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authorjranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>2013-02-18 22:11:49 +0000
committerjranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>2013-02-18 22:11:49 +0000
commitfa10b85d6bb964742d2c5a3e3f633a5238c43d56 (patch)
tree7497bddd9937aee3989db75cae5bbdff3fae9146 /inst/unitTests
parent67860242fc619624421a8fd96ba9e385456a9c2d (diff)
- Completion of the multicompartment part of the mkin examples vignette
- Fix to chi2 error level calculation by correctly returning backtransformed parameters as bparms.optim and bparms.fixed - Adaptations of unit tests, summary and plot functions git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@67 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
Diffstat (limited to 'inst/unitTests')
-rw-r--r--inst/unitTests/runit.mkinfit.R44
1 files changed, 22 insertions, 22 deletions
diff --git a/inst/unitTests/runit.mkinfit.R b/inst/unitTests/runit.mkinfit.R
index 26007e7..784054b 100644
--- a/inst/unitTests/runit.mkinfit.R
+++ b/inst/unitTests/runit.mkinfit.R
@@ -30,11 +30,11 @@ test.FOCUS_2006_SFO <- function()
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$parms.all, endpoints(fit.A.SFO.1)$distimes))
+ 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$parms.all, endpoints(fit.A.SFO.2)$distimes))
+ 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)))
@@ -44,11 +44,11 @@ test.FOCUS_2006_SFO <- function()
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$parms.all, endpoints(fit.C.SFO.1)$distimes))
+ 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$parms.all, endpoints(fit.C.SFO.2)$distimes))
+ 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)))
} # }}}
@@ -66,7 +66,7 @@ test.FOCUS_2006_FOMC <- function()
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$parms.all, endpoints(fit.A.FOMC)$distimes))
+ fit.A.FOMC.r <- as.numeric(c(fit.A.FOMC$bparms.optim, endpoints(fit.A.FOMC)$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)))
@@ -77,7 +77,7 @@ test.FOCUS_2006_FOMC <- function()
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$parms.all, endpoints(fit.B.FOMC)$distimes))
+ fit.B.FOMC.r <- as.numeric(c(fit.B.FOMC$bparms.optim, endpoints(fit.B.FOMC)$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)))
@@ -88,7 +88,7 @@ test.FOCUS_2006_FOMC <- function()
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$parms.all, endpoints(fit.C.FOMC)$distimes))
+ fit.C.FOMC.r <- as.numeric(c(fit.C.FOMC$bparms.optim, endpoints(fit.C.FOMC)$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)))
@@ -106,7 +106,7 @@ test.FOCUS_2006_DFOP <- function()
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$parms.all, endpoints(fit.A.DFOP)$distimes))
+ fit.A.DFOP.r <- as.numeric(c(fit.A.DFOP$bparms.optim, endpoints(fit.A.DFOP)$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)))
@@ -117,7 +117,7 @@ test.FOCUS_2006_DFOP <- function()
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$parms.all, endpoints(fit.B.DFOP)$distimes))
+ fit.B.DFOP.r <- as.numeric(c(fit.B.DFOP$bparms.optim, endpoints(fit.B.DFOP)$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)))
@@ -135,7 +135,7 @@ test.FOCUS_2006_HS <- function()
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$parms.all, endpoints(fit.A.HS)$distimes))
+ fit.A.HS.r <- as.numeric(c(fit.A.HS$bparms.optim, endpoints(fit.A.HS)$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)))
@@ -146,7 +146,7 @@ test.FOCUS_2006_HS <- function()
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$parms.all, endpoints(fit.B.HS)$distimes))
+ fit.B.HS.r <- as.numeric(c(fit.B.HS$bparms.optim, endpoints(fit.B.HS)$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)]
@@ -158,7 +158,7 @@ test.FOCUS_2006_HS <- function()
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$parms.all, endpoints(fit.A.HS)$distimes))
+ fit.A.HS.r <- as.numeric(c(fit.A.HS$bparms.optim, endpoints(fit.A.HS)$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)))
@@ -177,7 +177,7 @@ test.FOCUS_2006_SFORB <- function()
c(M0, k1, k2, DT50, DT90)), "median"))
fit.A.SFORB.1.r <- as.numeric(c(
- parent_0 = fit.A.SFORB.1$parms.all[[1]],
+ parent_0 = fit.A.SFORB.1$bparms.optim[[1]],
k1 = endpoints(fit.A.SFORB.1)$SFORB[[1]],
k2 = endpoints(fit.A.SFORB.1)$SFORB[[2]],
endpoints(fit.A.SFORB.1)$distimes))
@@ -188,7 +188,7 @@ test.FOCUS_2006_SFORB <- function()
checkIdentical(dev.A.SFORB.1 < 1, rep(TRUE, length(dev.A.SFORB.1)))
fit.A.SFORB.2.r <- as.numeric(c(
- parent_0 = fit.A.SFORB.2$parms.all[[1]],
+ parent_0 = fit.A.SFORB.2$bparms.optim[[1]],
k1 = endpoints(fit.A.SFORB.2)$SFORB[[1]],
k2 = endpoints(fit.A.SFORB.2)$SFORB[[2]],
endpoints(fit.A.SFORB.2)$distimes))
@@ -206,7 +206,7 @@ test.FOCUS_2006_SFORB <- function()
c(M0, k1, k2, DT50, DT90)), "median"))
fit.B.SFORB.1.r <- as.numeric(c(
- parent_0 = fit.B.SFORB.1$parms.all[[1]],
+ parent_0 = fit.B.SFORB.1$bparms.optim[[1]],
k1 = endpoints(fit.B.SFORB.1)$SFORB[[1]],
k2 = endpoints(fit.B.SFORB.1)$SFORB[[2]],
endpoints(fit.B.SFORB.1)$distimes))
@@ -214,7 +214,7 @@ test.FOCUS_2006_SFORB <- function()
checkIdentical(dev.B.SFORB.1 < 1, rep(TRUE, length(dev.B.SFORB.1)))
fit.B.SFORB.2.r <- as.numeric(c(
- parent_0 = fit.B.SFORB.2$parms.all[[1]],
+ 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))
@@ -239,15 +239,15 @@ test.FOCUS_2006_D_SFO_SFO <- function()
fit.2.d <- mkinfit(SFO_SFO.2, solution_type = "deSolve", FOCUS_2006_D)
# Eigenvalue based solution with maximum use of formation fractions only
# works correctly with initial parameters very close to final parameters!
- fit.2.e <- mkinfit(SFO_SFO.2, parms.ini = fit.2.d$odeparms.final, FOCUS_2006_D)
+ fit.2.e <- mkinfit(SFO_SFO.2, parms.ini = fit.2.d$bparms.ode, 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$parms.all[[1]], endpoints(fit.1.e)$distimes[[1]])
- r.1.d <- c(fit.1.d$parms.all[[1]], endpoints(fit.1.d)$distimes[[1]])
- r.2.e <- c(fit.2.e$parms.all[[1]], endpoints(fit.2.e)$distimes[[1]])
- r.2.d <- c(fit.2.d$parms.all[[1]], endpoints(fit.2.d)$distimes[[1]])
+ 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))
@@ -273,7 +273,7 @@ test.mkinfit.schaefer07_complex_example <- function()
mkin_wide_to_long(schaefer07_complex_case, time = "time"))
s <- summary(fit)
r <- schaefer07_complex_results
- attach(as.list(fit$parms.all))
+ attach(as.list(fit$bparms.optim))
k_parent <- sum(k_parent_A1, k_parent_B1, k_parent_C1)
r$mkin <- c(
k_parent,

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