Nothing
tests/testthat/testTraitWrappers.r
In growthPheno: Functional Analysis of Phenotypic Growth Data to Smooth and Extract Traits
#Tests for the trait wrapper functions
cat("#### Test traitSmooth with small example\n")
test_that("exampleData_traitSmooth", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(growthPheno)
data(exampleData)
testthat::expect_true(all(abs(longi.dat$sPSA[1:3] - c(51.18456, 87.67343, 107.68232)) < 1e-03))
testthat::expect_true(all(abs(longi.dat$sPSA.AGR[2:4] - c(18.24443, 20.00889, 22.13115)) < 1e-03))
vline <- list(ggplot2::geom_vline(xintercept=29, linetype="longdash", linewidth=1))
trt.facets <- c("Smarthouse", "Treatment.1")
#Get a chosen smooth - can set an option without worrying about the other option in traitSmooth
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag", times = "DAP",
keep.columns = trt.facets,
profile.plot.args =
args4profile_plot(facet.y = trt.facets,
include.raw = "no",
breaks.spacing.x = -2,
addMediansWhiskers = TRUE, #used whenever plotLongitudinal is used
ggplotFuncs = vline),
chosen.plot.args =
args4chosen_plot(facet.y = trt.facets),
mergedata = longi.dat),
regexp = "containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
testthat::expect_true(all(names(longi.dat) %in% names(smth.dat)))
testthat::expect_true(all(longi.dat$Snapshot.ID.Tag == smth.dat$Snapshot.ID.Tag))
testthat::expect_true(all(c("Smarthouse","Treatment.1","PSA","PSA.AGR","PSA.RGR",
"sPSA","sPSA.AGR","sPSA.RGR") %in% names(smth.dat)))
#Get the full set of smooths
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(facet.y = trt.facets,
include.raw = "no",
collapse.facets.x = FALSE,
breaks.spacing.x = -2,
ggplotFuncs = vline))
testthat::expect_equal(nrow(smth.dat), 1960)
testthat::expect_equal(ncol(smth.dat), 16)
#Supply smth.dat and do just the profile plots
tmp.dat <- traitSmooth(data = smth.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(facet.y = trt.facets,
include.raw = "facet.x",
collapse.facets.x = FALSE,
breaks.spacing.x = -2,
ggplotFuncs = vline))
testthat::expect_equal(nrow(smth.dat), 1960)
testthat::expect_equal(ncol(smth.dat), 16)
#Supply smth.dat and do just the chosen plots
tmp.dat <- traitSmooth(data = smth.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
which.plots = "none",
chosen.smooth.args =
args4chosen_smooth(lambda = 3.162),
chosen.plot.args =
args4chosen_plot(facet.y = trt.facets,
ggplotFuncs = vline),
mergedata = longi.dat)
testthat::expect_equal(nrow(tmp.dat), 280)
testthat::expect_equal(ncol(tmp.dat), 37)
testthat::expect_true(all(names(longi.dat) %in% names(tmp.dat)))
testthat::expect_true(all(longi.dat$Snapshot.ID.Tag == tmp.dat$Snapshot.ID.Tag))
testthat::expect_true(all(c("Smarthouse","Treatment.1","sPSA","sPSA.AGR","sPSA.RGR")
%in% names(tmp.dat)))
testthat::expect_true(all(abs(tmp.dat$sPSA[1:3] - c(58.6448, 87.0271, 105.4621)) < 1e-03))
testthat::expect_true(all(abs(tmp.dat$sPSA.AGR[2:4] - c(14.19115, 18.43499, 21.57451)) < 1e-03))
#Extract a single.smooth
tmp.dat <- traitSmooth(data = smth.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
which.plots = "none", chosen.smooth.args = NULL,
chosen.plot.args = NULL)
testthat::expect_equal(nrow(tmp.dat), 280)
testthat::expect_equal(ncol(tmp.dat), 11)
#Produce a single smooth
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = "Type",
facet.x = trt.facets, facet.y = "Tuning",
include.raw = "facet.y",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline)),
regexp = "Removed 4 rows containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
#Test plotting raw in yfacet when yfacet is "."
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = c("Type","Method","Tuning"),
facet.x = trt.facets, facet.y = ".",
include.raw = "facet.y",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline)),
regexp = "Removed 4 rows containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
#Test plotting raw in xfacet when xfacet is "."
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = c("Type","Method","Tuning"),
facet.x = ".", facet.y = trt.facets,
include.raw = "facet.x",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline)),
regexp = "Removed 4 rows containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
#Test scales.pf
#Supply smth.dat and do just the profile plots
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
chosen.smooth = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = "Type",
facet.x = trt.facets, facet.y = "Tuning",
include.raw = "facet.y",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline))
testthat::expect_equal(nrow(smth.dat), 1960)
testthat::expect_equal(ncol(smth.dat), 16)
})
cat("#### Test traitExtractFeatures with tomato example\n")
test_that("tomato_traitExtractFeatures", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(dae)
library(growthPheno)
data(tomato.dat)
DAP.endpts <- c(18,22,27,33,39,43,51)
nDAP.endpts <- length(DAP.endpts)
DAP.starts <- DAP.endpts[-nDAP.endpts]
DAP.stops <- DAP.endpts[-1]
DAP.mids <- (DAP.starts + DAP.stops)/2
DAP.segs <- list(c(DAP.endpts[1]-1, 39),
c(40, DAP.endpts[nDAP.endpts]))
#Add PSA rates and smooth PSA, also producing sPSA rates
tom.dat <- byIndv4Times_SplinesGRs(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP", rates.method = "differences",
smoothing.method = "log",
spline.type = "PS", lambda = 1,
smoothing.segments = DAP.segs)
#Smooth WU
tom.dat <- byIndv4Times_SplinesGRs(data = tom.dat,
response = "WU", response.smoothed = "sWU",
rates.method = "none",
times = "DAP",
smoothing.method = "direct",
spline.type = "PS", lambda = 10^(-0.5),
smoothing.segments = DAP.segs)
testthat::expect_equal(nrow(tom.dat), 1120)
testthat::expect_equal(ncol(tom.dat), 20)
#Test with overlapping segments and rates.method = "differences",
DAP.segs <- list(c(DAP.endpts[1]-1, 39),
c(38, DAP.endpts[nDAP.endpts]))
#Add PSA rates and smooth PSA, also producing sPSA rates
tmp.dat <- testthat::expect_error(
byIndv4Times_SplinesGRs(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP", rates.method = "differences",
smoothing.method = "log",
spline.type = "PS", lambda = 1,
smoothing.segments = DAP.segs),
regexp = "rates.method must be `none` when times values occur in more than one smoothing segment")
#Test with overlapping segments and rates.method = "none",
#Add PSA rates and smooth PSA, also producing sPSA rates
tmp.dat <- testthat::expect_warning(
byIndv4Times_SplinesGRs(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP", rates.method = "none",
smoothing.method = "log",
spline.type = "PS", lambda = 1,
smoothing.segments = DAP.segs),
regexp = paste0("The values for some times occur in multiple smoothing.segments and so some individuals ",
"will have multiple rows in the returned data.frame, one for each segment in which the ",
"times occur."))
testthat::expect_true(all(table(tmp.dat$DAP) %in% c(32,64)))
testthat::expect_equal(nrow(tmp.dat), 1184)
table(with(tmp.dat, tmp.dat[c(DAP %in% 38:39),]$DAP))
tmp <- with(tmp.dat, tmp.dat[c(DAP %in% 38:39),c("DAP","sPSA")])
tmp$DAP <- factor(tmp$DAP)
testthat::expect_true(all(table(tmp$DAP) == 64))
testthat::expect_true(all(diff(tmp$sPSA) != 0))
### Omit responses for the outlier plant
omit <- with(tom.dat, Zn==90 & AMF=="+" & Block ==4)
responses.all <- names(tom.dat)[match("Weight.After", names(tom.dat)):length(tom.dat)]
tom.dat[responses.all] <- lapply(tom.dat[responses.all],
function(kcol, omit)
{
kcol[omit] <- NA
return(kcol)
}, omit = omit)
#Set up for individual traits
indv.cols <- c("Snapshot.ID.Tag", "Lane", "Position", "Block", "Cart", "AMF", "Zn")
indv.ini <- subset(tom.dat, subset = DAP == DAP.endpts[1],
select = indv.cols)
#'## Extract single-valued smoothed traits for each individual
indv.dat <- traitExtractFeatures(data = tom.dat,
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = "sPSA", growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = "sWU",
responses4water = "sPSA",
responses4singletimes = "sPSA",
responses4overall.total = "sWU",
responses4overall.max = "sPSA.AGR",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 47)
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = c("PSA", "sPSA"), growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = c("WU","sWU"),
responses4water = c("PSA","sPSA"),
responses4singletimes = c("PSA", "sPSA"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*7) + (4*6) + (6*6) + 4 + 6) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "to")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = ".")),
as.vector(outer(c("PSA.AGR","PSA.RGR"), suffs, paste, sep = ".")),
as.vector(outer(c("sPSA.AGR","sPSA.RGR"), suffs, paste, sep = ".")),
as.vector(outer(c("WU","WUR","PSA.WUI"), suffs, paste, sep = ".")),
as.vector(outer(c("sWU","sWUR","sPSA.sWUI"), suffs, paste, sep = ".")),
"PSA.AGR","PSA.RGR","sPSA.AGR","sPSA.RGR","WU","WUR","PSA.WUI",
"sWU","sWUR","sPSA.sWUI")))
#'## Extract water traits only
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
water.trait.types = "WU",
water.use4intvl.traits = c("WU","sWU"),
water.use4overall.water = c("WU","sWU"),
intvl.overall = c(18,51), suffix.overall = "total",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*6) + 2) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "to")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer("WU", suffs, paste, sep = ".")),
as.vector(outer("sWU", suffs, paste, sep = ".")),
"WU.total","sWU.total")))
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual with "_" separator
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = c("PSA", "sPSA"), growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = c("WU","sWU"),
responses4water = c("PSA","sPSA"),
responses4singletimes = c("PSA", "sPSA"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
sep.growth.rates = "_", sep.water.traits = "_",
sep.suffix.times = "_", sep.times.intvl = "_",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*7) + (4*6) + (6*6) + 4 + 6) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "_")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = "_")),
as.vector(outer(c("PSA_AGR","PSA_RGR"), suffs, paste, sep = "_")),
as.vector(outer(c("sPSA_AGR","sPSA_RGR"), suffs, paste, sep = "_")),
as.vector(outer(c("WU","WU_R","PSA_WU_I"), suffs, paste, sep = "_")),
as.vector(outer(c("sWU","sWU_R","sPSA_sWU_I"), suffs, paste, sep = "_")),
"PSA_AGR","PSA_RGR","sPSA_AGR","sPSA_RGR","WU","WU_R","PSA_WU_I",
"sWU","sWU_R","sPSA_sWU_I")))
#Check the overall values
testthat::expect_true(all((indv.dat[1, c("PSA_AGR","PSA_RGR","sPSA_AGR","sPSA_RGR","WU","WU_R","PSA_WU_I",
"sWU","sWU_R","sPSA_sWU_I")] -
c( 4.899273,0.08852807,4.897457,0.08655332,932,28.24242,0.1734721,
921.4677,27.92326,0.1753898)) < 1e-04))
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual with no separator
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = c("PSA", "sPSA"), growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = c("WU","sWU"),
responses4water = c("PSA","sPSA"),
responses4singletimes = c("PSA", "sPSA"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
sep.growth.rates = "", sep.water.traits = "",
sep.suffix.times = "", sep.times.intvl = "",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*7) + (4*6) + (6*6) + 4 + 6) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = "")),
as.vector(outer(c("PSAAGR","PSARGR"), suffs, paste, sep = "")),
as.vector(outer(c("sPSAAGR","sPSARGR"), suffs, paste, sep = "")),
as.vector(outer(c("WU","WUR","PSAWUI"), suffs, paste, sep = "")),
as.vector(outer(c("sWU","sWUR","sPSAsWUI"), suffs, paste, sep = "")),
"PSAAGR","PSARGR","sPSAAGR","sPSARGR","WU","WUR","PSAWUI",
"sWU","sWUR","sPSAsWUI")))
#one AGR for sPSA and its overall AGR
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = "sPSA",
growth.rates = "AGR",
responses4overall.rates = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 14)
#Overall values only for both unsmoothed and smoothed traits in parallel
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = c("AGR", "RGR"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini)
#Check the overall values
testthat::expect_true(all((indv.dat[1, c("PSA.AGR","PSA.RGR","sPSA.AGR","sPSA.RGR","WU","WUR","PSA.WUI",
"sWU","sWUR","sPSA.sWUI")] -
c( 4.899273,0.08852807,4.897457,0.08655332,932,28.24242,0.1734721,
921.4677,27.92326,0.1753898)) < 1e-04))
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 17)
#Overall values only for smoothed traits
testthat::expect_error(indv.diff.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
responses4overall.rates = "sPSA",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini),
regexp = "growth.rates needs to be set for responses4overall.rates")
indv.diff.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = "AGR",
responses4overall.rates = "sPSA",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.diff.dat), 32)
testthat::expect_equal(ncol(indv.diff.dat), 11)
#only overall water traits
indv.diff.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.diff.dat), 32)
testthat::expect_equal(ncol(indv.diff.dat), 10)
#Overall values only for unsmoothed and smoothed traits in parallel using ratesaverage
testthat::expect_silent(
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = c("AGR", "RGR"), rates.method = "ratesaverage",
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini))
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 17)
#Overall values only for smoothed traits using ratesaverage
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = "sPSA",
growth.rates = "AGR", rates.method = "ratesaverage",
responses4overall.rates = "sPSA",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 17)
#Check the overall values
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = c("AGR", "RGR"), rates.method = "ratesaverage",
responses4overall.rates = c("PSA","sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_true(all((indv.dat[1, c("PSA.AGR","PSA.RGR","sPSA.AGR","sPSA.RGR","WU","WUR","PSA.WUI",
"sWU","sWUR","sPSA.sWUI")] -
c( 4.899273,0.08852807,4.897457,0.08655332,932,28.24242,0.1734721,
921.4677,27.92326,0.1753898)) < 1e-04))
#Only singletimes
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual with no separator
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
responses4singletimes = c("PSA", "sPSA"),
times.single = DAP.endpts,
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 21)
suffs <- paste(DAP.starts, DAP.stops, sep = "")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = "."))))
})
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#Tests for the trait wrapper functions
cat("#### Test traitSmooth with small example\n")
test_that("exampleData_traitSmooth", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(growthPheno)
data(exampleData)
testthat::expect_true(all(abs(longi.dat$sPSA[1:3] - c(51.18456, 87.67343, 107.68232)) < 1e-03))
testthat::expect_true(all(abs(longi.dat$sPSA.AGR[2:4] - c(18.24443, 20.00889, 22.13115)) < 1e-03))
vline <- list(ggplot2::geom_vline(xintercept=29, linetype="longdash", linewidth=1))
trt.facets <- c("Smarthouse", "Treatment.1")
#Get a chosen smooth - can set an option without worrying about the other option in traitSmooth
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag", times = "DAP",
keep.columns = trt.facets,
profile.plot.args =
args4profile_plot(facet.y = trt.facets,
include.raw = "no",
breaks.spacing.x = -2,
addMediansWhiskers = TRUE, #used whenever plotLongitudinal is used
ggplotFuncs = vline),
chosen.plot.args =
args4chosen_plot(facet.y = trt.facets),
mergedata = longi.dat),
regexp = "containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
testthat::expect_true(all(names(longi.dat) %in% names(smth.dat)))
testthat::expect_true(all(longi.dat$Snapshot.ID.Tag == smth.dat$Snapshot.ID.Tag))
testthat::expect_true(all(c("Smarthouse","Treatment.1","PSA","PSA.AGR","PSA.RGR",
"sPSA","sPSA.AGR","sPSA.RGR") %in% names(smth.dat)))
#Get the full set of smooths
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(facet.y = trt.facets,
include.raw = "no",
collapse.facets.x = FALSE,
breaks.spacing.x = -2,
ggplotFuncs = vline))
testthat::expect_equal(nrow(smth.dat), 1960)
testthat::expect_equal(ncol(smth.dat), 16)
#Supply smth.dat and do just the profile plots
tmp.dat <- traitSmooth(data = smth.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(facet.y = trt.facets,
include.raw = "facet.x",
collapse.facets.x = FALSE,
breaks.spacing.x = -2,
ggplotFuncs = vline))
testthat::expect_equal(nrow(smth.dat), 1960)
testthat::expect_equal(ncol(smth.dat), 16)
#Supply smth.dat and do just the chosen plots
tmp.dat <- traitSmooth(data = smth.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
which.plots = "none",
chosen.smooth.args =
args4chosen_smooth(lambda = 3.162),
chosen.plot.args =
args4chosen_plot(facet.y = trt.facets,
ggplotFuncs = vline),
mergedata = longi.dat)
testthat::expect_equal(nrow(tmp.dat), 280)
testthat::expect_equal(ncol(tmp.dat), 37)
testthat::expect_true(all(names(longi.dat) %in% names(tmp.dat)))
testthat::expect_true(all(longi.dat$Snapshot.ID.Tag == tmp.dat$Snapshot.ID.Tag))
testthat::expect_true(all(c("Smarthouse","Treatment.1","sPSA","sPSA.AGR","sPSA.RGR")
%in% names(tmp.dat)))
testthat::expect_true(all(abs(tmp.dat$sPSA[1:3] - c(58.6448, 87.0271, 105.4621)) < 1e-03))
testthat::expect_true(all(abs(tmp.dat$sPSA.AGR[2:4] - c(14.19115, 18.43499, 21.57451)) < 1e-03))
#Extract a single.smooth
tmp.dat <- traitSmooth(data = smth.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
which.plots = "none", chosen.smooth.args = NULL,
chosen.plot.args = NULL)
testthat::expect_equal(nrow(tmp.dat), 280)
testthat::expect_equal(ncol(tmp.dat), 11)
#Produce a single smooth
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = "Type",
facet.x = trt.facets, facet.y = "Tuning",
include.raw = "facet.y",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline)),
regexp = "Removed 4 rows containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
#Test plotting raw in yfacet when yfacet is "."
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = c("Type","Method","Tuning"),
facet.x = trt.facets, facet.y = ".",
include.raw = "facet.y",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline)),
regexp = "Removed 4 rows containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
#Test plotting raw in xfacet when xfacet is "."
testthat::expect_warning(
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
smoothing.args =
args4smoothing(spline.types = "PS",
df = NULL, lambdas = 3.162),
chosen.smooth.args = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = c("Type","Method","Tuning"),
facet.x = ".", facet.y = trt.facets,
include.raw = "facet.x",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline)),
regexp = "Removed 4 rows containing missing values or values outside the scale range \\(\\`geom_vline\\(\\)\\`\\)")
testthat::expect_equal(nrow(smth.dat), 280)
testthat::expect_equal(ncol(smth.dat), 37)
#Test scales.pf
#Supply smth.dat and do just the profile plots
smth.dat <- traitSmooth(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
individuals = "Snapshot.ID.Tag",times = "DAP",
keep.columns = trt.facets,
chosen.smooth = NULL,
which.plots = "profile",
profile.plot.args =
args4profile_plot(plots.by = "Type",
facet.x = trt.facets, facet.y = "Tuning",
include.raw = "facet.y",
collapse.facets.x = FALSE,
facet.scales = "free_y",
breaks.spacing.x = -2, angle.x = 90,
ggplotFuncs = vline))
testthat::expect_equal(nrow(smth.dat), 1960)
testthat::expect_equal(ncol(smth.dat), 16)
})
cat("#### Test traitExtractFeatures with tomato example\n")
test_that("tomato_traitExtractFeatures", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(dae)
library(growthPheno)
data(tomato.dat)
DAP.endpts <- c(18,22,27,33,39,43,51)
nDAP.endpts <- length(DAP.endpts)
DAP.starts <- DAP.endpts[-nDAP.endpts]
DAP.stops <- DAP.endpts[-1]
DAP.mids <- (DAP.starts + DAP.stops)/2
DAP.segs <- list(c(DAP.endpts[1]-1, 39),
c(40, DAP.endpts[nDAP.endpts]))
#Add PSA rates and smooth PSA, also producing sPSA rates
tom.dat <- byIndv4Times_SplinesGRs(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP", rates.method = "differences",
smoothing.method = "log",
spline.type = "PS", lambda = 1,
smoothing.segments = DAP.segs)
#Smooth WU
tom.dat <- byIndv4Times_SplinesGRs(data = tom.dat,
response = "WU", response.smoothed = "sWU",
rates.method = "none",
times = "DAP",
smoothing.method = "direct",
spline.type = "PS", lambda = 10^(-0.5),
smoothing.segments = DAP.segs)
testthat::expect_equal(nrow(tom.dat), 1120)
testthat::expect_equal(ncol(tom.dat), 20)
#Test with overlapping segments and rates.method = "differences",
DAP.segs <- list(c(DAP.endpts[1]-1, 39),
c(38, DAP.endpts[nDAP.endpts]))
#Add PSA rates and smooth PSA, also producing sPSA rates
tmp.dat <- testthat::expect_error(
byIndv4Times_SplinesGRs(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP", rates.method = "differences",
smoothing.method = "log",
spline.type = "PS", lambda = 1,
smoothing.segments = DAP.segs),
regexp = "rates.method must be `none` when times values occur in more than one smoothing segment")
#Test with overlapping segments and rates.method = "none",
#Add PSA rates and smooth PSA, also producing sPSA rates
tmp.dat <- testthat::expect_warning(
byIndv4Times_SplinesGRs(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times = "DAP", rates.method = "none",
smoothing.method = "log",
spline.type = "PS", lambda = 1,
smoothing.segments = DAP.segs),
regexp = paste0("The values for some times occur in multiple smoothing.segments and so some individuals ",
"will have multiple rows in the returned data.frame, one for each segment in which the ",
"times occur."))
testthat::expect_true(all(table(tmp.dat$DAP) %in% c(32,64)))
testthat::expect_equal(nrow(tmp.dat), 1184)
table(with(tmp.dat, tmp.dat[c(DAP %in% 38:39),]$DAP))
tmp <- with(tmp.dat, tmp.dat[c(DAP %in% 38:39),c("DAP","sPSA")])
tmp$DAP <- factor(tmp$DAP)
testthat::expect_true(all(table(tmp$DAP) == 64))
testthat::expect_true(all(diff(tmp$sPSA) != 0))
### Omit responses for the outlier plant
omit <- with(tom.dat, Zn==90 & AMF=="+" & Block ==4)
responses.all <- names(tom.dat)[match("Weight.After", names(tom.dat)):length(tom.dat)]
tom.dat[responses.all] <- lapply(tom.dat[responses.all],
function(kcol, omit)
{
kcol[omit] <- NA
return(kcol)
}, omit = omit)
#Set up for individual traits
indv.cols <- c("Snapshot.ID.Tag", "Lane", "Position", "Block", "Cart", "AMF", "Zn")
indv.ini <- subset(tom.dat, subset = DAP == DAP.endpts[1],
select = indv.cols)
#'## Extract single-valued smoothed traits for each individual
indv.dat <- traitExtractFeatures(data = tom.dat,
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = "sPSA", growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = "sWU",
responses4water = "sPSA",
responses4singletimes = "sPSA",
responses4overall.total = "sWU",
responses4overall.max = "sPSA.AGR",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 47)
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = c("PSA", "sPSA"), growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = c("WU","sWU"),
responses4water = c("PSA","sPSA"),
responses4singletimes = c("PSA", "sPSA"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*7) + (4*6) + (6*6) + 4 + 6) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "to")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = ".")),
as.vector(outer(c("PSA.AGR","PSA.RGR"), suffs, paste, sep = ".")),
as.vector(outer(c("sPSA.AGR","sPSA.RGR"), suffs, paste, sep = ".")),
as.vector(outer(c("WU","WUR","PSA.WUI"), suffs, paste, sep = ".")),
as.vector(outer(c("sWU","sWUR","sPSA.sWUI"), suffs, paste, sep = ".")),
"PSA.AGR","PSA.RGR","sPSA.AGR","sPSA.RGR","WU","WUR","PSA.WUI",
"sWU","sWUR","sPSA.sWUI")))
#'## Extract water traits only
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
water.trait.types = "WU",
water.use4intvl.traits = c("WU","sWU"),
water.use4overall.water = c("WU","sWU"),
intvl.overall = c(18,51), suffix.overall = "total",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*6) + 2) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "to")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer("WU", suffs, paste, sep = ".")),
as.vector(outer("sWU", suffs, paste, sep = ".")),
"WU.total","sWU.total")))
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual with "_" separator
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = c("PSA", "sPSA"), growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = c("WU","sWU"),
responses4water = c("PSA","sPSA"),
responses4singletimes = c("PSA", "sPSA"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
sep.growth.rates = "_", sep.water.traits = "_",
sep.suffix.times = "_", sep.times.intvl = "_",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*7) + (4*6) + (6*6) + 4 + 6) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "_")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = "_")),
as.vector(outer(c("PSA_AGR","PSA_RGR"), suffs, paste, sep = "_")),
as.vector(outer(c("sPSA_AGR","sPSA_RGR"), suffs, paste, sep = "_")),
as.vector(outer(c("WU","WU_R","PSA_WU_I"), suffs, paste, sep = "_")),
as.vector(outer(c("sWU","sWU_R","sPSA_sWU_I"), suffs, paste, sep = "_")),
"PSA_AGR","PSA_RGR","sPSA_AGR","sPSA_RGR","WU","WU_R","PSA_WU_I",
"sWU","sWU_R","sPSA_sWU_I")))
#Check the overall values
testthat::expect_true(all((indv.dat[1, c("PSA_AGR","PSA_RGR","sPSA_AGR","sPSA_RGR","WU","WU_R","PSA_WU_I",
"sWU","sWU_R","sPSA_sWU_I")] -
c( 4.899273,0.08852807,4.897457,0.08655332,932,28.24242,0.1734721,
921.4677,27.92326,0.1753898)) < 1e-04))
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual with no separator
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = c("PSA", "sPSA"), growth.rates = c("AGR", "RGR"),
water.use4intvl.traits = c("WU","sWU"),
responses4water = c("PSA","sPSA"),
responses4singletimes = c("PSA", "sPSA"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
sep.growth.rates = "", sep.water.traits = "",
sep.suffix.times = "", sep.times.intvl = "",
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 7 + (2*7) + (4*6) + (6*6) + 4 + 6) #91
suffs <- paste(DAP.starts, DAP.stops, sep = "")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == c(as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = "")),
as.vector(outer(c("PSAAGR","PSARGR"), suffs, paste, sep = "")),
as.vector(outer(c("sPSAAGR","sPSARGR"), suffs, paste, sep = "")),
as.vector(outer(c("WU","WUR","PSAWUI"), suffs, paste, sep = "")),
as.vector(outer(c("sWU","sWUR","sPSAsWUI"), suffs, paste, sep = "")),
"PSAAGR","PSARGR","sPSAAGR","sPSARGR","WU","WUR","PSAWUI",
"sWU","sWUR","sPSAsWUI")))
#one AGR for sPSA and its overall AGR
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = "sPSA",
growth.rates = "AGR",
responses4overall.rates = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 14)
#Overall values only for both unsmoothed and smoothed traits in parallel
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = c("AGR", "RGR"),
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini)
#Check the overall values
testthat::expect_true(all((indv.dat[1, c("PSA.AGR","PSA.RGR","sPSA.AGR","sPSA.RGR","WU","WUR","PSA.WUI",
"sWU","sWUR","sPSA.sWUI")] -
c( 4.899273,0.08852807,4.897457,0.08655332,932,28.24242,0.1734721,
921.4677,27.92326,0.1753898)) < 1e-04))
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 17)
#Overall values only for smoothed traits
testthat::expect_error(indv.diff.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
responses4overall.rates = "sPSA",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini),
regexp = "growth.rates needs to be set for responses4overall.rates")
indv.diff.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = "AGR",
responses4overall.rates = "sPSA",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.diff.dat), 32)
testthat::expect_equal(ncol(indv.diff.dat), 11)
#only overall water traits
indv.diff.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.diff.dat), 32)
testthat::expect_equal(ncol(indv.diff.dat), 10)
#Overall values only for unsmoothed and smoothed traits in parallel using ratesaverage
testthat::expect_silent(
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = c("AGR", "RGR"), rates.method = "ratesaverage",
responses4overall.rates = c("PSA", "sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini))
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 17)
#Overall values only for smoothed traits using ratesaverage
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
starts.intvl = DAP.starts, stops.intvl = DAP.stops,
responses4intvl.rates = "sPSA",
growth.rates = "AGR", rates.method = "ratesaverage",
responses4overall.rates = "sPSA",
water.use4overall.water = "sWU",
responses4overall.water = "sPSA",
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 17)
#Check the overall values
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
growth.rates = c("AGR", "RGR"), rates.method = "ratesaverage",
responses4overall.rates = c("PSA","sPSA"),
water.use4overall.water = c("WU","sWU"),
responses4overall.water = c("PSA","sPSA"),
intvl.overall = c(18,51),
mergedata = indv.ini)
testthat::expect_true(all((indv.dat[1, c("PSA.AGR","PSA.RGR","sPSA.AGR","sPSA.RGR","WU","WUR","PSA.WUI",
"sWU","sWUR","sPSA.sWUI")] -
c( 4.899273,0.08852807,4.897457,0.08655332,932,28.24242,0.1734721,
921.4677,27.92326,0.1753898)) < 1e-04))
#Only singletimes
#'## Extract single-valued unsmoothed and smoothed traits in parallel for each individual with no separator
indv.dat <- traitExtractFeatures(data = tom.dat, times = "DAP",
responses4singletimes = c("PSA", "sPSA"),
times.single = DAP.endpts,
mergedata = indv.ini)
testthat::expect_equal(nrow(indv.dat), 32)
testthat::expect_equal(ncol(indv.dat), 21)
suffs <- paste(DAP.starts, DAP.stops, sep = "")
testthat::expect_true(all(names(indv.dat)[-(1:7)] == as.vector(outer(c("PSA","sPSA"), DAP.endpts, paste, sep = "."))))
})
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