# S-290 PingPong Ball
#
# The following R program was designed for use in cold calling in a
# class room environment that tries to balance true randomness with
# the desire to spread questions out.
#
# The software was written by Benjamin Mako Hill <mako@atdot.cc> and
# is released into the public domain.

# replace this line with a list of the names from which we want to sample
member.names <- c("Alonso", "Alejandro", "Andres", "Becky",
                  "Deborah", "Lauren", "Mako", "Nikhit", "North",
                  "Steve")

# set the default weight: after being selected the likelihood of the
# selected value being chosen will be reduced to 1 over this value
pp.weight <- 2

# create a variable which we'll use to keep track of who has been selected
reset.weights <- function () {
  w <- rep(1, length(member.names))
  names(w) <- member.names
  assign("w", w, envir=.GlobalEnv)
}

# only run this if you want to create new we
if (!exists("w")) reset.weights()

get.ping.pong.ball <- function () {
  # create the "jar" according to the weights
  weighted.names <- c(sapply(member.names,
                             function (x) {rep(x, w[x])}), recursive=TRUE)
  # select something out of it
  selected <- sample(weighted.names, 1)

  # adjust the weights for the next run based on what was selected
  w[!names(w) == selected] <- w[!names(w) == selected] * pp.weight

  # if we can reduce the weights by a lowest common denom, do it
  if (all((w %% pp.weight) == 0)) w <- w / pp.weight

  # save the variable in the global namespace so we can return to it next time
  assign("w", w, envir=.GlobalEnv)

  # clean up the output and return the value
  names(selected) <- NULL
  return(selected)
}

# run this function to get a person selected
get.ping.pong.ball()

# run the following function to reset the weights
reset.weights()