inittime <- Sys.time()
cat(paste("\n Starting test.flfast-additional.R test at", date()))
date()
test_that("Issue warnings and messages", {
df1 <- data.frame(Genotype = c("A", "B, C"), Fitness = c(1.3, 2),
stringsAsFactors = FALSE)
expect_warning(OncoSimulR:::allGenotypes_to_matrix(df1),
"No WT genotype. Setting its fitness to 1.", fixed = TRUE)
df2 <- data.frame(Genotype = c("WT", "A", "B, C"), Fitness = c(5, 1.3, 2))
expect_warning(OncoSimulR:::allGenotypes_to_matrix(df2),
"First column of genotype fitness is a factor.",
fixed = TRUE)
df1 <- data.frame(Genotype = c("A", "B, C"), Fitness = c(1.3, 2),
stringsAsFactors = FALSE)
expect_warning(OncoSimulR:::to_genotFitness_std(df1),
"No WT genotype. Setting its fitness to 1.", fixed = TRUE)
df2 <- data.frame(Genotype = c("WT", "A", "B, C"), Fitness = c(5, 1.3, 2))
expect_warning(OncoSimulR:::to_genotFitness_std(df2),
"First column of genotype fitness is a factor.",
fixed = TRUE)
})
test_that("Equality of fitness including allFitnessEffects", {
df3 <- data.frame(Genotype = c("WT", "A", "B, C"), Fitness = c(1, 2, 0),
stringsAsFactors = FALSE)
m3 <- rbind(c(0, 0, 0, 1), c(1, 0, 0, 2.0))
colnames(m3) <- c("A", "B", "C", "Fitness")
m4 <- rbind(c(0, 0, 0, 1), c(1, 0, 0, 2.0), c(0, 1, 1, 0))
colnames(m4) <- c("A", "B", "C", "Fitness")
## yes, m3 and m3 missing the attributes
expect_equivalent(OncoSimulR:::to_genotFitness_std(df3), m3)
expect_equivalent(OncoSimulR:::to_genotFitness_std(df3, simplify = FALSE), m4)
## now, scale by fitness of WT
df3 <- data.frame(Genotype = c("WT", "A", "B, C"),
Fitness = c(1.3, 2, 0),
stringsAsFactors = FALSE)
m3 <- rbind(c(0, 0, 0, 1.3), c(1, 0, 0, 2.0))
colnames(m3) <- c("A", "B", "C", "Fitness")
m3[, "Fitness"] <- m3[, "Fitness"]/1.3
m4 <- rbind(c(0, 0, 0, 1.3), c(1, 0, 0, 2.0), c(0, 1, 1, 0))
colnames(m4) <- c("A", "B", "C", "Fitness")
m4[, "Fitness"] <- m4[, "Fitness"]/1.3
expect_equivalent(OncoSimulR:::to_genotFitness_std(df3), m3)
expect_equivalent(OncoSimulR:::to_genotFitness_std(df3, simplify = FALSE), m4)
for(i in 1:10) {
rxx <- rfitness(7)
expect_equal(
allFitnessEffects(genotFitness = rxx)$fitnessLandscape,
OncoSimulR:::to_genotFitness_std(rxx))
}
for(i in 1:10) {
ng <- 7
rxx <- rfitness(ng)
cnn <-
replicate(ng,
paste(sample(c(LETTERS,
letters,
0:9), 5, replace = TRUE),
collapse = ""))
if(any(duplicated(cnn))) cnn <- LETTERS[1:ng]
colnames(rxx)[1:ng] <- cnn
fex <- allFitnessEffects(genotFitness = rxx)
gn <- OncoSimulR:::allNamedGenes(fex)
m1x <- data.frame(Gene = gtools::mixedsort(cnn),
GeneNumID = 1:ng,
stringsAsFactors = FALSE)
expect_identical(m1x, gn)
}
})
test_that("drv names OK", {
rxx <- rfitness(5)
expect_silent(allFitnessEffects(genotFitness = rxx, drvNames = LETTERS[1:4]))
})
## Make sure warning if using Bozic
test_that("Bozic and fitness landscape spec", {
rxx <- rfitness(7)
expect_warning(oncoSimulIndiv(
allFitnessEffects(genotFitness = rxx),
model = "Bozic", initSize = 5000,
onlyCancer = FALSE,
finalTime = 10,
verbosity = 0),
"Bozic model passing a fitness landscape will not work for now",
fixed = TRUE)
rm(rxx)
})
test_that("fitness evaluation what we expect", {
for(i in 1:10) {
rxx <- rfitness(5)
## allFitnessEffects(genotFitness = rxx)
eag <- evalAllGenotypes(allFitnessEffects(genotFitness = rxx),
addwt = TRUE)
rxxf <- rxx[, "Fitness"]
rxxf[rxxf <= 1e-09] <- 0
expect_equal(rxxf, eag[, "Fitness"])
}
})
## rxx <- rfitness(7)
## simul1 <- oncoSimulIndiv(allFitnessEffects(genotFitness = rxx,
## drvNames = LETTERS[1:7]),
## model = "Exp", initSize = 5000,
## onlyCancer = FALSE,
## finalTime = 1000,
## verbosity = 0)
## summary(simul1)
test_that("rt and fl specifications are the same", {
## We test that passing a DAG as a DAG of restrictions or as its
## fitness landscape give identical output
## This subsumes taking an rT, converting to fitness landscape, and
## verifying we get same fitnesses
## n: number of genes
dag_fitness <- function(n) {
s1min <- 0.1
s1max <- 0.7
dummys1 <- 0.5 ## to put something below, to begin with
rt <- simOGraph(n, out ="rT", geneNames = LETTERS[1:n],
s = dummys1, sh = -99)
## nparents = sample(2:5, 1),
## h = sample(2:5, 1))
## Make sure we get variation
uc <- unique(rt$child)
s1v <- runif(uc, s1min, s1max)
names(s1v) <- uc
rt$s <- s1v[rt$child]
rtf <- evalAllGenotypes(allFitnessEffects(rt), addwt = TRUE)
fl <- OncoSimulR:::allGenotypes_to_matrix(rtf)
fl[fl[, "Fitness"] == 0, "Fitness"] <- 1e-9
return(list(rt = rt, fl = fl))
}
tests <- 10
ng <- 7
for(i in 1:tests) {
rtfl <- dag_fitness(ng)
is <- round(runif(1) * 100)
set.seed(is)
s1 <- oncoSimulIndiv(allFitnessEffects(rtfl$rt))
set.seed(is)
s2 <- oncoSimulIndiv(allFitnessEffects(genotFitness = rtfl$fl))
expect_identical(s1$pops.by.time, s2$pops.by.time)
print(summary(s1))
expect_identical(s1[1:length(s1)], s2[1:length(s2)])
## they differ in the call attribute, of course
## adding a package for this is an overkill
## expect_true(compare::compare(s1, s2, ignoreAttrs = TRUE)$result)
}
})
## FIXME: some tests with mutator, etc?
## NOTE the BREAKING changes!!! missing genotypes set to 0
## ## catching the label bug
## I was getting weird genotypes labels
## o3 <- allFitnessEffects(orderEffects = c(
## "M > D > F" = 0.99,
## "D > M > F" = 0.2,
## "D > M" = 0.1,
## "M > D" = 0.9),
## noIntGenes = c("u" = 0.01, "z" = 0.01, "w" = 0.02),
## geneToModule =
## c("Root" = "Root",
## "M" = "m",
## "F" = "f",
## "D" = "d") )
## tmp <- oncoSimulIndiv(o3, model = "McFL",
## mu = 5e-5, finalTime = 500,
## detectionDrivers = 3,
## sampleEvery = 0.03,
## keepEvery = 1,
## onlyCancer = FALSE,
## initSize = 1000,
## keepPhylog = TRUE
## , initMutant = c("d > m > w")
## )
## tmp$GenotypesLabels
## set.seed(1)
## rxx <- rfitness(5)
## rxx[2, 6] <- 2
## simul1 <- oncoSimulIndiv(allFitnessEffects(genotFitness = rxx,
## drvNames = LETTERS[1:5]),
## model = "Exp", initSize = 5000,
## onlyCancer = FALSE,
## finalTime = 300,
## verbosity = 3)
## summary(simul1)
## set.seed(1)
## rxx <- rfitness(5)
## rxx[2, 6] <- 2
## simul1 <- oncoSimulIndiv(allFitnessEffects(genotFitness = rxx,
## drvNames = LETTERS[1:5]),
## model = "Exp", initSize = 5000,
## onlyCancer = FALSE,
## finalTime = 1000,
## verbosity = 0)
## summary(simul1)
## rtfl <- dag_fitness(5)
## set.seed(2)
## s1 <- oncoSimulIndiv(allFitnessEffects(rtfl$rt))
## set.seed(2)
## s2 <- oncoSimulIndiv(allFitnessEffects(genotFitness = rtfl$fl))
## summary(s1)
## summary(s2)
## I think this is already tested
## rxx <- rfitness(3)
## allFitnessEffects(genotFitness = rxx,
## geneToModule = c("Root" = "Root",
## "A" = "a1, a2",
## "B" = "b1",
## "C" = "c1"))
cat(paste("\n Ending test.flfast-additional.R test at", date(), "\n"))
cat(paste(" Took ", round(difftime(Sys.time(), inittime, units = "secs"), 2), "\n\n"))
rm(inittime)
