# Prepare function input:
data(hdacTR_smallExample)
tpptrData <- suppressMessages(
tpptrImport(configTable = hdacTR_config, data = hdacTR_data)
)
testData <- tpptrTidyUpESets(tpptrData, returnType = "exprs") %>%
filter(uniqueID %in% c("HDAC1", "HDAC2", "HDAC9", "CBR3"))
splineFits <- suppressMessages(
tpptrFitSplines(data = testData, factorsH1 = "condition", returnModels = TRUE,
splineDF = 3:7, nCores = 1)
)
splineFits2 <- suppressMessages(
tpptrFitSplines(data = testData,
factorsH1 = c("condition", "replicate"),
factorsH0 = c("replicate"),
returnModels = TRUE,
splineDF = 3:7, nCores = 1)
)
test_that(desc="allOk_returnPlots", code={
datIn <- testData
fitsIn <- splineFits
plots <- TPP:::plotIndividual(data = datIn,
fittedModels = fitsIn,
plotAnnotation = NULL,
plotDir = NULL,
filePrefix = NULL,
returnPlots = TRUE,
nCores = 1)
check1 <- nrow(plots) == length(unique(fitsIn$uniqueID))
check2 <- all(plots$uniqueID == unique(fitsIn$uniqueID))
check3 <- all(sapply(plots$plot, function(p) inherits(p,"ggplot")))
check4 <- all(colnames(plots) == c("uniqueID", "plot"))
expect_true(check1 & check2 & check3 & check4)
})
test_that(desc="allOk_printPlots", code={
datIn <- testData
fitsIn <- splineFits
paths <- TPP:::plotIndividual(data = datIn,
fittedModels = fitsIn,
plotAnnotation = NULL,
plotDir = getwd(),
filePrefix = "splineFit",
returnPlots = FALSE,
nCores = 1)
check1 <- nrow(paths) == length(unique(fitsIn$uniqueID))
check2 <- all(paths$uniqueID == unique(fitsIn$uniqueID))
check3 <- all(file.exists(paths$path))
check4 <- all(colnames(paths) == c("uniqueID", "path"))
unlink(file.path(getwd(), "Individual"), recursive = TRUE)
expect_true(check1 & check2 & check3 & check4)
})
test_that(desc="allOk_both", code={
datIn <- testData
fitsIn <- splineFits
both <- TPP:::plotIndividual(data = datIn,
fittedModels = fitsIn,
plotAnnotation = NULL,
plotDir = getwd(),
filePrefix = "splineFit",
returnPlots = TRUE,
nCores = 1)
check1 <- nrow(both) == length(unique(fitsIn$uniqueID))
check2 <- all(both$uniqueID == unique(fitsIn$uniqueID))
check3 <- all(sapply(both$plot, function(p) inherits(p,"ggplot")))
check4 <- all(file.exists(both$path))
check5 <- all(colnames(both) == c("uniqueID", "plot", "path"))
expect_true(check1 & check2 & check3 & check4 & check5)
unlink(file.path(getwd(), "Individual"), recursive = TRUE)
})
test_that(desc="allOk_both2", code={
datIn <- testData
fitsIn <- splineFits2
both <- TPP:::plotIndividual(data = datIn,
fittedModels = fitsIn,
plotAnnotation = NULL,
plotDir = getwd(),
filePrefix = "splineFit",
returnPlots = TRUE,
nCores = 1)
check1 <- nrow(both) == length(unique(fitsIn$uniqueID))
check2 <- all(both$uniqueID == unique(fitsIn$uniqueID))
check3 <- all(sapply(both$plot, function(p) inherits(p,"ggplot")))
check4 <- all(file.exists(both$path))
check5 <- all(colnames(both) == c("uniqueID", "plot", "path"))
expect_true(check1 & check2 & check3 & check4 & check5)
unlink(file.path(getwd(), "Individual"), recursive = TRUE)
})
test_that(desc="noData", code={
datIn <- testData %>% filter(uniqueID == "CBR3")
fitsIn <- splineFits
plots <- TPP:::plotIndividual(data = datIn,
fittedModels = fitsIn,
plotAnnotation = NULL,
plotDir = NULL,
filePrefix = NULL,
returnPlots = TRUE,
nCores = 1)
p <- plots$plot[[1]]
check1 <- nrow(plots) == 1
check2 <- inherits(p, "ggplot")
# Check if only the original data was added, not the failed predictions.
# Adding these would cause problems due to the missing color column 'condition'
# which is only added automatically when at least 1 successfull model fit was present:
check3 <- length(p$layers) == 1
expect_true(check1 & check2 & check3)
})
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