R/time_bp_to_index.R

In pastclim: Manipulate Time Series of Climate Reconstructions

#' Find the closest index to a given time in years BP
#'
#' Internal function
#'
#' @param time_bp vector of times BP
#' @param time_steps time steps for which reconstructions are available
#' @returns the indeces for the relevant time steps
#' @keywords internal

time_bp_to_index <- function(time_bp, time_steps) {
  # give warning if some dates are too extreme
  time_steps_ordered <- sort(time_steps)
  # if you have only one time step within your database you cannot calculate the
  # range between min and max time steps the following if statement was added
  # because otherwise you would get NAs
  if (length(time_steps_ordered) != 1) {
    # calculate the range between the min and the max time steps this allow to
    # check if the dates within your data frame are within a sensible range of
    # the database's time steps
    # nolint start (the brackets are too many)
    range_minmax <- c(
      head(time_steps_ordered, n = 1)[1] -
        (abs(head(time_steps_ordered, n = 2)[1] -
          head(time_steps_ordered, n = 2)[2]) / 2),
      tail(time_steps_ordered, n = 1)[1] +
        (abs(tail(time_steps_ordered, n = 2)[1] -
          tail(time_steps_ordered, n = 2)[2]) / 2)
    )
    # nolint end
    if (any(time_bp < range_minmax[1]) || any(time_bp > range_minmax[2])) {
      warning(
        "Some dates are out of the range of the available time series.\n",
        "They will be assigned to the most extreme time point available, ",
        "but this\n",
        "might not make sense. The potentially problematic dates are:\n",
        time_bp[
          which((time_bp < range_minmax[1]) | (time_bp > range_minmax[2]))
        ]
      )
    }
  }
  # get indeces
  time_indeces <-
    sapply(time_bp, function(a, b) {
      which.min(abs(a - b))
    }, time_steps)
  return(time_indeces)
}