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-rw-r--r--inst/unitTests/Makefile15
-rw-r--r--inst/unitTests/runit.mkinerrmin.R62
-rw-r--r--inst/unitTests/runit.mkinfit.R227
-rw-r--r--inst/unitTests/runit.mkinpredict.R86
4 files changed, 0 insertions, 390 deletions
diff --git a/inst/unitTests/Makefile b/inst/unitTests/Makefile
deleted file mode 100644
index 8d132253..00000000
--- a/inst/unitTests/Makefile
+++ /dev/null
@@ -1,15 +0,0 @@
-TOP=../..
-PKG=${shell cd ${TOP};pwd}
-SUITE=doRUnit.R
-R=R
-
-all: inst test
-
-inst: # Install package
- cd ${TOP}/..;\
- ${R} CMD INSTALL ${PKG}
-
-test: # Run unit tests
- export RCMDCHECK=FALSE;\
- cd ${TOP}/tests;\
- ${R} --vanilla --slave < ${SUITE}
diff --git a/inst/unitTests/runit.mkinerrmin.R b/inst/unitTests/runit.mkinerrmin.R
deleted file mode 100644
index 56a33ff9..00000000
--- a/inst/unitTests/runit.mkinerrmin.R
+++ /dev/null
@@ -1,62 +0,0 @@
-# Test SFO_SFO model with FOCUS_2006_D against Schaefer 2007 paper, tolerance = 1% # {{{
-# and check chi2 error values against values obtained with mkin 0.33
-test.FOCUS_2006_D_SFO_SFO <- function()
-{
- SFO_SFO.1 <- mkinmod(parent = list(type = "SFO", to = "m1"),
- m1 = list(type = "SFO"), use_of_ff = "min")
- SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"),
- m1 = list(type = "SFO"), use_of_ff = "max")
-
- fit.1.e <- mkinfit(SFO_SFO.1, FOCUS_2006_D)
- fit.1.d <- mkinfit(SFO_SFO.1, solution_type = "deSolve", FOCUS_2006_D)
- fit.2.e <- mkinfit(SFO_SFO.2, FOCUS_2006_D)
- fit.2.d <- mkinfit(SFO_SFO.2, solution_type = "deSolve", FOCUS_2006_D)
-
- FOCUS_2006_D_results_schaefer07_means <- c(
- parent_0 = 99.65, DT50_parent = 7.04, DT50_m1 = 131.34)
-
- r.1.e <- c(fit.1.e$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/inst/unitTests/runit.mkinfit.R b/inst/unitTests/runit.mkinfit.R
deleted file mode 100644
index 8eefb995..00000000
--- a/inst/unitTests/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/inst/unitTests/runit.mkinpredict.R b/inst/unitTests/runit.mkinpredict.R
deleted file mode 100644
index 997857ce..00000000
--- a/inst/unitTests/runit.mkinpredict.R
+++ /dev/null
@@ -1,86 +0,0 @@
-# $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:

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