#' Calculate a time course of relative concentrations based on an mkinmod model
#'
#' @import mkin
#' @param model The degradation model to be used. Either a parent only model like
#'   'SFO' or 'FOMC', or an mkinmod object
#' @param DT50 The half-life. This is only used when simple exponential decline
#'   is calculated (SFO model).
#' @param parms The parameters used for the degradation model
#' @param years For how many years should the degradation be predicted?
#' @param step_days What step size in days should the output have?
#' @param times The output times
#' @return A data frame containing the output times and the concentrations
#'   assuming initial concentrations of 1 for the parent and zero for
#'   metabolites, if any.
#' @export
#' @author Johannes Ranke
#' @examples
#' # Simple example of an SFO decline curve
#' sfo_out <- pfm_degradation("SFO", DT50 = 10)
#' head(sfo_out)
#'
#' # Fictive example with a metabolite where we first generate an SFO-SFO model
#' sfo_sfo <- mkinmod(
#'   parent = mkinsub("SFO", to = "metabolite"),
#'   metabolite = mkinsub("SFO"))
#'
#' sfo_sfo_out <- pfm_degradation(sfo_sfo,
#'   parms = c(k_parent = 0.1, f_parent_to_metabolite = 0.5, k_metabolite = 0.02))
#'
#' plot(
#'   sfo_sfo_out[, "time"],
#'   sfo_sfo_out[, "parent"], type = "l",
#'   xlab = "Time", ylab = "Relative concentration",
#'   xlim = c(0, 100))
#' lines(
#'   sfo_sfo_out[, "time"],
#'   sfo_sfo_out[, "metabolite"], lty = 2)
#'
pfm_degradation <- function(model = "SFO",
  DT50 = 1000, parms = c(k_parent = log(2)/DT50),
  years = 1, step_days = 1,
  times = seq(0, years * 365, by = step_days))
{
  if (!inherits(model, "mkinmod")) {
    if (model[1] %in% c("SFO", "FOMC", "DFOP", "HS", "IORE")) {
      model <- mkinmod(parent = list(type = model))
    } else {
      stop("Please specify the model with a suitable name or an mkinmod object")
    }
  }
  initial_state = c(1, rep(0, length(model$diffs) - 1))
  names(initial_state) <- names(model$diffs)
  time_course <- mkinpredict(model, odeparms = parms,
    odeini = initial_state,
    outtimes = times,
    solution_type = ifelse(length(model$spec) == 1, "analytical", "deSolve"))
  invisible(time_course)
}