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author | Johannes Ranke <jranke@uni-bremen.de> | 2015-06-11 15:23:22 +0200 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2015-06-11 15:23:22 +0200 |
commit | 3aa5fb86772c28402047c7ebd07841061dbcdbba (patch) | |
tree | 524b67e02e6eee8584bf85211bc522e4918e8708 /pkg/R | |
parent | d3daa7b73fa5d0508ff51a843247d126c2a11691 (diff) |
Add facilities to calculate decline curves
Diffstat (limited to 'pkg/R')
-rw-r--r-- | pkg/R/SFO_actual_twa.R | 36 | ||||
-rw-r--r-- | pkg/R/pfm_degradation.R | 48 |
2 files changed, 84 insertions, 0 deletions
diff --git a/pkg/R/SFO_actual_twa.R b/pkg/R/SFO_actual_twa.R new file mode 100644 index 0000000..7facb6a --- /dev/null +++ b/pkg/R/SFO_actual_twa.R @@ -0,0 +1,36 @@ +# 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/> + +#' Actual and maximum moving window time average concentrations for SFO kinetics +#' +#' @param DT50 The half-life. +#' @param times The output times, and window sizes for time weighted average concentrations +#' @export +#' @author Johannes Ranke +#' @source FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation +#' Kinetics from Environmental Fate Studies on Pesticides in EU Registratin, Version 1.1, +#' 18 December 2014, p. 251 +#' @examples +#' SFO_actual_twa(10) +SFO_actual_twa <- function(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100)) +{ + k = log(2)/DT50 + result <- data.frame(actual = 1 * exp(-k * times), + twa = (1 - exp(-k * times))/(k * times), + row.names = times) + return(result) +} diff --git a/pkg/R/pfm_degradation.R b/pkg/R/pfm_degradation.R new file mode 100644 index 0000000..d1d2f9d --- /dev/null +++ b/pkg/R/pfm_degradation.R @@ -0,0 +1,48 @@ +# 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) +} |