R/distance_reduction.R

In lwawrowski/combat: Artificial intelligence engine for simple combat game

#' Distance reduction value
#'
#' Calculate distance reduction value due to range and accuracy of the unit and distance from the target.
#'
#' @param range_min minimum range of the unit
#' @param range_max maximum range of the unit
#' @param accuracy accuracy of the unit
#' @param distance distance between unit and target
#' @return distance reduction value from [0;1] interval
#' @importFrom assertthat assert_that
#' @importFrom assertthat is.number
#' @importFrom assertthat noNA
#' @export
#' @examples
#' distance_reduction(range_min = 1, range_max = 5, accuracy = 6, distance = 4)

distance_reduction <- function(range_min, range_max, accuracy, distance){

  assert_that(is.number(range_min))
  assert_that(is.number(range_max))
  assert_that(is.number(accuracy))
  assert_that(is.number(distance))

  assert_that(range_min %in% 1:10, msg = "Range must be a number from 1 to 10.")
  assert_that(range_max %in% 1:10, msg = "Range must be a number from 1 to 10.")
  assert_that(range_max > range_min, msg = "Maximum range must be greater than minimum range")
  assert_that(accuracy %in% 1:10, msg = "Accuracy must be a number from 1 to 10.")
  assert_that(distance %in% 1:max(dist_matrix), msg = paste0("Distance must be a number from 1 to ", max(dist_matrix)))

  assert_that(noNA(range_min))
  assert_that(noNA(range_max))
  assert_that(noNA(accuracy))
  assert_that(noNA(distance))

  a <- c(range_min,1)
  b <- c(range_max,accuracy/10)

  betas <- linear_model(a, b)

  y <- betas[2]*distance+betas[1]

  return(y)
}