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authorJohannes Ranke <jranke@uni-bremen.de>2016-12-21 10:35:16 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2016-12-21 10:35:16 +0100
commitb847fec686bc1db59079412eb18063d3514ecf75 (patch)
tree0ca2ed22905b022f9beb70ec989884718ca34385 /tests/testthat/test_twa.R
parentb07bdb3d8732a24a1fc9e8185cd6a2b21d7d0ca3 (diff)
TWA calculation for SFO, FOMC and DFOP (parent)
Diffstat (limited to 'tests/testthat/test_twa.R')
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diff --git a/tests/testthat/test_twa.R b/tests/testthat/test_twa.R
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+# Copyright (C) 2016 Johannes Ranke
+# Contact: jranke@uni-bremen.de
+
+# This file is part of the R package mkin
+
+# mkin 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/>
+
+context("Calculation of maximum time weighted average concentrations (TWAs)")
+
+twa_models <- c("SFO", "FOMC", "DFOP")
+fits <- mmkin(twa_models, list(FOCUS_D = FOCUS_2006_D),
+ quiet = TRUE)
+
+SFO_SFO <- mkinmod(parent = list(type = "SFO", to = "m1"),
+ m1 = list(type = "SFO"), quiet = TRUE)
+fit.m1 <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+
+test_that("Time weighted average concentrations are correct", {
+ outtimes_7 <- seq(0, 7, length.out = 10000)
+ for (model in twa_models) {
+ fit <- fits[[model, 1]]
+ bpar <- summary(fit)$bpar[, "Estimate"]
+ pred_7 <- mkinpredict(fit$mkinmod,
+ odeparms = bpar[2:length(bpar)],
+ odeini = c(parent = bpar[[1]]),
+ outtimes = outtimes_7)
+ twa_num <- mean(pred_7$parent)
+ names(twa_num) <- 7
+ twa_ana <- twa(fit, 7)
+
+ # Test for absolute difference (scale = 1)
+ expect_equal(twa_num, twa_ana, tolerance = 0.001, scale = 1)
+ }
+})

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