create_weights_fun <- function(i, list_param){

  #This function generates weights from a point location on a raster layer.

  #Note that the weights are normatlized on 0-1 scale using max and min values.

  #Inputs:

  #lf: list of raster files

  #df_points: 

  #Outputs:

  #

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

  lf <- list_param$lf

  df_centroids <- list_param$df_points

  out_dir_str <- list_param$out_dir_str

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

  r1 <- raster(lf[i]) #input image

  set1f <- function(x){rep(NA, x)}

  r_init <- init(r1, fun=set1f)

  cell_ID <- cellFromXY(r_init,xy=df_centroids[i,])

  r_init[cell_ID] <- df_centroids$ID[i]

  r_dist <- distance(r_init)

  min_val <- cellStats(r_dist,min) 

  max_val <- cellStats(r_dist,max)

  r_dist_normalized <- abs(r_dist - max_val)/ (max_val - min_val)

  extension_str <- extension(lf_mosaic_pred_1500x4500[i])

  raster_name_tmp <- gsub(extension_str,"",basename(lf_mosaic_pred_1500x4500[i]))

  raster_name <- file.path(out_dir_str,paste(raster_name_tmp,"_weights.tif",sep=""))

  writeRaster(r_dist_normalized, NAflag=NA_flag_val,filename=raster_name,overwrite=TRUE)  

  r_var_prod <- r1*r_dist_normalized

  raster_name_prod <- file.path(out_dir_str, paste(raster_name_tmp,"_prod_weights.tif"))

  writeRaster(r_var_prod, NAflag=NA_flag_val,filename=raster_name_prod,overwrite=TRUE)  

  weights_obj <- list(raster_name,raster_name_prod)

  names(weights_obj) <- c("r_weights","r_weights_prod")

  return(weights_obj)

}

list_param_create_weights <- list(lf_mosaic_pred_1500x4500,df_centroids,out_dir_str) 

names(list_param_create_weights) <- c("lf","df_points","out_dir_str") 

create_weights_fun

num_cores <- 6

#debug(create_weights_fun)

weights_obj <- create_weights_fun(1,list_param=list_param_create_weights)

weights_obj_list <- mclapply(1:length(lf_mosaic_pred_1500x4500),FUN=create_weights_fun,list_param=list_param_create_weights,mc.preschedule=FALSE,mc.cores = num_cores)                           

list_args_weights_prod <- lapply(1:length(weights_obj_list), FUN=function(x){raster(x[[i]]$r_weights_prod})}

list_args_weights_prod$fun <- "sum"

#"r_weights","r_weights_prod"

list_args_weights <- lapply(1:length(weights_obj_list), FUN=function(i,x){raster(x[[i]]$r_weights)},x=weights_obj_list)

list_args_weights_prod <- lapply(1:length(weights_obj_list), FUN=function(i,x){raster(x[[i]]$r_weights_prod)},x=weights_obj_list)

list_args_weights$fun <- "sum"

#list_args_weights$fun <- "mean"

list_args_weights$na.rm <- TRUE

list_args_weights$tolerance <- 1

list_args_weights_prod$fun <- "sum"

list_args_weights_prod$na.rm <- TRUE

list_args_weights_prod$na.rm <- TRUE

r_weights_sum <- do.call(mosaic,list_args_weights) #sum

r_prod_sum <- do.call(mosaic,list_args_weights_prod) #sum

r_weighted_mean <- r_weights_sum/r_prod_sum

#r_weights_sum <- do.call(overlay,list_args_weights) #sum

#r_weights_sum <- do.call(overlay,list_args_weights) #sum

#r_test_w <-do.call(overlay,list_args_w) #prod

##Quick function to generate test dataset

make_raster_from_lf <- function(i,list_lf,r_ref){

  vect_val <- list_lf[[i]]

  r <-  r_ref

  values(r) <-vect_val

  #writeRaster...

  return(r)

}

df_vect_w <-do.call(cbind,lf_vect_w)

df_vect_pred <-do.call(cbind,lf_vect_pred)

list_args_pred <- r_pred_l

list_args_pred$fun <- "sum"

r_pred <- stack(r_pred_l)

r_w <- stack(r_w_l)

list_args_pred <- r_pred_l

list_args_pred$fun <- mean

list_args_pred$na.rm <- TRUE

#r_sum_pred <-do.call(overlay,list_args_pred) #prod

#r_sum_pred <-do.call(mean,list_args_pred) #prod

r_sum_pred <-do.call(mosaic,list_args_pred) #prod

list_args_pred$na.rm <- FALSE

r_sum_pred <-do.call(overlay,list_args_pred) #prod

r_sum_pred <-do.call(overlay,list_args_w) #prod