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-rw-r--r--tests/testthat/runit.mkinerrmin.R62
-rw-r--r--tests/testthat/runit.mkinfit.R227
-rw-r--r--tests/testthat/test_FOCUS_D_UBA_expertise.R58
-rw-r--r--tests/testthat/test_FOCUS_chi2_error_level.R53
-rw-r--r--tests/testthat/test_parent_only.R210
-rw-r--r--tests/testthat/test_schaefer07_complex_case.R68
6 files changed, 363 insertions, 315 deletions
diff --git a/tests/testthat/runit.mkinerrmin.R b/tests/testthat/runit.mkinerrmin.R
deleted file mode 100644
index 56a33ff9..00000000
--- a/tests/testthat/runit.mkinerrmin.R
+++ /dev/null
@@ -1,62 +0,0 @@
-# Test SFO_SFO model with FOCUS_2006_D against Schaefer 2007 paper, tolerance = 1% # {{{
-# and check chi2 error values against values obtained with mkin 0.33
-test.FOCUS_2006_D_SFO_SFO <- function()
-{
- SFO_SFO.1 <- mkinmod(parent = list(type = "SFO", to = "m1"),
- m1 = list(type = "SFO"), use_of_ff = "min")
- SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"),
- m1 = list(type = "SFO"), use_of_ff = "max")
-
- fit.1.e <- mkinfit(SFO_SFO.1, FOCUS_2006_D)
- fit.1.d <- mkinfit(SFO_SFO.1, solution_type = "deSolve", FOCUS_2006_D)
- fit.2.e <- mkinfit(SFO_SFO.2, FOCUS_2006_D)
- fit.2.d <- mkinfit(SFO_SFO.2, solution_type = "deSolve", FOCUS_2006_D)
-
- FOCUS_2006_D_results_schaefer07_means <- c(
- parent_0 = 99.65, DT50_parent = 7.04, DT50_m1 = 131.34)
-
- r.1.e <- c(fit.1.e$bparms.optim[[1]], endpoints(fit.1.e)$distimes[[1]])
- r.1.d <- c(fit.1.d$bparms.optim[[1]], endpoints(fit.1.d)$distimes[[1]])
- r.2.e <- c(fit.2.e$bparms.optim[[1]], endpoints(fit.2.e)$distimes[[1]])
- r.2.d <- c(fit.2.d$bparms.optim[[1]], endpoints(fit.2.d)$distimes[[1]])
-
- dev.1.e <- 100 * (r.1.e - FOCUS_2006_D_results_schaefer07_means)/r.1.e
- checkIdentical(as.numeric(abs(dev.1.e)) < 1, rep(TRUE, 3))
- dev.1.d <- 100 * (r.1.d - FOCUS_2006_D_results_schaefer07_means)/r.1.d
- checkIdentical(as.numeric(abs(dev.1.d)) < 1, rep(TRUE, 3))
- dev.2.e <- 100 * (r.2.e - FOCUS_2006_D_results_schaefer07_means)/r.2.e
- checkIdentical(as.numeric(abs(dev.2.e)) < 1, rep(TRUE, 3))
- dev.2.d <- 100 * (r.2.d - FOCUS_2006_D_results_schaefer07_means)/r.2.d
- checkIdentical(as.numeric(abs(dev.2.d)) < 1, rep(TRUE, 3))
-
- round(mkinerrmin(fit.2.e), 4)
- round(mkinerrmin(fit.2.d), 4)
-
- errmin.FOCUS_2006_D_rounded = data.frame(
- err.min = c(0.0640, 0.0646, 0.0469),
- n.optim = c(4, 2, 2),
- df = c(15, 7, 8),
- row.names = c("All data", "parent", "m1"))
- checkEqualsNumeric(round(mkinerrmin(fit.2.e), 4),
- errmin.FOCUS_2006_D_rounded)
-} # }}}
-
-# Test SFO_SFO model with FOCUS_2006_E against values obtained with mkin 0.33 {{{
-test.FOCUS_2006_E_SFO_SFO <- function()
-{
- SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"),
- m1 = list(type = "SFO"), use_of_ff = "max")
-
- fit.2.e <- mkinfit(SFO_SFO.2, FOCUS_2006_E)
-
- round(mkinerrmin(fit.2.e), 4)
- errmin.FOCUS_2006_E_rounded = data.frame(
- err.min = c(0.1544, 0.1659, 0.1095),
- n.optim = c(4, 2, 2),
- df = c(13, 7, 6),
- row.names = c("All data", "parent", "m1"))
- checkEqualsNumeric(round(mkinerrmin(fit.2.e), 4),
- errmin.FOCUS_2006_E_rounded)
-} # }}}
-
-
diff --git a/tests/testthat/runit.mkinfit.R b/tests/testthat/runit.mkinfit.R
deleted file mode 100644
index 8eefb995..00000000
--- a/tests/testthat/runit.mkinfit.R
+++ /dev/null
@@ -1,227 +0,0 @@
-# Copyright (C) 2010-2014 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/>
-
-# Test SFO model to a relative tolerance of 1% # {{{
-test.FOCUS_2006_SFO <- function()
-{
- SFO.1 <- mkinmod(parent = list(type = "SFO"))
- SFO.2 <- mkinmod(parent = list(type = "SFO"), use_of_ff = "max")
-
- fit.A.SFO.1 <- mkinfit(SFO.1, FOCUS_2006_A, quiet=TRUE)
- fit.A.SFO.2 <- mkinfit(SFO.2, FOCUS_2006_A, quiet=TRUE)
-
- median.A.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F, dataset == "A",
- c(M0, k, DT50, DT90)), "median"))
-
- fit.A.SFO.1.r <- as.numeric(c(fit.A.SFO.1$bparms.optim, endpoints(fit.A.SFO.1)$distimes))
- dev.A.SFO.1 <- abs(round(100 * ((median.A.SFO - fit.A.SFO.1.r)/median.A.SFO), digits=1))
- checkIdentical(dev.A.SFO.1 < 1, rep(TRUE, length(dev.A.SFO.1)))
-
- fit.A.SFO.2.r <- as.numeric(c(fit.A.SFO.2$bparms.optim, endpoints(fit.A.SFO.2)$distimes))
- dev.A.SFO.2 <- abs(round(100 * ((median.A.SFO - fit.A.SFO.2.r)/median.A.SFO), digits=1))
- checkIdentical(dev.A.SFO.2 < 1, rep(TRUE, length(dev.A.SFO.2)))
-
- fit.C.SFO.1 <- mkinfit(SFO.1, FOCUS_2006_C, quiet=TRUE)
- fit.C.SFO.2 <- mkinfit(SFO.2, FOCUS_2006_C, quiet=TRUE)
-
- median.C.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F, dataset == "C",
- c(M0, k, DT50, DT90)), "median"))
-
- fit.C.SFO.1.r <- as.numeric(c(fit.C.SFO.1$bparms.optim, endpoints(fit.C.SFO.1)$distimes))
- dev.C.SFO.1 <- abs(round(100 * ((median.C.SFO - fit.C.SFO.1.r)/median.C.SFO), digits=1))
- checkIdentical(dev.C.SFO.1 < 1, rep(TRUE, length(dev.C.SFO.1)))
-
- fit.C.SFO.2.r <- as.numeric(c(fit.C.SFO.2$bparms.optim, endpoints(fit.C.SFO.2)$distimes))
- dev.C.SFO.2 <- abs(round(100 * ((median.C.SFO - fit.C.SFO.2.r)/median.C.SFO), digits=1))
- checkIdentical(dev.C.SFO.2 < 1, rep(TRUE, length(dev.C.SFO.2)))
-} # }}}
-
-# Test FOMC model to a relative tolerance of 1% {{{
-# See kinfit vignette for a discussion of FOMC fits to FOCUS_2006_A
-# In this case, only M0, DT50 and DT90 are checked
-test.FOCUS_2006_FOMC <- function()
-{
- FOMC <- mkinmod(parent = list(type = "FOMC"))
-
- # FOCUS_2006_A (compare kinfit vignette for discussion)
- fit.A.FOMC <- mkinfit(FOMC, FOCUS_2006_A, quiet=TRUE)
-
- median.A.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F, dataset == "A",
- c(M0, alpha, beta, DT50, DT90)), "median"))
-
- fit.A.FOMC.r <- as.numeric(c(fit.A.FOMC$bparms.optim, endpoints(fit.A.FOMC)$distimes[c("DT50", "DT90")]))
- dev.A.FOMC <- abs(round(100 * ((median.A.FOMC - fit.A.FOMC.r)/median.A.FOMC), digits=1))
- dev.A.FOMC <- dev.A.FOMC[c(1, 4, 5)]
- checkIdentical(dev.A.FOMC < 1, rep(TRUE, length(dev.A.FOMC)))
-
- # FOCUS_2006_B
- fit.B.FOMC <- mkinfit(FOMC, FOCUS_2006_B, quiet=TRUE)
-
- median.B.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F, dataset == "B",
- c(M0, alpha, beta, DT50, DT90)), "median"))
-
- fit.B.FOMC.r <- as.numeric(c(fit.B.FOMC$bparms.optim, endpoints(fit.B.FOMC)$distimes[c("DT50", "DT90")]))
- dev.B.FOMC <- abs(round(100 * ((median.B.FOMC - fit.B.FOMC.r)/median.B.FOMC), digits=1))
- dev.B.FOMC <- dev.B.FOMC[c(1, 4, 5)]
- checkIdentical(dev.B.FOMC < 1, rep(TRUE, length(dev.B.FOMC)))
-
- # FOCUS_2006_C
- fit.C.FOMC <- mkinfit(FOMC, FOCUS_2006_C, quiet=TRUE)
-
- median.C.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F, dataset == "C",
- c(M0, alpha, beta, DT50, DT90)), "median"))
-
- fit.C.FOMC.r <- as.numeric(c(fit.C.FOMC$bparms.optim, endpoints(fit.C.FOMC)$distimes[c("DT50", "DT90")]))
- dev.C.FOMC <- abs(round(100 * ((median.C.FOMC - fit.C.FOMC.r)/median.C.FOMC), digits=1))
- dev.C.FOMC <- dev.C.FOMC[c(1, 4, 5)]
- checkIdentical(dev.C.FOMC < 1, rep(TRUE, length(dev.C.FOMC)))
-} # }}}
-
-# Test DFOP model, tolerance of 1% with the exception of f parameter for A {{{
-test.FOCUS_2006_DFOP <- function()
-{
- DFOP <- mkinmod(parent = list(type = "DFOP"))
-
- # FOCUS_2006_A
- # Results were too much dependent on algorithm, as this dataset
- # is pretty much SFO. "Port" gave a lower deviance, but deviated from the
- # median of FOCUS_2006 solutions
-
- # FOCUS_2006_B
- fit.B.DFOP <- mkinfit(DFOP, FOCUS_2006_B, quiet=TRUE)
-
- median.B.DFOP <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B, dataset == "B",
- c(M0, k1, k2, f, DT50, DT90)), "median"))
-
- fit.B.DFOP.r <- as.numeric(c(fit.B.DFOP$bparms.optim, endpoints(fit.B.DFOP)$distimes[c("DT50", "DT90")]))
- dev.B.DFOP <- abs(round(100 * ((median.B.DFOP - fit.B.DFOP.r)/median.B.DFOP), digits=1))
- # about 0.6% deviation for parameter f, the others are <= 0.1%
- checkIdentical(dev.B.DFOP < 1, rep(TRUE, length(dev.B.DFOP)))
-} # }}}
-
-# Test HS model to a relative tolerance of 1% excluding Mathematica values {{{
-# as they are unreliable
-test.FOCUS_2006_HS <- function()
-{
- HS <- mkinmod(parent = list(type = "HS"))
-
- # FOCUS_2006_A
- fit.A.HS <- mkinfit(HS, FOCUS_2006_A, quiet=TRUE)
-
- median.A.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F, dataset == "A",
- c(M0, k1, k2, tb, DT50, DT90)), "median"))
-
- fit.A.HS.r <- as.numeric(c(fit.A.HS$bparms.optim, endpoints(fit.A.HS)$distimes[c("DT50", "DT90")]))
- dev.A.HS <- abs(round(100 * ((median.A.HS - fit.A.HS.r)/median.A.HS), digits=1))
- # about 6.7% deviation for parameter f, the others are < 0.1%
- checkIdentical(dev.A.HS < 1, rep(TRUE, length(dev.A.HS)))
-
- # FOCUS_2006_B
- fit.B.HS <- mkinfit(HS, FOCUS_2006_B, quiet=TRUE)
-
- median.B.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F, dataset == "B",
- c(M0, k1, k2, tb, DT50, DT90)), "median"))
-
- fit.B.HS.r <- as.numeric(c(fit.B.HS$bparms.optim, endpoints(fit.B.HS)$distimes[c("DT50", "DT90")]))
- dev.B.HS <- abs(round(100 * ((median.B.HS - fit.B.HS.r)/median.B.HS), digits=1))
- # < 10% deviation for M0, k1, DT50 and DT90, others are problematic
- dev.B.HS <- dev.B.HS[c(1, 2, 5, 6)]
- checkIdentical(dev.B.HS < 10, rep(TRUE, length(dev.B.HS)))
-
- # FOCUS_2006_C
- fit.C.HS <- mkinfit(HS, FOCUS_2006_C, quiet=TRUE)
-
- median.C.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F, dataset == "C",
- c(M0, k1, k2, tb, DT50, DT90)), "median"))
-
- fit.C.HS.r <- as.numeric(c(fit.C.HS$bparms.optim, endpoints(fit.C.HS)$distimes[c("DT50", "DT90")]))
- dev.C.HS <- abs(round(100 * ((median.C.HS - fit.C.HS.r)/median.C.HS), digits=1))
- # deviation <= 0.1%
- checkIdentical(dev.C.HS < 1, rep(TRUE, length(dev.C.HS)))
-} # }}}
-
-# Test SFORB model against DFOP solutions to a relative tolerance of 1% # {{{
-test.FOCUS_2006_SFORB <- function()
-{
- SFORB <- mkinmod(parent = list(type = "SFORB"))
-
- # FOCUS_2006_A
- # Again it does not make a lot of sense to use a SFO dataset for this
-
- # FOCUS_2006_B
- fit.B.SFORB.1 <- mkinfit(SFORB, FOCUS_2006_B, quiet=TRUE)
- fit.B.SFORB.2 <- mkinfit(SFORB, FOCUS_2006_B, solution_type = "deSolve", quiet=TRUE)
-
- median.B.SFORB <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B, dataset == "B",
- c(M0, k1, k2, DT50, DT90)), "median"))
-
- fit.B.SFORB.1.r <- as.numeric(c(
- parent_0 = fit.B.SFORB.1$bparms.optim[[1]],
- k1 = endpoints(fit.B.SFORB.1)$SFORB[[1]],
- k2 = endpoints(fit.B.SFORB.1)$SFORB[[2]],
- endpoints(fit.B.SFORB.1)$distimes[c("DT50", "DT90")]))
- dev.B.SFORB.1 <- abs(round(100 * ((median.B.SFORB - fit.B.SFORB.1.r)/median.B.SFORB), digits=1))
- checkIdentical(dev.B.SFORB.1 < 1, rep(TRUE, length(dev.B.SFORB.1)))
-
- fit.B.SFORB.2.r <- as.numeric(c(
- parent_0 = fit.B.SFORB.2$bparms.optim[[1]],
- k1 = endpoints(fit.B.SFORB.2)$SFORB[[1]],
- k2 = endpoints(fit.B.SFORB.2)$SFORB[[2]],
- endpoints(fit.B.SFORB.2)$distimes[c("DT50", "DT90")]))
- dev.B.SFORB.2 <- abs(round(100 * ((median.B.SFORB - fit.B.SFORB.2.r)/median.B.SFORB), digits=1))
- checkIdentical(dev.B.SFORB.2 < 1, rep(TRUE, length(dev.B.SFORB.2)))
-} # }}}
-
-# Test eigenvalue based fit to Schaefer 2007 data against solution from conference paper {{{
-test.mkinfit.schaefer07_complex_example <- function()
-{
- schaefer07_complex_model <- mkinmod(
- parent = list(type = "SFO", to = c("A1", "B1", "C1"), sink = FALSE),
- A1 = list(type = "SFO", to = "A2"),
- B1 = list(type = "SFO"),
- C1 = list(type = "SFO"),
- A2 = list(type = "SFO"), use_of_ff = "max")
-
- # If we use the default algorithm 'Marq' we need to give a good starting
- # estimate for k_A2 in order to find the solution published by Schaefer et al.
- fit <- mkinfit(schaefer07_complex_model, method.modFit = "Port",
- mkin_wide_to_long(schaefer07_complex_case, time = "time"))
- s <- summary(fit)
- r <- schaefer07_complex_results
- attach(as.list(fit$bparms.optim))
- r$mkin <- c(
- k_parent,
- s$distimes["parent", "DT50"],
- s$ff["parent_A1"],
- k_A1,
- s$distimes["A1", "DT50"],
- s$ff["parent_B1"],
- k_B1,
- s$distimes["B1", "DT50"],
- s$ff["parent_C1"],
- k_C1,
- s$distimes["C1", "DT50"],
- s$ff["A1_A2"],
- k_A2,
- s$distimes["A2", "DT50"])
- r$means <- (r$KinGUI + r$ModelMaker)/2
- r$mkin.deviation <- abs(round(100 * ((r$mkin - r$means)/r$means), digits=1))
- checkIdentical(r$mkin.deviation < 10, rep(TRUE, 14))
-} # }}}
-
-# vim: set foldmethod=marker ts=2 sw=2 expandtab:
diff --git a/tests/testthat/test_FOCUS_D_UBA_expertise.R b/tests/testthat/test_FOCUS_D_UBA_expertise.R
new file mode 100644
index 00000000..f9322714
--- /dev/null
+++ b/tests/testthat/test_FOCUS_D_UBA_expertise.R
@@ -0,0 +1,58 @@
+# Copyright (C) 2015 Johannes Ranke
+# Contact: jranke@uni-bremen.de
+
+# This file is part of the R package mkin
+
+# mkin is free software: you can redistribute it and/or modify it under the
+# terms of the GNU General Public License as published by the Free Software
+# Foundation, either version 3 of the License, or (at your option) any later
+# version.
+
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
+# details.
+
+# You should have received a copy of the GNU General Public License along with
+# this program. If not, see <http://www.gnu.org/licenses/>
+
+context("Results for FOCUS D established in expertise for UBA (Ranke 2014)")
+
+SFO_SFO <- mkinmod(parent = list(type = "SFO", to = "m1"),
+ m1 = list(type = "SFO"))
+SFO_SFO.ff <- mkinmod(parent = list(type = "SFO", to = "m1"),
+ m1 = list(type = "SFO"),
+ use_of_ff = "max")
+
+fit.default <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
+
+# Results are from p. 40
+
+test_that("Fitted parameters are correct for FOCUS D", {
+ expect_equivalent(round(fit.ff$bparms.optim, c(2, 4, 4, 4)),
+ c(99.60, 0.0987, 0.0053, 0.5145))
+})
+
+test_that("Fitted parameters are correct for FOCUS D", {
+ expect_equivalent(round(100 * mkinerrmin(fit.ff)$err.min, 2),
+ c(6.40, 6.46, 4.69))
+})
+
+test_that("DT50/90 are correct for FOCUS D when using formation fractions", {
+ expect_equal(round(as.numeric(endpoints(fit.ff)$distimes["parent", ]), 2),
+ c(7.02, 23.33))
+ expect_equal(round(as.numeric(endpoints(fit.ff)$distimes["m1", ]), 1),
+ c(131.8, 437.7))
+})
+
+test_that("DT50/90 are correct for FOCUS D when not using formation fractions", {
+ expect_equal(round(as.numeric(endpoints(fit.default)$distimes["parent", ]), 2),
+ c(7.02, 23.33))
+ expect_equal(round(as.numeric(endpoints(fit.default)$distimes["m1", ]), 1),
+ c(131.8, 437.7))
+})
+
+# References:
+# Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
+# zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452
diff --git a/tests/testthat/test_FOCUS_chi2_error_level.R b/tests/testthat/test_FOCUS_chi2_error_level.R
new file mode 100644
index 00000000..65e1ada7
--- /dev/null
+++ b/tests/testthat/test_FOCUS_chi2_error_level.R
@@ -0,0 +1,53 @@
+# Copyright (C) 2014-15 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/>
+
+# These tests were migrated from inst/unitTests/runit.mkinerrmin.R
+
+context("Calculation of FOCUS chi2 error levels")
+
+SFO_SFO.ff <- mkinmod(parent = list(type = "SFO", to = "m1"),
+ m1 = list(type = "SFO"),
+ use_of_ff = "max")
+
+test_that("Chi2 error levels for FOCUS D are as in mkin 0.9-33", {
+
+ fit <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
+
+ errmin.FOCUS_2006_D_rounded = data.frame(
+ err.min = c(0.0640, 0.0646, 0.0469),
+ n.optim = c(4, 2, 2),
+ df = c(15, 7, 8),
+ row.names = c("All data", "parent", "m1"))
+
+ expect_equal(round(mkinerrmin(fit), 4),
+ errmin.FOCUS_2006_D_rounded)
+})
+
+test_that("Chi2 error levels for FOCUS E are as in mkin 0.9-33", {
+
+ fit <- mkinfit(SFO_SFO.ff, FOCUS_2006_E, quiet = TRUE)
+
+ errmin.FOCUS_2006_E_rounded = data.frame(
+ err.min = c(0.1544, 0.1659, 0.1095),
+ n.optim = c(4, 2, 2),
+ df = c(13, 7, 6),
+ row.names = c("All data", "parent", "m1"))
+
+ expect_equal(round(mkinerrmin(fit), 4),
+ errmin.FOCUS_2006_E_rounded)
+})
diff --git a/tests/testthat/test_parent_only.R b/tests/testthat/test_parent_only.R
index 16fc5131..2ed38ffa 100644
--- a/tests/testthat/test_parent_only.R
+++ b/tests/testthat/test_parent_only.R
@@ -1,11 +1,35 @@
+# Copyright (C) 2015 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("Fitting of parent only models")
-calc_dev.percent <- function(fitlist, reference) {
+calc_dev.percent <- function(fitlist, reference, endpoints = TRUE, round_results = NULL) {
+ dev.percent <- list()
for (i in 1:length(fitlist)) {
fit <- fitlist[[i]]
- results <- c(fit$bparms.optim,
- endpoints(fit)$distimes$DT50,
- endpoints(fit)$distimes$DT90)
+ if (endpoints) {
+ results <- c(fit$bparms.optim,
+ endpoints(fit)$distimes$DT50,
+ endpoints(fit)$distimes$DT90)
+ } else {
+ results <- fit$bparms.optim
+ }
+ if (!missing(round_results)) results <- round(results, round_results)
dev.percent[[i]] <- abs(100 * ((reference - results)/reference))
}
return(dev.percent)
@@ -13,36 +37,170 @@ calc_dev.percent <- function(fitlist, reference) {
SFO <- mkinmod(parent = list(type = "SFO"))
FOMC <- mkinmod(parent = list(type = "FOMC"))
+DFOP <- mkinmod(parent = list(type = "DFOP"))
+HS <- mkinmod(parent = list(type = "HS"))
+SFORB <- mkinmod(parent = list(type = "SFORB"))
-test_that("SFO fit for FOCUS A deviates less than 0.1% from median of values from FOCUS report", {
- fits.A.SFO <- list()
- fits.A.SFO[[1]] <- mkinfit("SFO", FOCUS_2006_A, quiet=TRUE)
- fits.A.SFO[[2]] <- mkinfit(SFO, FOCUS_2006_A, quiet=TRUE)
- fits.A.SFO[[3]] <- mkinfit(SFO, FOCUS_2006_A, quiet=TRUE, solution_type = "eigen")
- fits.A.SFO[[4]] <- mkinfit(SFO, FOCUS_2006_A, quiet=TRUE, solution_type = "deSolve")
+test_that("Fits for FOCUS A deviate less than 0.1% from median of values from FOCUS report", {
+ fit.A.SFO <- list(mkinfit("SFO", FOCUS_2006_A, quiet = TRUE))
median.A.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F,
dataset == "A",
c(M0, k, DT50, DT90)), "median"))
- dev.percent <- calc_dev.percent(fits.A.SFO, median.A.SFO)
- expect_equivalent(dev.percent[[1]] < 0.1, rep(TRUE, 4))
- expect_equivalent(dev.percent[[2]] < 0.1, rep(TRUE, 4))
- expect_equivalent(dev.percent[[3]] < 0.1, rep(TRUE, 4))
- expect_equivalent(dev.percent[[4]] < 0.1, rep(TRUE, 4))
+ dev.percent.A.SFO <- calc_dev.percent(fit.A.SFO, median.A.SFO)
+ expect_equivalent(dev.percent.A.SFO[[1]] < 0.1, rep(TRUE, 4))
+
+ fit.A.FOMC <- list(mkinfit("FOMC", FOCUS_2006_A, quiet = TRUE))
+
+ median.A.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F,
+ dataset == "A",
+ c(M0, alpha, beta, DT50, DT90)), "median"))
+
+ dev.percent.A.FOMC <- calc_dev.percent(fit.A.FOMC, median.A.FOMC)
+ #expect_equivalent(dev.percent.A.FOMC[[1]] < 0.1, rep(TRUE, 5)) # alpha and beta ill-determined
+ expect_equivalent(dev.percent.A.FOMC[[1]][c(1, 4, 5)] < 0.1, rep(TRUE, 3))
+
+ fit.A.DFOP <- list(mkinfit("DFOP", FOCUS_2006_A, quiet = TRUE))
+
+ median.A.DFOP <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B,
+ dataset == "A",
+ c(M0, k1, k2, f, DT50, DT90)), "median"))
+
+ dev.percent.A.DFOP <- calc_dev.percent(fit.A.DFOP, median.A.DFOP)
+ #expect_equivalent(dev.percent.A.DFOP[[1]] < 0.1, rep(TRUE, 6)) # g/f is ill-determined
+ expect_equivalent(dev.percent.A.DFOP[[1]][c(1, 2, 3, 5, 6)] < 0.1, rep(TRUE, 5))
+
+ fit.A.HS <- list(mkinfit("HS", FOCUS_2006_A, quiet = TRUE))
+
+ median.A.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F,
+ dataset == "A",
+ c(M0, k1, k2, tb, DT50, DT90)), "median"))
+
+ dev.percent.A.HS <- calc_dev.percent(fit.A.HS, median.A.HS)
+ expect_equivalent(dev.percent.A.HS[[1]] < 0.1, rep(TRUE, 6))
})
-test_that("SFO fit for FOCUS C deviates less than 0.1% from median of values from FOCUS report", {
- fits.C.SFO <- list()
- fits.C.SFO[[1]] <- mkinfit("SFO", FOCUS_2006_C, quiet=TRUE)
- fits.C.SFO[[2]] <- mkinfit(SFO, FOCUS_2006_C, quiet=TRUE)
- fits.C.SFO[[3]] <- mkinfit(SFO, FOCUS_2006_C, quiet=TRUE, solution_type = "deSolve")
+test_that("Fits for FOCUS B deviate less than 0.1% from median of values from FOCUS report", {
+ fit.B.SFO <- list(mkinfit("SFO", FOCUS_2006_B, quiet = TRUE))
+
+ median.B.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F,
+ dataset == "B",
+ c(M0, k, DT50, DT90)), "median"))
+
+ dev.percent.B.SFO <- calc_dev.percent(fit.B.SFO, median.B.SFO)
+ expect_equivalent(dev.percent.B.SFO[[1]] < 0.1, rep(TRUE, 4))
+
+ fit.B.FOMC <- list(mkinfit("FOMC", FOCUS_2006_B, quiet = TRUE))
+
+ median.B.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F,
+ dataset == "B",
+ c(M0, alpha, beta, DT50, DT90)), "median"))
+
+ dev.percent.B.FOMC <- calc_dev.percent(fit.B.FOMC, median.B.FOMC)
+ expect_equivalent(dev.percent.B.FOMC[[1]] < 0.1, rep(TRUE, 5))
+
+ fit.B.DFOP <- list(mkinfit("DFOP", FOCUS_2006_B, quiet = TRUE))
+
+ median.B.DFOP <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B,
+ dataset == "B",
+ c(M0, k1, k2, f, DT50, DT90)), "median"))
+
+ dev.percent.B.DFOP <- calc_dev.percent(fit.B.DFOP, median.B.DFOP)
+ #expect_equivalent(dev.percent.B.DFOP[[1]] < 0.1, rep(TRUE, 6)) # g/f is ill-determined
+ expect_equivalent(dev.percent.B.DFOP[[1]][c(1, 2, 3, 5, 6)] < 0.1, rep(TRUE, 5))
+
+ fit.B.HS <- list(mkinfit("HS", FOCUS_2006_B, quiet = TRUE))
+
+ median.B.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F,
+ dataset == "B",
+ c(M0, k1, k2, tb, DT50, DT90)),
+ "median", na.rm = TRUE))
+
+ dev.percent.B.HS <- calc_dev.percent(fit.B.HS, median.B.HS)
+ expect_equivalent(dev.percent.B.HS[[1]] < 0.1, rep(TRUE, 6))
+
+ fit.B.SFORB <- list(mkinfit(SFORB, FOCUS_2006_B, quiet=TRUE))
+ dev.percent.B.SFORB <- calc_dev.percent(fit.B.SFORB, median.B.DFOP)
+ expect_equivalent(dev.percent.B.SFORB[[1]][c(1, 5, 6)] < 0.1, rep(TRUE, 3))
+})
+
+test_that("Fits for FOCUS C deviate less than 0.1% from median of values from FOCUS report", {
+ fit.C.SFO <- list(mkinfit("SFO", FOCUS_2006_C, quiet = TRUE))
median.C.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F,
- dataset == "C",
- c(M0, k, DT50, DT90)), "median"))
- dev.percent <- calc_dev.percent(fits.C.SFO, median.C.SFO)
- expect_equivalent(dev.percent[[1]] < 0.1, rep(TRUE, 4))
- expect_equivalent(dev.percent[[2]] < 0.1, rep(TRUE, 4))
- expect_equivalent(dev.percent[[3]] < 0.1, rep(TRUE, 4))
+ dataset == "C",
+ c(M0, k, DT50, DT90)), "median"))
+
+ dev.percent.C.SFO <- calc_dev.percent(fit.C.SFO, median.C.SFO)
+ expect_equivalent(dev.percent.C.SFO[[1]] < 0.1, rep(TRUE, 4))
+
+ fit.C.FOMC <- list(mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE))
+
+ median.C.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F,
+ dataset == "C",
+ c(M0, alpha, beta, DT50, DT90)), "median"))
+
+ dev.percent.C.FOMC <- calc_dev.percent(fit.C.FOMC, median.C.FOMC,
+ round_results = 2) # Not enough precision in FOCUS results
+ expect_equivalent(dev.percent.C.FOMC[[1]] < 0.1, rep(TRUE, 5))
+
+ fit.C.HS <- list(mkinfit("HS", FOCUS_2006_C, quiet = TRUE))
+
+ median.C.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F,
+ dataset == "C",
+ c(M0, k1, k2, tb, DT50, DT90)), "median"))
+
+ dev.percent.C.HS <- calc_dev.percent(fit.C.HS, median.C.HS, round_results = c(2, 4, 6, 2, 2))
+ # Not enouth precision in k2 available
+ expect_equivalent(dev.percent.C.HS[[1]] < c(0.1, 0.1, 0.3, 0.1, 0.1, 0.1), rep(TRUE, 6))
+})
+
+test_that("SFO fits give approximately (0.001%) equal results with different solution methods", {
+ fit.A.SFO.default <- mkinfit("SFO", FOCUS_2006_A, quiet = TRUE)$bparms.optim
+
+ fits.A.SFO <- list()
+ fits.A.SFO[[1]] <- mkinfit(SFO, FOCUS_2006_A, quiet = TRUE)
+ fits.A.SFO[[2]] <- mkinfit(SFO, FOCUS_2006_A, quiet = TRUE, solution_type = "eigen")
+ fits.A.SFO[[3]] <- mkinfit(SFO, FOCUS_2006_A, quiet = TRUE, solution_type = "deSolve")
+
+ dev.percent <- calc_dev.percent(fits.A.SFO, fit.A.SFO.default, endpoints = FALSE)
+ expect_equivalent(dev.percent[[1]] < 0.001, rep(TRUE, 2))
+ expect_equivalent(dev.percent[[2]] < 0.001, rep(TRUE, 2))
+ expect_equivalent(dev.percent[[3]] < 0.001, rep(TRUE, 2))
+})
+
+test_that("FOMC fits give approximately (0.001%) equal results with different solution methods", {
+ fit.C.FOMC.default <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)$bparms.optim
+
+ fits.C.FOMC <- list()
+ fits.C.FOMC[[1]] <- mkinfit(FOMC, FOCUS_2006_C, quiet = TRUE)
+ fits.C.FOMC[[2]] <- mkinfit(FOMC, FOCUS_2006_C, quiet = TRUE, solution_type = "deSolve")
+
+ dev.percent <- calc_dev.percent(fits.C.FOMC, fit.C.FOMC.default, endpoints = FALSE)
+ expect_equivalent(dev.percent[[1]] < 0.001, rep(TRUE, 3))
+ expect_equivalent(dev.percent[[2]] < 0.001, rep(TRUE, 3))
+})
+
+test_that("DFOP fits give approximately (0.001%) equal results with different solution methods", {
+ fit.C.DFOP.default <- mkinfit("DFOP", FOCUS_2006_C, quiet = TRUE)$bparms.optim
+
+ fits.C.DFOP <- list()
+ fits.C.DFOP[[1]] <- mkinfit(DFOP, FOCUS_2006_C, quiet = TRUE)
+ fits.C.DFOP[[2]] <- mkinfit(DFOP, FOCUS_2006_C, quiet = TRUE, solution_type = "deSolve")
+
+ dev.percent <- calc_dev.percent(fits.C.DFOP, fit.C.DFOP.default, endpoints = FALSE)
+ expect_equivalent(dev.percent[[1]] < 0.001, rep(TRUE, 4))
+ expect_equivalent(dev.percent[[2]] < 0.001, rep(TRUE, 4))
+})
+
+test_that("SFORB fits give approximately (0.001%) equal results with different solution methods", {
+ fit.B.SFORB.default <- mkinfit(SFORB, FOCUS_2006_B, quiet=TRUE)$bparms.optim
+
+ fits.B.SFORB <- list()
+ fits.B.SFORB[[1]] <- mkinfit(SFORB, FOCUS_2006_B, quiet=TRUE, solution_type = "eigen")
+ fits.B.SFORB[[2]] <- mkinfit(SFORB, FOCUS_2006_B, quiet=TRUE, solution_type = "deSolve")
+ dev.percent <- calc_dev.percent(fits.B.SFORB, fit.B.SFORB.default, endpoints = FALSE)
+ expect_equivalent(dev.percent[[1]] < 0.001, rep(TRUE, 4))
+ expect_equivalent(dev.percent[[2]] < 0.001, rep(TRUE, 4))
})
diff --git a/tests/testthat/test_schaefer07_complex_case.R b/tests/testthat/test_schaefer07_complex_case.R
new file mode 100644
index 00000000..1ef5106e
--- /dev/null
+++ b/tests/testthat/test_schaefer07_complex_case.R
@@ -0,0 +1,68 @@
+# Copyright (C) 2014-2015 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/>
+
+# This test was migrated from a RUnit test inst/unitTests/runit.mkinfit.R
+
+context("Complex test case from Schaefer et al. (2007) Piacenza paper")
+
+schaefer07_complex_model <- mkinmod(
+ parent = list(type = "SFO", to = c("A1", "B1", "C1"), sink = FALSE),
+ A1 = list(type = "SFO", to = "A2"),
+ B1 = list(type = "SFO"),
+ C1 = list(type = "SFO"),
+ A2 = list(type = "SFO"), use_of_ff = "max")
+
+schaefer07_long <- mkin_wide_to_long(schaefer07_complex_case, time = "time")
+
+fit.default <- mkinfit(schaefer07_complex_model, schaefer07_long, quiet = TRUE)
+
+test_that("Complex test case from Schaefer (2007) can be reproduced (10% tolerance)", {
+
+ s <- summary(fit.default)
+ r <- schaefer07_complex_results
+
+ with(as.list(fit.default$bparms.optim), {
+ r$mkin <<- c(
+ k_parent,
+ s$distimes["parent", "DT50"],
+ s$ff["parent_A1"],
+ k_A1,
+ s$distimes["A1", "DT50"],
+ s$ff["parent_B1"],
+ k_B1,
+ s$distimes["B1", "DT50"],
+ s$ff["parent_C1"],
+ k_C1,
+ s$distimes["C1", "DT50"],
+ s$ff["A1_A2"],
+ k_A2,
+ s$distimes["A2", "DT50"])
+ }
+ )
+ r$means <- (r$KinGUI + r$ModelMaker)/2
+ r$mkin.deviation <- abs(round(100 * ((r$mkin - r$means)/r$means), digits=1))
+ expect_equal(r$mkin.deviation < 10, rep(TRUE, 14))
+})
+
+test_that("We avoid the local minumum with default settings", {
+ # If we use optimisation algorithm 'Marq' we get a local minimum with a
+ # sum of squared residuals of 273.3707
+ # When using 'Marq', we need to give a good starting estimate e.g. for k_A2 in
+ # order to get the optimum with sum of squared residuals 240.5686
+ expect_equal(round(fit.default$ssr, 4), 240.5686)
+})

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