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-rw-r--r--inst/unitTests/runit.mkinfit.R257
1 files changed, 232 insertions, 25 deletions
diff --git a/inst/unitTests/runit.mkinfit.R b/inst/unitTests/runit.mkinfit.R
index 2a026ce0..a06e4ff1 100644
--- a/inst/unitTests/runit.mkinfit.R
+++ b/inst/unitTests/runit.mkinfit.R
@@ -18,36 +18,243 @@
# 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$parms.all, fit.A.SFO.1$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$parms.all, fit.A.SFO.2$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$parms.all, fit.C.SFO.1$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$parms.all, fit.C.SFO.2$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$parms.all, fit.A.FOMC$distimes))
+ 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$parms.all, fit.B.FOMC$distimes))
+ 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$parms.all, fit.C.FOMC$distimes))
+ 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
+ fit.A.DFOP <- mkinfit(DFOP, FOCUS_2006_A, quiet=TRUE)
+ fit.A.DFOP <- mkinfit(DFOP, FOCUS_2006_A, quiet=TRUE, plot=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"))
+
+ fit.A.DFOP.r <- as.numeric(c(fit.A.DFOP$parms.all, fit.A.DFOP$distimes))
+ dev.A.DFOP <- abs(round(100 * ((median.A.DFOP - fit.A.DFOP.r)/median.A.DFOP), digits=1))
+ # about 6.7% deviation for parameter f, the others are < 0.1%
+ checkIdentical(dev.A.DFOP < c(1, 1, 1, 10, 1, 1), rep(TRUE, length(dev.A.DFOP)))
+
+ # 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$parms.all, fit.B.DFOP$distimes))
+ 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$parms.all, fit.A.HS$distimes))
+ 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$parms.all, fit.B.HS$distimes))
+ 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.A.HS.r <- as.numeric(c(fit.A.HS$parms.all, fit.A.HS$distimes))
+ dev.A.HS <- abs(round(100 * ((median.A.HS - fit.A.HS.r)/median.A.HS), digits=1))
+ # deviation <= 0.1%
+ checkIdentical(dev.A.HS < 1, rep(TRUE, length(dev.A.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
+ fit.A.SFORB.1 <- mkinfit(SFORB, FOCUS_2006_A, quiet=TRUE)
+ fit.A.SFORB.2 <- mkinfit(SFORB, FOCUS_2006_A, solution_type = "deSolve", quiet=TRUE)
+
+ median.A.SFORB <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B, dataset == "A",
+ c(M0, k1, k2, DT50, DT90)), "median"))
+
+ fit.A.SFORB.1.r <- as.numeric(c(
+ parent_0 = fit.A.SFORB.1$parms.all[[1]],
+ k1 = fit.A.SFORB.1$SFORB[[1]],
+ k2 = fit.A.SFORB.1$SFORB[[2]],
+ fit.A.SFORB.1$distimes))
+ dev.A.SFORB.1 <- abs(round(100 * ((median.A.SFORB - fit.A.SFORB.1.r)/median.A.SFORB), digits=1))
+ # The first Eigenvalue is a lot different from k1 in the DFOP fit
+ # The explanation is that the dataset is simply SFO
+ dev.A.SFORB.1 <- dev.A.SFORB.1[c(1, 3, 4, 5)]
+ checkIdentical(dev.A.SFORB.1 < 1, rep(TRUE, length(dev.A.SFORB.1)))
+
+ fit.A.SFORB.2.r <- as.numeric(c(
+ parent_0 = fit.A.SFORB.2$parms.all[[1]],
+ k1 = fit.A.SFORB.2$SFORB[[1]],
+ k2 = fit.A.SFORB.2$SFORB[[2]],
+ fit.A.SFORB.2$distimes))
+ dev.A.SFORB.2 <- abs(round(100 * ((median.A.SFORB - fit.A.SFORB.2.r)/median.A.SFORB), digits=1))
+ # The first Eigenvalue is a lot different from k1 in the DFOP fit
+ # The explanation is that the dataset is simply SFO
+ dev.A.SFORB.2 <- dev.A.SFORB.2[c(1, 3, 4, 5)]
+ checkIdentical(dev.A.SFORB.2 < 1, rep(TRUE, length(dev.A.SFORB.2)))
+
+ # 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$parms.all[[1]],
+ k1 = fit.B.SFORB.1$SFORB[[1]],
+ k2 = fit.B.SFORB.1$SFORB[[2]],
+ fit.B.SFORB.1$distimes))
+ 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$parms.all[[1]],
+ k1 = fit.B.SFORB.2$SFORB[[1]],
+ k2 = fit.B.SFORB.2$SFORB[[2]],
+ fit.B.SFORB.2$distimes))
+ 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")),
+ 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"))
-# Commented out because it takes too much time and is currently not used (see below)
-# fit <- mkinfit(schaefer07_complex_model,
-# mkin_wide_to_long(schaefer07_complex_case, time = "time"))
-# r <- schaefer07_complex_results
-# r$mkin <- c(
-# fit$parms.all["k_parent"],
-# fit$distimes["parent", "DT50"],
-# fit$parms.all["f_parent_to_A1"],
-# fit$parms.all["k_A1"],
-# fit$distimes["A1", "DT50"],
-# fit$parms.all["f_parent_to_B1"],
-# fit$parms.all["k_B1"],
-# fit$distimes["B1", "DT50"],
-# fit$parms.all["f_parent_to_C1"],
-# fit$parms.all["k_C1"],
-# fit$distimes["C1", "DT50"],
-# fit$parms.all["f_A1_to_A2"],
-# fit$parms.all["k_A2"],
-# fit$distimes["A2", "DT50"])
-# r$means <- (r$KinGUI + r$ModelMaker)/2
-# r$mkin.deviation <- abs(round(100 * ((r$mkin - r$means)/r$means), digits=1))
- # Commented out the check as mkin is fitting a different model
- #checkIdentical(r$mkin.deviation < 10, rep(TRUE, length(r$mkin.deviation)))
-}
+ fit <- mkinfit(schaefer07_complex_model,
+ mkin_wide_to_long(schaefer07_complex_case, time = "time"))
+ s <- summary(fit)
+ r <- schaefer07_complex_results
+ attach(as.list(fit$parms.all))
+ k_parent <- sum(k_parent_A1, k_parent_B1, k_parent_C1)
+ r$mkin <- c(
+ k_parent,
+ s$distimes["parent", "DT50"],
+ s$ff["parent_A1"],
+ sum(k_A1_sink, k_A1_A2),
+ s$distimes["A1", "DT50"],
+ s$ff["parent_B1"],
+ k_B1_sink,
+ s$distimes["B1", "DT50"],
+ s$ff["parent_C1"],
+ k_C1_sink,
+ s$distimes["C1", "DT50"],
+ s$ff["A1_A2"],
+ k_A2_sink,
+ 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$mkin.deviation < 10, rep(TRUE, length(r$mkin.deviation)))
+} # }}}
+# vim: set foldmethod=marker ts=2 sw=2 expandtab:

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