#STAGE 8: Comparison of predictions across regions and years with figures generation.

#AUTHOR: Benoit Parmentier                                                                        

#CREATED ON: 12/29/2015  

#PROJECT: NCEAS-IPLANT-NASA: Environment Layers                                                                           

#First source these files:

#CALLED FROM MASTER SCRIPT:

#script_path <- "/nobackupp8/bparmen1/env_layers_scripts" #path to script

function_assessment_part1_functions <- "global_run_scalingup_assessment_part1_functions_02112015.R" #PARAM12

function_assessment_part1a <-"global_run_scalingup_assessment_part1a_01042016.R"

function_assessment_part2 <- "global_run_scalingup_assessment_part2_02092016.R"

function_assessment_part2_functions <- "global_run_scalingup_assessment_part2_functions_01032016.R"

source(file.path(script_path,function_assessment_part1_functions)) #source all functions used in this script 

source(file.path(script_path,function_assessment_part1a)) #source all functions used in this script 

source(file.path(script_path,function_assessment_part2)) #source all functions used in this script 

#master directory containing the definition of tile size and tiles predicted

#in_dir1 <- "/nobackupp6/aguzman4/climateLayers/out/" #param 5, arg 2

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

#in_dir <- "" #PARAM 0

#y_var_name <- "dailyTmax" #PARAM1

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

#region_names <- c("reg23","reg4") #selected region names,

#run assessment by region, this is a unique region only 

region_name <- args[3] #param 6, arg 3

#out_prefix <- "run_global_analyses_pred_12282015" #param 7, arg 4

#out_dir <- "/nobackupp8/bparmen1/" #param 8, arg 5

#out_dir <-paste(out_dir,"_",out_prefix,sep="")

create_out_dir_param <- TRUE #param 9, arg 6

out_prefix <- args[4] #param 7, arg 4

out_dir <- args[5] #param 8, arg 5

#out_dir <-paste(out_dir,"_",out_prefix,sep="")

create_out_dir_param <- args[6] #param 9, arg 6

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

#run_figure_by_year <- TRUE # param 10, arg 7

file_format <- ".tif" #format for mosaiced files # param 11

NA_flag_val <- -9999  #No data value, # param 12

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

plotting_figures <- TRUE #running part2 of assessment to generate figures... # param 14

num_cores <- args[8] #number of cores used # param 13, arg 8

##Additional parameters used in part 2, some these may be removed as code is simplified

mosaic_plot <- FALSE #param 15

max_mem <- args[9] #param 21

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"

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

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

proj_str <- CRS_interp

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

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

      )

      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

  #function_assessment_part2 <- "global_run_scalingup_assessment_part2_01032016.R"

  #source(file.path(script_path,function_assessment_part2)) #source all functions used in this script

  df_assessment_combined_figures_files <-

  run_assessment_combined_region_plotting_prediction_fun(list_param_run_assessment_combined_region_plotting_prediction)

}