#

#AUTHOR: Benoit Parmentier 

#CREATED ON: 10/31/2016  

#Version: 1

#PROJECT: Environmental Layers project     

#COMMENTS: removing unused functions and clean up for part0 global prodduct assessment part0 

  ##### Sum missing tiles in the stack and generate number of predictions by pixels

  ## This stores files in the temp dir

  r_data_sum <- stackApply(r_tiles_s, 1:nlayers(r_tiles_s), fun = sum,filename=raster_name_data_sum,overwrite=TRUE)

  ### then substract missing tiles...

  year_predicted <- list_param$year_predicted #selected year #PARAM 23

  data_type <- list_param$data_type #PARAM 24

  scaling <- list_param$scaling #PARAM 25

  ########################## START SCRIPT #########################################

  #http://stackoverflow.com/questions/26220913/replace-na-with-na

  #Use dfr[dfr=="<NA>"]=NA where dfr is your dataframe.

  names(df_lf_tiles_time_series) <- unlist(basename(in_dir_reg))

  write.table(df_lf_tiles_time_series,file=filename_df_lf_tiles)

  ###Now combined missing in one table?

  df_missing$reg <- region_name

  df_missing$date <- day_to_mosaic

  write.table(df_missing,file=filename_df_missing)

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

           col_name = "overlap",

           date_val=df_missing$date[1],

           out_dir = out_dir,

            mc.preschedule=FALSE,

           mc.cores = num_cores)

  #plot(spdf_tiles_test,add=T,border="green",usePolypath = FALSE) #added usePolypath following error on brige and NEX

  ### Make a list of file

  out_dir_str <- out_dir

  filename_list_predicted <- file.path(out_dir_str,paste("list_to_mosaics_",out_suffix_str_tmp,".txt",sep=""))

  #out_mosaic_name_weights_m <- r_weights_sum_raster_name <- file.path(out_dir,paste("r_weights_sum_m_",mosaic_method,"_weighted_mean_",out_suffix,".tif",sep=""))

  #out_mosaic_name_prod_weights_m <- r_weights_sum_raster_name <- file.path(out_dir,paste("r_prod_weights_sum_m_",mosaic_method,"_weighted_mean_",out_suffix,".tif",sep=""))

  rast_ref_name <- infile_mask

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

  r_overlap <- raster(r_overlap_raster_name)

  r_mask <- raster(infile_mask)

  r_overlap_m <- mask(r_overlap,

                  mask=r_mask,

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

  #### Step 3: combine overlap information and number of predictions by day

  ##Now loop through every day if missing then generate are raster showing map of number of prediction

  #r_tiles_stack <- stack(list_tiles_predicted_masked)

  #names(r_tiles_stack) <- basename(in_dir_reg) #this does not work, X. is added to the name, use list instead

  #r_tiles_s <- r_tiles_stack

  names_tiles <- basename(in_dir_reg)

  list_param_generate_raster_number_pred <- list(list_tiles_predicted_masked,df_missing_tiles_day,r_overlap_m,

                                                 num_cores,region_name,data_type,scaling,python_bin,

                                                 plotting_figures,

    obj_number_pix_predictions <- NULL

  }

  #Delete temporary files : Fix this part later...

  #rasterOptions(), find where tmp dir are stored

  #rasterOptions(tempdir=out_dir)

  if(tmp_files==F){ #if false...delete all files with "_tmp"

    ##now delete temporary files...

    file.remove(lf_tmp)

  }

                                            "tb_freq_overlap","png_maximum_overlap","obj_number_pix_predictions")

  return(predictions_tiles_missing_obj)

}