Nothing
tests/testthat/test-visualizeDesign.R
In ExploreModelMatrix: Graphical Exploration of Design Matrices
context("VisualizeDesign")
test_that("VisualizeDesign fails with incorrect inputs", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
designFormula <- ~genotype
expect_error(VisualizeDesign(sampleData = 0,
designFormula = designFormula,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = as.matrix(sampleData),
designFormula = designFormula,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = as.list(sampleData),
designFormula = designFormula,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = TRUE,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = "genotype",
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = "~genotyp",
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotyp,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype|treatment,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = 1, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = "TRUE", textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = c(TRUE, FALSE), textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordCoocc = 1, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordCoocc = "TRUE", textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordCoocc = c(TRUE, FALSE), textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = c(1, 2),
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = "1",
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = TRUE,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeCoocc = c(1, 2),
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeCoocc = "1",
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeCoocc = TRUE,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = c(1, 2), lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = "1", lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = TRUE, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsCoocc = c(1, 2), lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsCoocc = "1", lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsCoocc = TRUE, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = c(1, 2),
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = "5",
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = TRUE,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = 1))
expect_warning(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = "nonexistent"))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL, colorPaletteFitted = "string"))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = model.matrix(~genotype,
data = sampleData)))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = data.frame(
model.matrix(~genotype,
data = sampleData))))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = model.matrix(
~genotype,
data = sampleData)[1:5, ]))
})
test_that("VisualizeDesign works with intercept", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 2L)
expect_equivalent(res0$designmatrix[, "(Intercept)"], rep(1L, 8L))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equal(res$value[res$genotype == "A"], "(Intercept)")
expect_equal(res$value[res$genotype == "B"], "(Intercept) + genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 3L)
expect_equivalent(res0$designmatrix[, "(Intercept)"], rep(1L, 8L))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equivalent(res0$designmatrix[, "treatmenttrt"], rep(c(1L, 0L), 4))
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"(Intercept) + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"(Intercept)")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"(Intercept) + genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"(Intercept) + genotypeB")
## Check that dropCols = NULL and dropCols = c() give the same results
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment,
dropCols = NULL)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment,
dropCols = c())
expect_equal(res1, res2)
})
test_that("VisualizeDesign works without intercept", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 2L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equal(res$value[res$genotype == "A"], "genotypeA")
expect_equal(res$value[res$genotype == "B"], "genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 3L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equivalent(res0$designmatrix[, "treatmenttrt"], rep(c(1L, 0L), 4))
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"genotypeA + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"genotypeA")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"genotypeB")
## Check that dropCols = NULL and dropCols = c() give the same results
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = NULL)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = c())
expect_equal(res1, res2)
})
test_that("VisualizeDesign works with DataFrame input", {
sampleData <- S4Vectors::DataFrame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4)
)
res <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype)$sampledata
expect_equal(res$value[res$genotype == "A"], "genotypeA")
expect_equal(res$value[res$genotype == "B"], "genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment)$sampledata
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"genotypeA + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"genotypeA")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"genotypeB")
## Check that dropCols = NULL and dropCols = c() give the same results
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = NULL)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = c())
expect_equal(res1, res2)
## Check that flipCoordFitted = TRUE/FALSE give same results except for the plot
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
flipCoordFitted = TRUE)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
flipCoordFitted = FALSE)
for (nm in names(res1)) {
if (nm != "plotlist") {
expect_equal(res1[[nm]], res2[[nm]])
}
}
})
test_that("VisualizeDesign works with design matrix input", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData %>% dplyr::select(genotype),
designFormula = NULL,
designMatrix = model.matrix(
~0 + genotype,
data = sampleData))
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 2L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equal(res$value[res$genotype == "A"], "genotypeA")
expect_equal(res$value[res$genotype == "B"], "genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
designMatrix = model.matrix(
~0 + genotype + treatment,
data = sampleData))
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 3L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equivalent(res0$designmatrix[, "treatmenttrt"], rep(c(1L, 0L), 4))
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"genotypeA + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"genotypeA")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"genotypeB")
})
test_that("VisualizeDesign works with three predictors", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
pred3 = rep(rep(paste0("C", 1:2), each = 2), 2),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment + pred3)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 4L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 4L)
expect_equivalent(res0$designmatrix[, "(Intercept)"], rep(1L, 8L))
expect_equivalent(res0$designmatrix[, "genotypeB"],
as.integer(sampleData$genotype == "B"))
expect_equivalent(res0$designmatrix[, "treatmenttrt"],
as.integer(sampleData$treatment == "trt"))
expect_equivalent(res0$designmatrix[, "pred3C2"],
as.integer(sampleData$pred3 == "C2"))
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl" &
res$pred3 == "C1"], "(Intercept)")
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt" &
res$pred3 == "C1"], "(Intercept) + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl" &
res$pred3 == "C2"], "(Intercept) + pred3C2")
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt" &
res$pred3 == "C2"], "(Intercept) + treatmenttrt + pred3C2")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl" &
res$pred3 == "C1"], "(Intercept) + genotypeB")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt" &
res$pred3 == "C1"], "(Intercept) + genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl" &
res$pred3 == "C2"], "(Intercept) + genotypeB + pred3C2")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt" &
res$pred3 == "C2"], "(Intercept) + genotypeB + treatmenttrt + pred3C2")
expect_equal(nrow(res), 8L)
expect_equal(colnames(res), c("genotype", "treatment", "pred3", "value", "nSamples"))
})
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context("VisualizeDesign")
test_that("VisualizeDesign fails with incorrect inputs", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
designFormula <- ~genotype
expect_error(VisualizeDesign(sampleData = 0,
designFormula = designFormula,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = as.matrix(sampleData),
designFormula = designFormula,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = as.list(sampleData),
designFormula = designFormula,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = TRUE,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = "genotype",
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = "~genotyp",
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotyp,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype|treatment,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = 1, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = "TRUE", textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = c(TRUE, FALSE), textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordCoocc = 1, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordCoocc = "TRUE", textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordCoocc = c(TRUE, FALSE), textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = c(1, 2),
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = "1",
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = TRUE,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeCoocc = c(1, 2),
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeCoocc = "1",
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeCoocc = TRUE,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = c(1, 2), lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = "1", lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = TRUE, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsCoocc = c(1, 2), lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsCoocc = "1", lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsCoocc = TRUE, lineWidthFitted = 25,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = c(1, 2),
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = "5",
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = TRUE,
dropCols = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = 1))
expect_warning(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = "nonexistent"))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL, colorPaletteFitted = "string"))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = model.matrix(~genotype,
data = sampleData)))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = NULL))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = data.frame(
model.matrix(~genotype,
data = sampleData))))
expect_error(VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
flipCoordFitted = FALSE, textSizeFitted = 5,
textSizeLabsFitted = 12, lineWidthFitted = 25,
dropCols = NULL,
designMatrix = model.matrix(
~genotype,
data = sampleData)[1:5, ]))
})
test_that("VisualizeDesign works with intercept", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 2L)
expect_equivalent(res0$designmatrix[, "(Intercept)"], rep(1L, 8L))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equal(res$value[res$genotype == "A"], "(Intercept)")
expect_equal(res$value[res$genotype == "B"], "(Intercept) + genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 3L)
expect_equivalent(res0$designmatrix[, "(Intercept)"], rep(1L, 8L))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equivalent(res0$designmatrix[, "treatmenttrt"], rep(c(1L, 0L), 4))
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"(Intercept) + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"(Intercept)")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"(Intercept) + genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"(Intercept) + genotypeB")
## Check that dropCols = NULL and dropCols = c() give the same results
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment,
dropCols = NULL)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment,
dropCols = c())
expect_equal(res1, res2)
})
test_that("VisualizeDesign works without intercept", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 2L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equal(res$value[res$genotype == "A"], "genotypeA")
expect_equal(res$value[res$genotype == "B"], "genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 3L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equivalent(res0$designmatrix[, "treatmenttrt"], rep(c(1L, 0L), 4))
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"genotypeA + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"genotypeA")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"genotypeB")
## Check that dropCols = NULL and dropCols = c() give the same results
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = NULL)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = c())
expect_equal(res1, res2)
})
test_that("VisualizeDesign works with DataFrame input", {
sampleData <- S4Vectors::DataFrame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4)
)
res <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype)$sampledata
expect_equal(res$value[res$genotype == "A"], "genotypeA")
expect_equal(res$value[res$genotype == "B"], "genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment)$sampledata
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"genotypeA + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"genotypeA")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"genotypeB")
## Check that dropCols = NULL and dropCols = c() give the same results
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = NULL)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
dropCols = c())
expect_equal(res1, res2)
## Check that flipCoordFitted = TRUE/FALSE give same results except for the plot
res1 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
flipCoordFitted = TRUE)
res2 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~0 + genotype + treatment,
flipCoordFitted = FALSE)
for (nm in names(res1)) {
if (nm != "plotlist") {
expect_equal(res1[[nm]], res2[[nm]])
}
}
})
test_that("VisualizeDesign works with design matrix input", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData %>% dplyr::select(genotype),
designFormula = NULL,
designMatrix = model.matrix(
~0 + genotype,
data = sampleData))
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 2L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equal(res$value[res$genotype == "A"], "genotypeA")
expect_equal(res$value[res$genotype == "B"], "genotypeB")
expect_equal(nrow(res), 2L)
expect_equal(colnames(res), c("genotype", "value", "nSamples"))
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = NULL,
designMatrix = model.matrix(
~0 + genotype + treatment,
data = sampleData))
res <- res0$sampledata
expect_equal(res0$totnbrrows, 2L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 3L)
expect_equivalent(res0$designmatrix[, "genotypeA"], rep(c(1L, 0L), each = 4))
expect_equivalent(res0$designmatrix[, "genotypeB"], rep(c(0L, 1L), each = 4))
expect_equivalent(res0$designmatrix[, "treatmenttrt"], rep(c(1L, 0L), 4))
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt"],
"genotypeA + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl"],
"genotypeA")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt"],
"genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl"],
"genotypeB")
})
test_that("VisualizeDesign works with three predictors", {
sampleData <- data.frame(
genotype = rep(c("A", "B"), each = 4),
treatment = rep(c("trt", "ctrl"), 4),
pred3 = rep(rep(paste0("C", 1:2), each = 2), 2),
stringsAsFactors = FALSE
)
res0 <- VisualizeDesign(sampleData = sampleData,
designFormula = ~genotype + treatment + pred3)
res <- res0$sampledata
expect_equal(res0$totnbrrows, 4L)
expect_equal(nrow(res0$designmatrix), 8L)
expect_equal(ncol(res0$designmatrix), 4L)
expect_equivalent(res0$designmatrix[, "(Intercept)"], rep(1L, 8L))
expect_equivalent(res0$designmatrix[, "genotypeB"],
as.integer(sampleData$genotype == "B"))
expect_equivalent(res0$designmatrix[, "treatmenttrt"],
as.integer(sampleData$treatment == "trt"))
expect_equivalent(res0$designmatrix[, "pred3C2"],
as.integer(sampleData$pred3 == "C2"))
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl" &
res$pred3 == "C1"], "(Intercept)")
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt" &
res$pred3 == "C1"], "(Intercept) + treatmenttrt")
expect_equal(res$value[res$genotype == "A" & res$treatment == "ctrl" &
res$pred3 == "C2"], "(Intercept) + pred3C2")
expect_equal(res$value[res$genotype == "A" & res$treatment == "trt" &
res$pred3 == "C2"], "(Intercept) + treatmenttrt + pred3C2")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl" &
res$pred3 == "C1"], "(Intercept) + genotypeB")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt" &
res$pred3 == "C1"], "(Intercept) + genotypeB + treatmenttrt")
expect_equal(res$value[res$genotype == "B" & res$treatment == "ctrl" &
res$pred3 == "C2"], "(Intercept) + genotypeB + pred3C2")
expect_equal(res$value[res$genotype == "B" & res$treatment == "trt" &
res$pred3 == "C2"], "(Intercept) + genotypeB + treatmenttrt + pred3C2")
expect_equal(nrow(res), 8L)
expect_equal(colnames(res), c("genotype", "treatment", "pred3", "value", "nSamples"))
})
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