Finished migration from RUnit to testthat

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)

+})