Add facilities to calculate decline curves

1 files changed, 48 insertions, 0 deletions

diff --git a/pkg/R/pfm_degradation.R b/pkg/R/pfm_degradation.R
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+# 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
+#' 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)
+}