# utils for mosaic creation

date_list <- function(end_date, offset){
  offset <- as.numeric(offset) - 1
  end_date <- as.Date(end_date)
  start_date <- end_date - lubridate::days(offset)
  
  week <- week(start_date)
  year <- year(start_date)
  days_filter <- seq(from = start_date, to = end_date, by = "day")
  
  return(list("week" = week, "year" = year, "days_filter" = days_filter))
}

# date_list <- function(weeks_in_the_paste){
#   week <- week(Sys.Date()- weeks(weeks_in_the_paste) )
#   year <- year(Sys.Date()- weeks(weeks_in_the_paste) )
#   days_filter <- Sys.Date() - weeks(weeks_in_the_paste) - days(0:6)
#
#   return(c("week" = week,
#            "year" = year,
#            "days_filter" = list(days_filter)))
#
# }
create_mask_and_crop <- function(file, field_boundaries) {
  # file <- filtered_files[5]
  message("starting ", file)
  loaded_raster <- rast(file)
  names(loaded_raster) <- c("Red", "Green", "Blue", "NIR")
  #   names(CI) <- c("green","nir")
  message("raster loaded")
  
  # CI <- CI[[2]] / CI[[1]] - 1
  CI <- loaded_raster$NIR / loaded_raster$Green - 1
  
  loaded_raster$CI <- CI
  #   CI <- CI$nir/CI$green-1
  message("CI calculated")
  loaded_raster <- terra::crop(loaded_raster, field_boundaries, mask = TRUE) #%>% CI_func()
  
  loaded_raster[loaded_raster == 0] <- NA
  # names(v_crop) <- c("red", "green", "blue","nir", "cloud" ,"CI")
  # v_crop$CI <- v_crop$CI - 1
  new_file <- here(merged_final, paste0(tools::file_path_sans_ext(basename(file)), ".tif"))
  writeRaster(loaded_raster, new_file, overwrite = TRUE)
  
  vrt_file <- here(daily_vrt, paste0(tools::file_path_sans_ext(basename(file)), ".vrt"))
  terra::vrt(new_file, vrt_file, overwrite = TRUE)
  
  # v_crop <- mask_raster(v, pivot_sf_q)
  return(loaded_raster)
}

CI_func <- function(x, drop_layers = FALSE){
  CI <- x[[4]]/x[[2]]-1
  add(x) <- CI
  names(x) <- c("red", "green", "blue","nir", "cloud" ,"CI")
  if(drop_layers == FALSE){
    return(x)
  }else{
    return(x$CI)
  }
}

mask_raster <- function(raster, fields){
  # x <- rast(filtered_files[1])
  x <- rast(raster) 
  emtpy_or_full <- global(x, sum)
  
  if(emtpy_or_full[1,] >=  2000000){
    names(x) <- c("red", "green", "blue","nir", "cloud")
    cloud <- x$cloud
    
    cloud[cloud == 0 ] <- NA
    x_masked <- mask(x, cloud, inverse = T) %>% crop(.,fields, mask = TRUE )
    x_masked <-  x_masked %>% CI_func()
    
    message(raster, " masked")
    return(x_masked)
  }
}

date_extract <- function(file_path) {
  str_extract(file_path, "\\d{4}-\\d{2}-\\d{2}")
}



right = function(text, num_char) {
  substr(text, nchar(text) - (num_char-1), nchar(text))
}

# load_fields <- function(geojson_path) {
#   field_geojson <- st_read(geojson_path) %>%
#     select(pivot, pivot_quadrant) %>%
#     vect()
#   return(field_geojson)
# }
# 
# load_harvest_data <- function(havest_data_path){
#   harvest_data <- readRDS(havest_data_path)
#   return(harvest_data)
# }

# load_rasters <- function(raster_path, dates) {
#   raster_files <- list.files(raster_path, full.names = TRUE, pattern = ".tif")
#   filtered_files <- map(dates$days_filter, ~ raster_files[grepl(pattern = .x, x = raster_files)]) %>%
#     compact() %>%
#     flatten_chr()
#   
#   return(filtered_files)
# }

# mask_and_set_names <- function(filtered_files, fields) {
#   rasters_masked <- map(filtered_files, mask_raster, fields = fields) %>% set_names(filtered_files)
#   rasters_masked[sapply(rasters_masked, is.null)] <- NULL
#   rasters_masked <- setNames(rasters_masked, map_chr(names(rasters_masked), date_extract))
#   
#   return(rasters_masked)
# }

# calculate_total_pix_area <- function(filtered_files, fields_geojson) {
#   # total_pix_area <- rast(filtered_files[1]) %>%
#   #   subset(1) %>%
#   #   crop(fields_geojson, mask = TRUE)%>%
#   #   global(.data, fun = "notNA")
#   total_pix_area <- rast(filtered_files[1]) %>% subset(1) %>% crop(fields_geojson, mask = TRUE) %>% freq(., usenames = TRUE)
#   
#   return(total_pix_area)
# }

# cloud_layer_extract <- function(rasters_masked){
#   cloud_layer_rast <- map(rasters_masked, function(spatraster) {
#     spatraster[[5]]
#   }) %>% rast()
#   
#   return(cloud_layer_rast)
# }

# calculate_cloud_coverage <- function(cloud_layer_rast, total_pix_area) {
#   cloud_perc_list <- freq(cloud_layer_rast, usenames = TRUE) %>%
#     mutate(cloud_perc = (100 -((count/total_pix_area$count)*100)),
#            cloud_thres_5perc = as.integer(cloud_perc < 5),
#            cloud_thres_40perc = as.integer(cloud_perc < 40)) %>%
#     rename(Date = layer) %>% select(-value, -count)
#   
#   cloud_index_5perc <- which(cloud_perc_list$cloud_thres_5perc == max(cloud_perc_list$cloud_thres_5perc))
#   cloud_index_40perc <- which(cloud_perc_list$cloud_thres_40perc == max(cloud_perc_list$cloud_thres_40perc))
#   
#   return(list(cloud_perc_list = cloud_perc_list, cloud_index_5perc = cloud_index_5perc, cloud_index_40perc = cloud_index_40perc))
# }

process_cloud_coverage <- function(cloud_coverage, rasters_masked) {
  if (sum(cloud_coverage$cloud_perc_list$cloud_thres_5perc) > 1) {
    message("More than 1 raster without clouds (<5%), max mosaic made ")
    
    cloudy_rasters_list <- rasters_masked[cloud_coverage$cloud_index_5perc]
    rsrc <- sprc(cloudy_rasters_list)
    x <- mosaic(rsrc)
    names(x) <-  c("red", "green", "blue", "nir", "cloud", "CI")
    
  } else if (sum(cloud_coverage$cloud_perc_list$cloud_thres_5perc) == 1) {
    message("Only 1 raster without clouds (<5%)")
    
    x <- rast(rasters_masked[cloud_coverage$cloud_index_5perc[1]])
    names(x) <-  c("red", "green", "blue", "nir", "cloud", "CI")
    
  } else if (sum(cloud_coverage$cloud_perc_list$cloud_thres_40perc) > 1) {
    message("More than 1 image contains clouds, composite made of <40% cloud cover images")
    
    cloudy_rasters_list <- rasters_masked[cloud_coverage$cloud_index_40perc]
    rsrc <- sprc(cloudy_rasters_list)
    x <- mosaic(rsrc)
    names(x) <-  c("red", "green", "blue", "nir", "cloud", "CI")
    
  } else if (sum(cloud_coverage$cloud_perc_list$cloud_thres_40perc) == 0) {
    message("No cloud free images available")
    x <-  rast(rasters_masked[1])
    x[x] <- NA
    names(x) <-  c("red", "green", "blue", "nir", "cloud", "CI")
  }
  
  return(x)
}


#functions for CI_data_prep
# create_mask_and_crop <- function(file, pivot_sf_q) {
#   # file <- filtered_files[5]
#   message("starting ", file)
#   loaded_raster <- rast(file)
#   names(loaded_raster) <- c("Red", "Green", "Blue", "NIR")
#   #   names(CI) <- c("green","nir")
#   message("raster loaded")
#   
#   # CI <- CI[[2]] / CI[[1]] - 1
#   CI <- loaded_raster$NIR / loaded_raster$Green - 1
#   
#   loaded_raster$CI <- CI
#   #   CI <- CI$nir/CI$green-1
#   message("CI calculated")
#   loaded_raster <- terra::crop(loaded_raster, pivot_sf_q, mask = TRUE) #%>% CI_func()
#   
#   loaded_raster[loaded_raster == 0] <- NA
#   # names(v_crop) <- c("red", "green", "blue","nir", "cloud" ,"CI")
#   # v_crop$CI <- v_crop$CI - 1
#   new_file <- here(merged_final, paste0(tools::file_path_sans_ext(basename(file)), ".tif"))
#   writeRaster(loaded_raster, new_file, overwrite = TRUE)
#   
#   vrt_file <- here(daily_vrt, paste0(tools::file_path_sans_ext(basename(file)), ".vrt"))
#   terra::vrt(new_file, vrt_file, overwrite = TRUE)
#   
#   # v_crop <- mask_raster(v, pivot_sf_q)
#   return(loaded_raster)
# }