#Part 1 create summary tables and inputs for figure in part 2 and part 3.

#AUTHOR: Benoit Parmentier 

#CREATED ON: 03/23/2014  

#Version: 3

#PROJECT: Environmental Layers project  

#TO DO:

#Additional libraries not used in workflow

library(pgirmess)                            # Krusall Wallis test with mulitple options, Kruskalmc {pgirmess}  

library(colorRamps)

#### FUNCTION USED IN SCRIPT

function_analyses_paper1 <-"contribution_of_covariates_paper_interpolation_functions_07182014.R" #first interp paper

function_analyses_paper2 <-"multi_timescales_paper_interpolation_functions_08132014.R"

load_obj <- function(f)

{

  env <- new.env()

  nm <- load(f, env)[1]

  env[[nm]]

}

create_dir_fun <- function(out_dir,out_suffix){

  if(!is.null(out_suffix)){

    out_name <- paste("output_",out_suffix,sep="")

#in_dir1 <- "/data/project/layers/commons/NEX_data/test_run1_03232014/output" #On Atlas

#in_dir1 <- "/nobackupp4/aguzman4/climateLayers/output20Deg2/"

#/nobackupp4/aguzman4/climateLayers/output10Deg/reg1/finished.txt

in_dir_list <- list.dirs(path=in_dir1,recursive=FALSE) #get the list regions processed for this run

#in_dir_list <- list.dirs(path=in_dir_reg,recursive=FALSE) #get the list of tiles/directories with outputs 

#in_dir_list <- in_dir_list[grep("bak",basename(basename(in_dir_list)),invert=TRUE)] #the first one is the in_dir1

in_dir_shp <- file.path(in_dir_subset,"shapefiles")

#select only directories used for predictions

in_dir_reg <- in_dir_list[grep(".*._.*.",basename(in_dir_list),invert=FALSE)] #select directory with shapefiles...

in_dir_list <- in_dir_reg

#Models used.

#list_models<-c("y_var ~ s(lat,lon,k=4) + s(elev_s,k=3) + s(LST,k=3)",

# the last directory contains shapefiles 

y_var_name <- "dailyTmax"

interpolation_method <- c("gam_CAI")

#out_dir<-"/data/project/layers/commons/NEX_data/" #On NCEAS Atlas

out_dir <- "/nobackup/bparmen1/" #on NEX

list_shp_world <- list.files(path=in_dir_shp,pattern=".*.shp",full.names=T)

l_shp <- unlist(lapply(1:length(list_shp_world),

                       FUN=function(i){paste(strsplit(list_shp_world[i],"_")[[1]][3:4],collapse="_")}))

matching_index <- match(basename(in_dir_list),l_shp)

list_shp_reg_files <- list_shp_world[matching_index]

df_tile_processed$shp_files <-list_shp_world[matching_index]

### This assumes the tree structure has been replicated on Atlas:

#for i in 1:length(df_tiled_processed$tile_coord)

#output_atlas_dir <- "/data/project/layers/commons/NEX_data/output_run3_global_analyses_06192014/output10Deg/reg1"

#Make directories on ATLAS

#for (i in 1:length(df_tile_processed$tile_coord)){

#  create_dir_fun(file.path(output_atlas_dir,as.character(df_tile_processed$tile_coord[i])),out_suffix=NULL)