#STAGE 5: Output analyses: assessment of results for specific dates... (tile based)

#STAGE 6: Assessement of predictions by tiles and region: summary tables and figures 

#STAGE 7: Mosaicing of predictions and accuracy layer productions

#AUTHOR: Benoit Parmentier                                                                        

#CREATED ON: 12/29/2015  

#PROJECT: NCEAS-IPLANT-NASA: Environment Layers                                                                           

#First source these files:

#CALLED FROM MASTER SCRIPT:

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

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_02072016.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

#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

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...

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

proj_str <- CRS_interp

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

list_param_run_assessment_combined_region_plotting_prediction <-list(  

    in_dir_list_filename,

    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,

names(list_param_run_assessment_combined_region_plotting_prediction) <- c(

    "in_dir_list_filename",

    "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",

i <- 1 #this select the first year of list_year_predicted

#Step 1: run figures production by region using table (part2 assessment script)

  #Step 1: run individual figure production if needed:

  if(run_figure_by_year==TRUE){

    #debug(run_assessment_plotting_prediction_fun)

    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)){