R/draw_sc_linear.R

In nhppp: Simulating Nonhomogeneous Poisson Point Processes

#' Special case: Simulate from a non homogeneous Poisson Point Process (NHPPP) from
#'    (t_min, t_max) with linear intensity function (inversion method)
#'
#' @description  Sample NHPPP times from a linear intensity function
#' using the inversion method, optionally using an `rstream`
#' generator
#'
#' @param intercept (double) the intercept
#' @param slope (double) the slope
#' @param t_min (double) lower bound of the time interval
#' @param t_max (double) upper bound of the time interval
#' @param atmost1 boolean, draw at most 1 event time
#'
#' @return a vector of event times (t_); if no events realize,
#'         a vector of length 0
#' @export
#'
#' @examples
#' x <- draw_sc_linear(intercept = 0, slope = 0.2, t_min = 0, t_max = 10)
#'
draw_sc_linear <- function(intercept,
                           slope,
                           t_min,
                           t_max,
                           atmost1 = FALSE) {
  if ((slope <= 0 && intercept <= 0) || (intercept + slope * t_min < 0)) {
    return(c())
  }
  if (slope == 0) {
    return(ppp2(rate = intercept, t_min = t_min, t_max = t_max, atmost1 = atmost1))
  }
  if (slope < 0) {
    t_upper <- -intercept / slope
    t_max <- min(t_upper, t_max)
  }
  return(
    draw_cumulative_intensity_inversion(
      Lambda = function(t) Lambda_linear_form(t, intercept = intercept, slope = slope, t0 = t_min),
      Lambda_inv = function(z) Lambda_inv_linear_form(z, intercept = intercept, slope = slope, t0 = t_min),
      t_min = t_min,
      t_max = t_max,
      atmost1 = atmost1
    )
  )
}