Nothing
#devtools::test("asremlPlus")
context("prediction_presentation")
cat("#### Test for sort.alldiffs on Smarthouse with asreml42\n")
test_that("sort.alldiffs42", {
skip_if_not_installed("asreml")
skip_on_cran()
library(asreml)
library(asremlPlus)
library(dae)
data(Smarthouse.dat)
#Set up without any sorting
m1.asr <- asreml(y1 ~ Genotype*A*B,
random=~Replicate/Mainplot/Subplot,
data=Smarthouse.dat)
testthat::expect_equal(length(m1.asr$vparameters),4)
current.asrt <- as.asrtests(m1.asr)
current.asrt <- rmboundary(current.asrt)
m <- current.asrt$asreml.obj
testthat::expect_equal(length(m$vparameters),3)
diffs <- predictPlus(m, classify = "Genotype:A:B",
wald.tab = current.asrt$wald.tab,
error.intervals = "Stand", tables = "none")
testthat::expect_is(diffs, "alldiffs")
testthat::expect_true(validAlldiffs(diffs))
testthat::expect_equal(nrow(diffs$predictions),120)
testthat::expect_equal(ncol(diffs$predictions),8)
testthat::expect_equal(as.character(diffs$predictions$Genotype[1]),"Axe")
testthat::expect_equal(length(attributes(diffs)),11)
testthat::expect_true(is.null(attr(diffs, which = "sortOrder")))
testthat::expect_silent(plotPredictions(data = diffs$predictions,
classify = "Genotype:A:B",
y = "predicted.value",
error.intervals = "StandardError",
y.title = attr(diffs,
which = "response.title")))
#Test sort in plotPredictions
testthat::expect_silent(plotPredictions(data = diffs$predictions,
classify = "Genotype:A:B",
y = "predicted.value",
error.intervals = "StandardError",
y.title = attr(diffs,
which = "response.title"),
sortFactor = "Genotype"))
#Test sort.alldiffs and save order for use with other response variables
diffs.sort <- sort(diffs, sortFactor = "Genotype")
sort.order <- attr(diffs.sort, which = "sortOrder")
testthat::expect_is(diffs.sort, "alldiffs")
testthat::expect_equal(nrow(diffs.sort$predictions),120)
testthat::expect_equal(ncol(diffs.sort$predictions),8)
testthat::expect_equal(as.character(diffs.sort$predictions$Genotype[1]),"Gladius")
testthat::expect_equal(length(attributes(diffs.sort)),13)
testthat::expect_equal(length(attr(diffs.sort, which = "sortOrder")),10)
#Test sort.alldiffs with supplied sortOrder
m2.asr <- asreml(y2 ~ Genotype*A*B,
random=~Replicate/Mainplot/Subplot,
data=Smarthouse.dat)
testthat::expect_equal(length(m1.asr$vparameters),4)
current.asrt <- as.asrtests(m2.asr)
diffs2.sort <- predictPlus(m2.asr, classify = "Genotype:A:B",
wald.tab = current.asrt$wald.tab,
error.intervals = "Stand", tables = "none",
sortFactor = "Genotype",
sortOrder = sort.order)
testthat::expect_equal(as.character(diffs.sort$predictions$Genotype[1]),
as.character(diffs2.sort$predictions$Genotype[1]))
testthat::expect_equal(attr(diffs.sort, which = "sortOrder"),
attr(diffs2.sort, which = "sortOrder"))
#Test sort.alldiffs with sortParallelToCombo and increasing order
diffs1.sort <- sort(diffs, sortFactor = "Genotype",
sortParallelToCombo = list(A = "N3", B = "D4"),
decreasing = TRUE)
diffs1.sort <- renewClassify(diffs1.sort, newclassify = "A:B:Genotype")
testthat::expect_is(diffs1.sort, "alldiffs")
testthat::expect_equal(as.character(attr(diffs1.sort, which = "sortOrder")[2]),"Wyalkatchem")
testthat::expect_equal(length(attr(diffs1.sort, which = "sortOrder")), 10)
#Check plot
testthat::expect_silent(plotPredictions(data = diffs1.sort$predictions,
classify = "Genotype:A:B",
y = "predicted.value",
error.intervals = "StandardError",
y.title = attr(diffs,
which = "response.title"),
sortFactor = "Genotype"))
})
cat("#### Test for sort.predictions.frame on WaterRunoff with asreml42\n")
test_that("sort.predictions.frame42", {
skip_if_not_installed("asreml")
skip_on_cran()
library(asreml)
library(asremlPlus)
library(dae)
data(WaterRunoff.dat)
tmp <- subset(WaterRunoff.dat, Date == "05-18")
##Use asreml to get predictions
#Analyse pH
m1.asr <- do.call(asreml,
list(fixed = pH ~ Benches + (Sources * (Type + Species)),
random = ~ Benches:MainPlots,
keep.order=TRUE, data= tmp))
current.asrt <- as.asrtests(m1.asr, NULL, NULL)
current.asrt <- as.asrtests(m1.asr)
current.asrt <- rmboundary(current.asrt)
m1.asr <- current.asrt$asreml.obj
#Get predictions and associated statistics
TS.diffs <- predictPlus.asreml(classify = "Sources:Type",
asreml.obj = m1.asr, tables = "none",
wald.tab = current.asrt$wald.tab,
present = c("Type","Species","Sources"))
#Use sort.predictions.frame and save order for use with other response variables
TS.preds <- TS.diffs$predictions
TS.preds.sort <- sort(TS.preds, classify = "Sources:Type",
sortFactor = "Sources", sortParallelToCombo = list(Type = "Control"))
TS.preds.sort[TS.preds.sort$Type == "Control", ]
sort.order <- attr(TS.preds.sort, which = "sortOrder")
testthat::expect_true(all(sort.order == c("Rain+Basalt", "Rain+Dolomite", "Tap water",
"Recycled water", "Rainwater", "Rain+Quartzite")))
diffs.full <- predictPlus.asreml(asreml.obj = m1.asr,
classify = "Sources:Type:Species",
wald.tab = current.asrt$wald.tab,
present = c("Type","Species","Sources"),
tables = "none", Vmatrix = TRUE)
testthat::expect_true(setequal(names(diffs.full$predictions),
c("Sources", "Type", "Species", "predicted.value",
"standard.error", "upper.Confidence.limit",
"lower.Confidence.limit", "est.status")))
pred <- diffs.full$predictions
diffs.sort <- sort(diffs.full, sortFactor = "Species", sortNestingFactor = "Type",
sortParallelToCombo = list(Sources = "Rain+Dolomite"))
testthat::expect_true(all(diffs.sort$predictions$Species[diffs.sort$predictions$Sources == "Rain+Dolomite"] ==
c("S. oymwjrcnepv", "S. iqscjbogxah", "S. ocphawvtlgi", "S. orcxszbujml",
"S. hbpgtylxqku", "S. tkujbvipoyr", "S. xeqackngdrt", 'Non-planted')))
testthat::expect_false(all(diffs.sort$predictions$predicted.value == pred$predicted.value))
t <- merge(diffs.sort$predictions, pred, by = c("Sources","Type","Species"))
testthat::expect_true(all(t$predicted.value.x == t$predicted.value.y))
})
cat("#### Test for sort.alldiffs on Oats with asreml42\n")
test_that("sort.alldiffs42", {
skip_if_not_installed("asreml")
skip_on_cran()
library(asreml)
library(asremlPlus)
library(dae)
data(Oats.dat)
m1.asr <- asreml(Yield ~ Nitrogen*Variety,
random=~Blocks/Wplots,
data=Oats.dat)
testthat::expect_equal(length(m1.asr$vparameters),3)
current.asrt <- as.asrtests(m1.asr)
#Test for as.alldiffs
Var.pred <- predict(m1.asr, classify="Nitrogen:Variety", sed=TRUE)
wald.tab <- current.asrt$wald.tab
den.df <- wald.tab[match("Variety", rownames(wald.tab)), "denDF"]
Var.diffs <- as.alldiffs(predictions = Var.pred$pvals,
sed = Var.pred$sed,
tdf = den.df)
testthat::expect_equal(length(attributes(Var.diffs)),4)
testthat::expect_true(is.null(attr(Var.diffs, which = "sortOrder")))
#Test for predictPlus no sorting
diffs <- predictPlus(m1.asr, classify = "Nitrogen:Variety",
wald.tab = current.asrt$wald.tab,
error.intervals = "Stand", tables = "none")
testthat::expect_is(diffs, "alldiffs")
testthat::expect_equal(nrow(diffs$predictions),12)
testthat::expect_equal(ncol(diffs$predictions),7)
testthat::expect_equal(as.character(diffs$predictions$Variety[1]),"Victory")
testthat::expect_equal(length(attributes(diffs)),11)
testthat::expect_true(is.null(attr(diffs, which = "sortOrder")))
testthat::expect_silent(plotPredictions(data = diffs$predictions,
classify ="Nitrogen:Variety",
y = "predicted.value",
error.intervals = "StandardError",
y.title = attr(diffs,
which = "response.title")))
#TestPlot with sort
testthat::expect_silent(plotPvalues(diffs, gridspacing = 3,
sortFactor = "Variety", decreasing = TRUE))
#Test for sort.alldiffs
diffs.sort <- sort(diffs, sortFactor = "Variety", decreasing = TRUE)
testthat::expect_equal(as.character(diffs.sort$predictions$Variety[1]),"Marvellous")
testthat::expect_equal(rownames(diffs.sort$differences)[1],"0,Marvellous")
testthat::expect_equal(colnames(diffs.sort$p.differences)[1],"0,Marvellous")
testthat::expect_silent(plotPvalues(diffs.sort, gridspacing = 3))
diffs.LSD <- redoErrorIntervals(diffs, error.intervals = "halfLeast", LSDtype = "factor", LSDby = "Variety")
diffs.LSD.sort <- sort(diffs.LSD, sortFactor = "Variety", decreasing = TRUE)
#Test for sort.predictions.frame
preds <- diffs$predictions
preds.sort <- sort.predictions.frame(preds, classify = "Nitrogen:Variety", sortFactor = "Variety", decreasing = TRUE)
testthat::expect_equal(as.character(preds.sort$Variety[1]),"Marvellous")
#Test for predictPresent
mx.asr <- asreml(Yield ~ xNitrogen*Variety,
random=~Blocks/Wplots,
data=Oats.dat)
testthat::expect_equal(length(mx.asr$vparameters),3)
current.asrt <- as.asrtests(mx.asr)
print(current.asrt)
diffs <- predictPresent(mx.asr, terms = "xNitrogen:Variety",
x.num = "xNitrogen", x.fac = "Nitrogen",
x.pred.values = sort(unique(Oats.dat$xNitrogen)),
wald.tab = current.asrt$wald.tab,
error.intervals = "Stand", tables = "none",
sortFactor = "Variety", decreasing = TRUE)
testthat::expect_is(diffs[[1]], "alldiffs")
testthat::expect_equal(nrow(diffs[[1]]$predictions),12)
testthat::expect_equal(ncol(diffs[[1]]$predictions),7)
testthat::expect_equal(as.character(diffs[[1]]$predictions$Variety[[1]]),"Marvellous")
testthat::expect_equal(length(attributes(diffs$xNitrogen.Variety)),13)
testthat::expect_equal(length(attr(diffs[[1]], which = "sortOrder")),3)
#Test for predictPlus with sortFactor
diffs <- predictPlus(mx.asr, classify = "xNitrogen:Variety",
x.num = "xNitrogen", x.fac = "Nitrogen",
x.pred.values = sort(unique(Oats.dat$xNitrogen)),
wald.tab = current.asrt$wald.tab,
error.intervals = "Stand", tables = "none",
sortFactor = "Variety", decreasing = TRUE)
testthat::expect_is(diffs, "alldiffs")
testthat::expect_equal(nrow(diffs$predictions),12)
testthat::expect_equal(ncol(diffs$predictions),7)
testthat::expect_equal(as.character(diffs$predictions$Variety[1]),"Marvellous")
testthat::expect_equal(length(attributes(diffs)),13)
testthat::expect_true(all(attr(diffs, which = "sortOrder") ==
levels(diffs$predictions$Variety)))
testthat::expect_true(all(attr(diffs, which = "sortOrder") ==
c("Marvellous","Golden Rain", "Victory")))
testthat::expect_silent(plotPredictions(data = diffs$predictions,
classify ="xNitrogen:Variety",
x.num = "xNitrogen", x.fac = "Nitrogen",
y = "predicted.value",
error.intervals = "StandardError",
y.title = attr(diffs,
which = "response.title")))
testthat::expect_silent(plotPvalues(diffs, gridspacing = 3))
})
cat("#### Test for sort in standard order for classify on Oats with asreml42\n")
test_that("classify.sort42", {
skip_if_not_installed("asreml")
skip_on_cran()
library(asreml)
library(asremlPlus)
library(dae)
data(Oats.dat)
m1.asr <- asreml(Yield ~ Nitrogen*Variety,
random=~Blocks/Wplots,
data=Oats.dat)
testthat::expect_equal(length(m1.asr$vparameters),3)
current.asrt <- as.asrtests(m1.asr)
#Test for as.alldiffs
Var.pred <- predict(m1.asr, classify="Variety:Nitrogen",
sed=TRUE)
wald.tab <- current.asrt$wald.tab
den.df <- wald.tab[match("Variety", rownames(wald.tab)), "denDF"]
Var.diffs <- as.alldiffs(predictions = Var.pred$pvals,
sed = Var.pred$sed,
tdf = den.df)
testthat::expect_equal(length(attributes(Var.diffs)),4)
testthat::expect_true(is.null(attr(Var.diffs, which = "sortOrder")))
testthat::expect_true(all(names(Var.diffs$predictions)[1:2] == c("Variety","Nitrogen")))
#Test for allDifferences without sortFactor
Var.diffs <- allDifferences(predictions = Var.pred$pvals,
classify = "Variety:Nitrogen",
sed = Var.pred$sed, tdf = den.df)
testthat::expect_true(all(names(Var.diffs$predictions)[1:2] == c("Variety","Nitrogen")))
testthat::expect_equal(as.character(Var.diffs$predictions$Variety[1]),"Victory")
#TestPlot with sort
testthat::expect_silent(plotPvalues(Var.diffs, gridspacing = 4))
#Test for allDifferences with sortFactor
Var.diffs <- allDifferences(predictions = Var.pred$pvals,
classify = "Variety:Nitrogen",
sed = Var.pred$sed, tdf = den.df,
sortFactor = "Variety", decreasing = TRUE)
testthat::expect_true(all(names(Var.diffs$predictions)[1:2] == c("Variety","Nitrogen")))
testthat::expect_equal(as.character(Var.diffs$predictions$Variety[1]),"Marvellous")
testthat::expect_equal(length(attr(Var.diffs, which = "sortOrder")),3)
#TestPlot with sort
testthat::expect_silent(plotPvalues(Var.diffs, gridspacing = 3,
sortFactor = "Variety", decreasing = TRUE))
#Test for sort.alldiffs
diffs <- allDifferences(predictions = Var.pred$pvals,
classify = "Variety:Nitrogen",
sed = Var.pred$sed, tdf = den.df)
diffs.sort <- sort(diffs, sortFactor = "Variety", decreasing = TRUE)
testthat::expect_equal(as.character(diffs.sort$predictions$Variety[1]),"Marvellous")
testthat::expect_silent(plotPvalues(diffs.sort, gridspacing = 3))
})
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