#MODIFIED ON: 02/08/2016  

#in_dir <- args[2] # This is the output directory containing global predictions for multiple years e.g./nobackupp6/aguzman4/climateLayers/out/ param 5, arg 2

#list_year_predicted <- args[7] # enter a range, min and max year #arg 7

in_dir_list_filename <- args[10]

#in_dir_list_filename <- "/data/project/layers/commons/NEX_data/reg4_assessment/stage6_reg4_in_dir_list_02072016.txt"

run_figure_by_year <- args[11] # param 10, arg 7, if true will create figures for individual years...

#in_dir_list_filename <- "/data/project/layers/commons/NEX_data/reg4_assessment/stage6_reg4_in_dir_list_02072016.txt"

#in_dir_list_filename <- "/data/project/layers/commons/NEX_data/reg4_assessment/stage6_reg4_in_dir_list_02072016.txt"

#run_figure_by_year <- args[11] # param 10, arg 7, if true will create figures for individual years...

#run_figure_by_year <- TRUE # param 10, arg 7, if true will create figures for individual years...

#Rscript /nobackupp8/bparmen1/env_layers_scripts/master_script_stage_8_02072016.R TMAX /nobackupp6/aguzman4/climateLayers/out/ reg4 run_global_analyses_pred_12282015 /nobackupp8/bparmen1/ TRUE 2010 6 1e+07

#Rscript /nobackupp8/bparmen1/env_layers_scripts/master_script_stage_8_02072016.R TMAX /data/project/layers/commons/NEX_data/reg4_assessment reg4 global_analyses_overall_assessment_reg4_02072016 /data/project/layers/commons/NEX_data/reg4_assessment TRUE 2010,2013 6 1e+07 stage6_reg4_in_dir_list_02072016.txt TRUE

script_path <- "/home/parmentier/Data/IPLANT_project/env_layers_scripts"

function_assessment_part2 <- "global_run_scalingup_assessment_part2_02072016.R"

function_assessment_part3 <- "global_run_scalingup_assessment_part3_02082016.R"

source(file.path(script_path,function_assessment_part3)) #source all functions used in this script 

stages_to_run<-c(0,0,0,0,0,0,0,8) #this stage 2 to 5 currently stored in another file.

var<-"TMAX" # variable being interpolated #param 1, arg 1

in_dir <- args[2] #param 5, arg 2

in_dir <- "/data/project/layers/commons/NEX_data/reg4_assessment"

#in_dir <- "" #PARAM 0

#y_var_name <- "dailyTmax" #PARAM1

#interpolation_method <- c("gam_CAI") #PARAM2

region_name <- c("reg4") #param 6, arg 3

out_suffix <- args[4] #param 7, arg 4s

out_suffix <- "global_analyses_overall_assessment_reg4_02072016"

out_dir <- "/data/project/layers/commons/NEX_data/reg4_assessment"

create_out_dir_param <- TRUE #param 9, arg 

list_year_predicted <- args[7] # param 10, arg 7, min and max year

#run_figure_by_year <- TRUE # param 10, arg 7

list_year_predicted <- "2010,2013"

num_cores <-6 #number of cores used # param 13, arg 8

#countries_shp <- "/nobackupp8/bparmen1/NEX_data/countries.shp" #param 18

countries_shp <-"/data/project/layers/commons/NEX_data/countries.shp" #Atlas

max_mem <- 1e+07

#in_dir_list_filename <- args[10] #param 22

in_dir_list_filename <- "/data/project/layers/commons/NEX_data/reg4_assessment/stage6_reg4_in_dir_list_02072016.txt"

#in_dir_list_filename <- "/data/project/layers/commons/NEX_data/reg4_assessment/stage6_reg4_in_dir_list_02072016.txt"

run_figure_by_year <- args[11] # param 10, arg 7, if true will create figures for individual years...

run_figure_by_year <- TRUE # param 10, arg 7, if true will create figures for individual years...

#### Prepare parameters for the production of figures...

proj_str <- CRS_interp

list_in_dir <- as.list(read.table(in_dir_list_filename,stringsAsFactors=F)[,1])

    region_name, df_assessment_files_name, threshold_missing_day,list_year_predicted)

    l_list_param_run_assessment_part2_plotting <- vector("list",length=length(list_in_dir))

    list_df_assessment_files <- lapply(list_in_dir,FUN=function(x,y){list.files(path=file.path(y,x),pattern="df_assessment_files_.*.txt",full.names=T)},y=in_dir)

    for(j in 1:length(list_in_dir)){

      df_assessment_files_name <- list_df_assessment_files[[j]]

      df_assessment <- read.table(df_assessment_files_name,stringsAsFactors=F,sep=",")

      year_tmp <- unique(df_assessment$year)

      reg_tmp <- unique(df_assessment$reg)

      in_dir_tmp <- file.path(in_dir,list_in_dir[[j]])

      out_suffix_tmp <- paste("s8_",year_tmp,"_",out_suffix,sep="")

      create_out_dir_param_tmp <- FALSE

      out_dir_tmp <- in_dir_tmp #write output in the existing dir from NEX

      list_param_run_assessment_part2_plotting <-list(  

             in_dir_tmp,y_var_name, interpolation_method, out_suffix_tmp,

             out_dir_tmp, create_out_dir_param_tmp, mosaic_plot, proj_str, file_format, NA_flag_val,

             multiple_region, countries_shp, plot_region, num_cores,

            region_name, df_assessment_files_name, threshold_missing_day,year_tmp

      )

      names(list_param_run_assessment_part2_plotting) <- c(

            "in_dir","y_var_name","interpolation_method","out_suffix",

            "out_dir","create_out_dir_param","mosaic_plot","proj_str","file_format","NA_flag_val",

            "multiple_region","countries_shp","plot_region","num_cores",

            "region_name","df_assessment_files_name","threshold_missing_day","year_predicted"

      )

      #undebug(run_assessment_plotting_prediction_fun)

      df_assessment_figures_files <-

      run_assessment_plotting_prediction_fun(list_param_run_assessment_part2_plotting)

      l_list_param_run_assessment_part2_plotting[[j]] <- list_param_run_assessment_part2_plotting

      list_df_assessment_files[[j]] <- df_assessment_figures_files

    }

  debug(run_assessment_combined_region_plotting_prediction_fun)