#MODIFIED ON: 12/11/2015            

# - generate delta and clim mosaic

# - Wrap in function to be able to extract information via a job?

# - Parallelize the region mosaics generation (by dates)?

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

region_names <- c("reg23","reg4") #selected region names, #PARAM2 

out_prefix<-"run10_1500x4500_global_analyses_pred_1992_12072015" #PARAM5

day_to_mosaic <- c("19920101","19920102","19920103,19920104,19920105")

######################################################

####### PART 2 CREATE MOSAIC OF PREDICTIONS PER DAY, Delta surfaces and clim ###

#if mosaicing_tiles==TRUE then do it?

#dates_l <- unique(robj1$tb_diagnostic_s$date) #list of dates to query tif

#create date!!!

if(is.null(day_to_mosaic)){

  #idx <- seq(as.Date('2010-01-01'), as.Date('2010-12-31'), 'day')

  #idx <- seq(as.Date('20100101'), as.Date('20101231'), 'day')

  #date_l <- strptime(idx[1], "%Y%m%d") # interpolation date being processed

  #dates_l <- format(idx, "%Y%m%d") # interpolation date being processed

  day_to_mosaic <- dates_predicted #should be 365 days...

  #l_dates <- day_to_mosaic

}

#else{

#  l_dates <- paste(day_to_mosaic,collapse=",")

#}

## make this a function? report on number of tiles used for mosaic...

#inputs: build a pattern to find files

#y_var_name <- "dailyTmax" #set up in parameters of this script

#interpolation_method <- c("gam_CAI") #set up in parameters of the script

name_method <- paste(interpolation_method,"_",y_var_name,"_",sep="")

##Use python code written by Alberto Guzman

#system("MODULEPATH=$MODULEPATH:/nex/modules/files")

#system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")

#module_path <- ""

module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/"

#/nobackupp6/aguzman4/climateLayers/sharedCode/mosaicUsingGdalMerge.py

l_dates <- paste(day_to_mosaic,collapse=",",sep=" ")

## use region 2 first

### FIRST mosaics by processing region

#make this a function later...with following param

#input:

#region_names

#in_dir1

##out_dir , not ehta out_dir moasic s can be created in rhe future function

#mod_str <- mod1

#For the time being use mean,median from python function by Alberto...

#Solved issue about calls from R

#First run 3 lines in the bash shell

#source /nobackupp6/aguzman4/climateLayers/sharedModules/etc/environ.sh 

#MODULEPATH=$MODULEPATH:/nex/modules/files

#module load pythonkits/gdal_1.10.0_python_2.7.3_nex

#recombine region first:

region_names_mosaic <- list(region_names)

names(region_names_mosaic) <- "reg5"

in_dir_mosaics <- lapply(region_names_mosaic,FUN=function(x){file.path(in_dir1,x)})

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

  #for(i in 1:length(region_names))

  in_dir_mosaics <- lapply(region_names_mosaic,FUN=function(x){file.path(in_dir1,x)})

  #in_dir_mosaics <- paste(region_names_mosaic,collapse=" ")

  #out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaicsMean"

  #Can be changed to have mosaics in different dir..

  out_dir_mosaics <- out_dir

  #prefix_str <- "reg4_1500x4500"

  #tile_size <- basename(dirname(in_dir[[i]]))

  tile_size <- basename(in_dir1)

  prefix_str <- paste(names(region_names_mosaic)[j],"_",tile_size,sep="")

  mod_str <- "mod1" #use mod2 which corresponds to model with LST and elev

  cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),

                 in_dir_mosaics,

                 out_dir_mosaics,

                 prefix_str,

                 "--mods", mod_str,

                 "--date", l_dates,sep=" ")

  system(cmd_str)

}

### SECOND mosaics globally from regional mosaics...

### Now find out how many files were predicted

# will be useful later on

# Transform this into a function that takes in a list of files!!! We can skip the region stage to reduce the number of files..

#sh /nobackupp6/aguzman4/climateLayers/sharedCode/shMergeFromFile.sh list_mosaics_20100901.txt world_mosaics_1000x3000_20100901.tif

in_dir_str <- in_dir_mosaics

region <- "reg5"  #can be the world...

for (i in 1:length(day_to_mosaic)){

  pattern_str <- paste("*.","predicted_mod1",".*.",day_to_mosaic[i],".*.tif",sep="")

  lf_day_to_mosaic <- lapply(1:length(unlist(in_dir_mosaics)),FUN=function(k){list.files(path=unlist(in_dir_mosaics)[k],pattern=pattern_str,full.names=T,recursive=T)}) 

  lf_day_to_mosaic <- unlist(lf_day_to_mosaic)

  #write.table(lf_day_to_mosaic,file=file.path(out_dir,paste("list_to_mosaics_",day_to_mosaic[i],".txt",sep="")))

  writeLines(lf_day_to_mosaic,con=file.path(out_dir,paste("list_to_mosaics_",day_to_mosaic[i],".txt",sep="")))

  in_file_to_mosaics <- file.path(out_dir,paste("list_to_mosaics_",day_to_mosaic[i],".txt",sep=""))        

  #in_dir_mosaics <- file.path(in_dir1,region_names[i])

  #out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaicsMean"

  #Can be changed to have mosaics in different dir..

  #out_dir_mosaics <- out_dir

  #prefix_str <- "reg4_1500x4500"

  #tile_size <- basename(dirname(in_dir[[i]]))

  tile_size <- basename(in_dir1)

  #prefix_str <- paste(region_names[i],"_",tile_size,sep="")

  mod_str <- "mod1" #use mod2 which corresponds to model with LST and elev

  out_mosaic_name <- paste(region,"_mosaics_",mod_str,"_",tile_size,"_",day_to_mosaic[i],"_",out_prefix,".tif",sep="")

  module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode" #this should be a parameter for the function...

  cmd_str <- paste("sh", file.path(module_path,"shMergeFromFile.sh"),

                 in_file_to_mosaics,

                 out_mosaic_name,

                 sep=" ")

  system(cmd_str)

}