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

#AUTHOR: Benoit Parmentier 

#CREATED ON: 03/23/2014  

#Version: 4

#PROJECT: Environmental Layers project  

#TO DO:

in_dir1 <- "/nobackupp6/aguzman4/climateLayers/out_15x45/"

#/nobackupp6/aguzman4/climateLayers/out_15x45/1982

#region_names <- c("reg1","reg2","reg3","reg4","reg5","reg6") #selected region names, #PARAM2

#region_namesb <- c("reg_1b","reg_1c","reg_2b","reg_3b","reg_6b") #selected region names, #PARAM2

y_var_name <- "dailyTmax" #PARAM3

interpolation_method <- c("gam_CAI") #PARAM4

#output_run10_1500x4500_global_analyses_pred_2003_04102015/

#day_to_mosaic <- c("20100101","20100901") #PARAM9

#day_to_mosaic <- c("20100829","20100830","20100831",

#                   "20100901","20100902","20100903")

#day_to_mosaic <- NULL #if day to mosaic is null then mosaic all dates?

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

#basename(in_dir_list)

                                               y=in_dir_list) 

#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_reg <- in_dir_list[grep("july_tiffs",basename(in_dir_reg),invert=TRUE)] #select directory with shapefiles...

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

                       FUN=function(i){paste(strsplit(l_shp[i],"_")[[1]][1:2],collapse="_")}))

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

list_shp_reg_files <- list_shp_world[matching_index]

tx<-strsplit(as.character(df_tile_processed$tile_coord),"_")

lat<- as.numeric(lapply(1:length(tx),function(i,x){x[[i]][1]},x=tx))

write.table(df_tile_processed,

            file=file.path(out_dir,paste("df_tile_processed_",out_prefix,".txt",sep="")),sep=",")

write.table(df_tiles_all,

            file=file.path(out_dir,paste("df_tiles_all_",out_prefix,".txt",sep="")),sep=",")

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

#output_atlas_dir <- "/data/project/layers/commons/NEX_data/output_run5_global_analyses_08252014/output20Deg"

output_atlas_dir <- file.path("/data/project/layers/commons/NEX_data/",out_dir)

#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)

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

#}  

#Copy summary textfiles back to atlas

Atlas_dir <- file.path("/data/project/layers/commons/NEX_data/",basename(out_dir))#,"output/subset/shapefiles")

cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,Atlas_dir,sep=":"), sep=" ")

system(cmd_str)

#system("scp -p ./*.txt parmentier@atlas.nceas.ucsb.edu:/data/project/layers/commons/NEX_data/output_run6_global_analyses_09162014")

#system("scp -p ./*.txt ./*.tif parmentier@atlas.nceas.ucsb.edu:/data/project/layers/commons/NEX_data/output_run2_global_analyses_05122014")

Atlas_dir <- file.path("/data/project/layers/commons/NEX_data/",basename(out_dir),"shapefiles")

Atlas_hostname <- "parmentier@atlas.nceas.ucsb.edu"

lf_cp_shp <- df_tile_processed$shp_files #get all the files...

lf_cp_shp_pattern <- gsub(".shp","*",basename(lf_cp_shp))

lf_cp_shp_pattern <- file.path(dirname(lf_cp_shp),lf_cp_shp_pattern)