#MODIFIED ON: 10/10/2016            

#COMMIT: generating animation for reg6 (Australia and South East Asia)

function_product_assessment_part2_functions <- "global_product_assessment_part2_functions_10102016b.R"

in_dir_mosaic <- "/data/project/layers/commons/NEX_data/climateLayers/out/reg6/mosaics/mosaic"

check_missing <- function(lf, pattern_str=NULL,in_dir=".",date_start="1984101",date_end="20141231",item_no=13,out_suffix=""){

  #Function to check for missing files such as mosaics or predictions for tiles etc.

  #The function assumes the name of the files contain "_".

  #INPUTS:

  #lf

  #pattern_str

  #in_dir

  #date_start

  #date_end

  #item_no

  #out_suffix

  #OUTPUTS

  #

  #

  ##### Start script #####

  out_dir <- in_dir

  list_dates_produced <- unlist(mclapply(1:length(lf),

                                         FUN = extract_date,

                                         x = lf,

                                         item_no = item_no,

                                         mc.preschedule = FALSE,

                                         mc.cores = num_cores))

  list_dates_produced_date_val <- as.Date(strptime(list_dates_produced, "%Y%m%d"))

  month_str <- format(list_dates_produced_date_val, "%b") ## Month, char, abbreviated

  year_str <- format(list_dates_produced_date_val, "%Y") ## Year with century

  day_str <- as.numeric(format(list_dates_produced_date_val, "%d")) ## numeric month

  df_files <- data.frame(lf = basename(lf),

                          date = list_dates_produced_date_val,

                          month_str = month_str,

                          year = year_str,

                          day = day_str,

                          dir = dirname(lf))

  df_files_fname <- file.path(out_dir, paste0("df_files_", out_suffix, ".txt"))

  write.table(df_files,file = df_files_fname,sep = ",",row.names = F)

  #undebug(finding_missing_dates )

  missing_dates_obj <- finding_missing_dates (date_start,date_end,list_dates_produced_date_val)

  df_time_series <- missing_dates_obj$df_dates

  df_time_series$date <- as.character(df_time_series$date)  

  df_files$date <- as.character(df_files$date)

  df_time_series <- merge(df_time_series,df_files,by="date",all=T) #outer join to keep missing dates

  df_time_series$month_str <- format(as.Date(df_time_series$date), "%b") ## Month, char, abbreviated

  df_time_series$year_str <- format(as.Date(df_time_series$date), "%Y") ## Year with century

  df_time_series$day <- as.numeric(format(as.Date(df_time_series$date), "%d")) ## numeric month

  df_time_series_fname <- file.path(out_dir,paste0("df_time_series_",out_suffix,".txt")) #add the name of var later (tmax)

  write.table(df_time_series,file= df_time_series_fname,sep=",",row.names = F) 

  df_time_series_obj <- list(df_raster_fname,df_time_series_fname,df_time_series)

  names(df_time_series_obj) <- c("df_raster_fname","df_time_series_fname","df_time_series")

  ## report in text file missing by year and list of dates missing in separate textfile!!

  return(df_time_series_obj)

}