R/helpers.R

In brain-r/brain: Neural Network

#' Reset
#'
#' Resets the brain, removing everything, including the architecture.
#'
#' @inheritParams architecture
#'
#' @export
clear <- function(brain){
  brain$brain$eval("net.clear()")
  return(brain)
}

#' Optimize
#'
#' Deativate self optimization of the network.
#'
#' @inheritParams architecture
#' @param opt Set to \code{FALSE} to deactivate self-optimization.
#'
#' @note Makes the learning slower but consumes less memory.
#'
#' @export
optimize_brain <- function(brain, opt = FALSE){
  brain$brain$eval(
    paste0("net.setOptimize(", tolower(opt), ")")
  )
  return(brain)
}

#' Balance
#'
#' Scale data (input and output) between 0 and 1.
#'
#' @param x A vector of class \code{numeric}
#'
#' @examples
#' x <- rnorm(20, 3, 7)
#'
#' range(x)
#'
#' (scaled <- balance(x))
#'
#' range(scaled)
#'
#' @export
balance <- function(x){

  if(!inherits(x, "numeric") & !inherits(x, "integer")){
    cat(
      crayon::yellow(cli::symbol$star), "x is not numeric, not scaling.\n"
    )
    return(x)
  } else {
    return((x - min(x)) / (max(x) - min(x)))
  }

}