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

#diagnostics_obj_gam_fitting_dailyTmax7__08062014.RData

lf_diagnostic_obj <- lapply(in_dir_list,FUN=function(x){list.files(path=x,pattern="diagnostics_.*.RData",full.names=T)})

lf_diagnostic_obj <- lf_diagnostic_obj[grep("lk_min",lf_diagnostic_obj,invert=T)] #remove object that have lk_min...

####### process gam fitting diagnostic info

#/nobackupp4/aguzman4/climateLayers/output20Deg/reg5/20.0_30.0//diagnostics_obj_gam_fitting_TMax_9_mod2_08062014.RData

#lf_diagnostic_obj <- lapply(in_dir_list,FUN=function(x){list.files(path=x,pattern="diagnostics_.*.RData",full.names=T)})

#lf_diagnostic_obj <- lapply(in_dir_list,FUN=function(x){list.files(path=x,pattern="diagnostics_obj_gam_fitting_TMax_*_mod*_08062014.RData",full.names=T)})

lf_diagnostic_obj <- lapply(in_dir_list,FUN=function(x){list.files(path=x,pattern="diagnostics_obj_gam_fitting_TMax_.*._mod.*._08062014.RData",full.names=T)})

#lf_diagnostic_obj <- lf_diagnostic_obj[grep("lk_min",lf_diagnostic_obj,invert=T)] #remove object that have lk_min...

names(lf_diagnostic_obj) <- list_names_tile_id

lf_diagnostic_obj_tmp <- remove_from_list_fun(lf_diagnostic_obj)$list

#df_tile_processed$tb_diag <- remove_from_list_fun(tb_diagnostic_v_list)$valid

gam_diagnostic_tb_list <- vector("list",length=length(lf_diagnostic_obj_tmp))

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

  l_diagnostic_obj_tmp <- lf_diagnostic_obj_tmp[[i]]

  tile_id_name <-  names(lf_diagnostic_obj_tmp)[i]

  #l_diagnostic_obj_tmp <- l_diagnostic_obj_tmp[grep("lk_min",l_diagnostic_obj_tmp,invert=T)] #remove object that have lk_min...

  l_diagnostic_obj_tmp_list <- lapply(l_diagnostic_obj_tmp,FUN=function(x){try(x<-load_obj(x));try(x[["df_diagnostics"]])})#,mc.preschedule=FALSE,mc.cores = 6)                            

  gam_diagnostic_tb <- do.call(rbind.fill,l_diagnostic_obj_tmp_list)#create a df for NA tiles with all accuracy metrics

  gam_diagnostic_tb$tile_id <- tile_id_name

  gam_diagnostic_tb_list[[i]] <- gam_diagnostic_tb    

}

gam_diagnostic_df <- do.call(rbind.fill,gam_diagnostic_tb_list) #create a df for NA tiles with all accuracy metrics

write.table(gam_diagnostic_df,

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