From 081b5f25cc4ef779175307d9ce20672e0573b7c9 Mon Sep 17 00:00:00 2001 From: jranke Date: Tue, 24 Apr 2012 17:33:56 +0000 Subject: - Added the reference fit data for FOCUS 2006 datasets from the kinfit package - Used these data in unit tests for parent only models - Fixed SFORB data and calculation of formation fractions along the way - Reintroduced the test for the Schaefer 2007 data - Got rid of the mkinmod unit tests - they are too hard to maintain and the mkinfit tests test the model definitions as well git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@32 edb9625f-4e0d-4859-8d74-9fd3b1da38cb --- inst/unitTests/runit.mkinfit.R | 257 +++++++++++++++++++++++++++++++++++++---- 1 file changed, 232 insertions(+), 25 deletions(-) (limited to 'inst/unitTests/runit.mkinfit.R') 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 +# 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: -- cgit v1.2.1