Start of migration from RUnit to testthat

6 files changed, 427 insertions, 42 deletions

diff --git a/tests/doRUnit.R b/tests/doRUnit.R
deleted file mode 100644
index 9faee940..00000000
--- a/tests/doRUnit.R
+++ /dev/null
@@ -1,42 +0,0 @@
-# Adapted from a version around 2.9 of the rcdk package by Rajarshi Guha
-if(require("RUnit", quietly=TRUE)) {
- 
-  pkg <- "mkin"
-  path <- system.file(package=pkg, "unitTests")
-
-  cat("\nRunning unit tests\n")
-  print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
- 
-  library(package=pkg, character.only=TRUE)
- 
-  ## Define tests
-  testSuite <- defineTestSuite(name=paste(pkg, " Unit Tests"),
-                                          dirs=path)
-  ## Run
-  tests <- runTestSuite(testSuite)
- 
-  ## Default report name
-  pathReport <- file.path(path, "report")
- 
-  ## Report to stdout and text files
-  cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
-  printTextProtocol(tests, showDetails=FALSE)
-  printTextProtocol(tests, showDetails=FALSE,
-                    fileName=paste(pathReport, "Summary.txt", sep=""))
-  printTextProtocol(tests, showDetails=TRUE,
-                    fileName=paste(pathReport, ".txt", sep=""))
- 
-  ## Report to HTML file
-  printHTMLProtocol(tests, fileName=paste(pathReport, ".html", sep=""))
- 
-  ## Return stop() to cause R CMD check stop in case of
-  ##  - failures i.e. FALSE to unit tests or
-  ##  - errors i.e. R errors
-  tmp <- getErrors(tests)
-  if(tmp$nFail > 0 | tmp$nErr > 0) {
-    stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
-               ", #R errors: ",  tmp$nErr, ")\n\n", sep=""))
-  }
-} else {
-  warning("cannot run unit tests -- package RUnit is not available")
-}
diff --git a/tests/testthat.R b/tests/testthat.R
new file mode 100644
index 00000000..01c9b7cd
--- /dev/null
+++ b/tests/testthat.R
@@ -0,0 +1,4 @@
+library(testthat)
+library(mkin)
+
+test_check("mkin")
diff --git a/tests/testthat/runit.mkinerrmin.R b/tests/testthat/runit.mkinerrmin.R
new file mode 100644
index 00000000..56a33ff9
--- /dev/null
+++ b/tests/testthat/runit.mkinerrmin.R
@@ -0,0 +1,62 @@
+# 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
new file mode 100644
index 00000000..8eefb995
--- /dev/null
+++ b/tests/testthat/runit.mkinfit.R
@@ -0,0 +1,227 @@
+# 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/runit.mkinpredict.R b/tests/testthat/runit.mkinpredict.R
new file mode 100644
index 00000000..997857ce
--- /dev/null
+++ b/tests/testthat/runit.mkinpredict.R
@@ -0,0 +1,86 @@
+# $Id: jranke $

+

+# Copyright (C) 2012 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/>

+

+# Check solution types for SFO {{{

+test.SFO_solution_types <- function()

+{

+  ot = seq(0, 100, by = 1)

+  SFO <- mkinmod(parent = list(type = "SFO"))

+  SFO.analytical <- round(subset(mkinpredict(SFO, c(k_parent_sink = 0.1),

+        c(parent = 100), ot, solution_type = "analytical"), time == 100), digits=5)

+  SFO.deSolve <- round(subset(mkinpredict(SFO, c(k_parent_sink = 0.1),

+        c(parent = 100), ot, solution_type = "deSolve"), time == 100), digits=5)

+  SFO.eigen <- round(subset(mkinpredict(SFO, c(k_parent_sink = 0.1),

+        c(parent = 100), ot, solution_type = "eigen"), time == 100), digits=5)

+

+  checkEquals(SFO.analytical, SFO.deSolve)

+  checkEquals(SFO.analytical, SFO.eigen)

+} # }}}

+

+# Check model specification and solution types for SFO_SFO {{{

+# Relative Tolerance is 0.01%

+# Do not use time 0, as eigenvalue based solution does not give 0 at time 0 for metabolites

+# and relative tolerance is thus not met

+test.SFO_solution_types <- function()

+{

+  tol = 0.01

+  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")

+

+  ot = seq(0, 100, by = 1)

+  r.1.e <- subset(mkinpredict(SFO_SFO.1, 

+             c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1), 

+             c(parent = 100, m1 = 0), ot, solution_type = "eigen"), 

+                 time %in% c(1, 10, 50, 100))

+  r.1.d <- subset(mkinpredict(SFO_SFO.1, 

+             c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1), 

+             c(parent = 100, m1 = 0), ot, solution_type = "deSolve"), 

+                 time %in% c(1, 10, 50, 100))

+

+  r.2.e <- subset(mkinpredict(SFO_SFO.2, c(k_parent = 0.2, f_parent_to_m1 = 0.5, k_m1 = 0.1), 

+	    c(parent = 100, m1 = 0), ot, solution_type = "eigen"),

+                  time %in% c(1, 10, 50, 100))

+  r.2.d <- subset(mkinpredict(SFO_SFO.2, c(k_parent = 0.2, f_parent_to_m1 = 0.5, k_m1 = 0.1), 

+	    c(parent = 100, m1 = 0), ot, solution_type = "deSolve"),

+                  time %in% c(1, 10, 50, 100))

+

+  # Compare eigen and deSolve for minimum use of formation fractions

+  dev.1.e_d.percent = 100 * (r.1.e[-1] - r.1.d[-1])/r.1.e[-1]

+  dev.1.e_d.percent = as.numeric(unlist((dev.1.e_d.percent)))

+  dev.1.e_d.percent = ifelse(is.na(dev.1.e_d.percent), 0, dev.1.e_d.percent)

+  checkIdentical(dev.1.e_d.percent < tol, rep(TRUE, length(dev.1.e_d.percent)))

+

+  # Compare eigen and deSolve for maximum use of formation fractions

+  dev.2.e_d.percent = 100 * (r.1.e[-1] - r.1.d[-1])/r.1.e[-1]

+  dev.2.e_d.percent = as.numeric(unlist((dev.2.e_d.percent)))

+  dev.2.e_d.percent = ifelse(is.na(dev.2.e_d.percent), 0, dev.2.e_d.percent)

+  checkIdentical(dev.2.e_d.percent < tol, rep(TRUE, length(dev.2.e_d.percent)))

+

+  # Compare minimum and maximum use of formation fractions

+  dev.1_2.e.percent = 100 * (r.1.e[-1] - r.2.e[-1])/r.1.e[-1]

+  dev.1_2.e.percent = as.numeric(unlist((dev.1_2.e.percent)))

+  dev.1_2.e.percent = ifelse(is.na(dev.1_2.e.percent), 0, dev.1_2.e.percent)

+  checkIdentical(dev.1_2.e.percent < tol, rep(TRUE, length(dev.1_2.e.percent)))

+

+} # }}}

+

+# vim: set foldmethod=marker ts=2 sw=2 expandtab:

diff --git a/tests/testthat/test_parent_only.R b/tests/testthat/test_parent_only.R
new file mode 100644
index 00000000..16fc5131
--- /dev/null
+++ b/tests/testthat/test_parent_only.R
@@ -0,0 +1,48 @@
+context("Fitting of parent only models")
+
+calc_dev.percent <- function(fitlist, reference) {
+  for (i in 1:length(fitlist)) {
+    fit <- fitlist[[i]]
+    results <- c(fit$bparms.optim, 
+                 endpoints(fit)$distimes$DT50,
+                 endpoints(fit)$distimes$DT90)
+    dev.percent[[i]] <- abs(100 * ((reference - results)/reference))
+  }
+  return(dev.percent)
+}
+
+SFO <- mkinmod(parent = list(type = "SFO"))
+FOMC <- mkinmod(parent = list(type = "FOMC"))
+
+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")
+
+  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))
+})
+
+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")
+
+  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))
+})