1 files changed, 0 insertions, 48 deletions
diff --git a/pkg/R/pfm_degradation.R b/pkg/R/pfm_degradation.R
deleted file mode 100644
index 6c8610e..0000000
--- a/pkg/R/pfm_degradation.R
+++ /dev/null
@@ -1,48 +0,0 @@
-# Copyright (C) 2015  Johannes Ranke
-# Contact: jranke@uni-bremen.de
-# This file is part of the R package pfm
-
-# This program is free software: you can redistribute it and/or modify it under
-# the terms of the GNU General Public License as published by the Free Software
-# Foundation, either version 3 of the License, or (at your option) any later
-# version.
-
-# This program is distributed in the hope that it will be useful, but WITHOUT
-# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
-# details.
-
-# You should have received a copy of the GNU General Public License along with
-# this program. If not, see <http://www.gnu.org/licenses/>
-
-#' 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
-#' @export
-#' @author Johannes Ranke
-#' @examples
-#' head(pfm_degradation("SFO", DT50 = 10))
-pfm_degradation <- function(model = "SFO", DT50 = 1000, parms = c(k_parent_sink = log(2)/DT50),
-                            years = 1, step_days = 1,
-                            times = seq(0, years * 365, by = step_days))
-{
-  if (model %in% c("SFO", "FOMC", "DFOP", "HS", "IORE")) {
-    model <- mkinmod(parent = list(type = model))
-  }
-  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)
-}