIR", "CI")
}else{
  message("No cloud free images available, all images combined")
  message(vrt_list)
  rsrc <- sprc(vrt_list)
  x <- mosaic(rsrc, fun = "max")
  # x <-  rast(vrt_list[1]) %>% setValues(NA)
  # names(x) <-  c("CI")
  names(x) <-  c("Red", "Green", "Blue", "NIR", "CI")
}

plot(x$CI, main = paste("CI map ", dates$week))
plotRGB(x, main = paste("RGB map ", dates$week))

file_path_tif <- here(weekly_CI_mosaic ,file_name_tif)
writeRaster(x, file_path_tif, overwrite=TRUE)
message("Raster written/made at: ", file_path_tif)