Nothing
## Test unit 'maximize'
library(svUnit)
###############################################################
# The new two functions are to set up the unit test environment
###############################################################
.setUp <-
function () {
## Specific actions for svUnit: prepare context
if ("package:svUnit" %in% search()) {
.Log <- Log() ## Make sure .Log is created
.Log$..Unit <- "inst/unitTests/runit_maximize.R"
.Log$..File <- ""
.Log$..Obj <- ""
.Log$..Tag <- ""
.Log$..Msg <- ""
rm(..Test, envir = .Log)
}
# Sets threads to 2 or less. This is a CRAN requirement.
if(.Call(likeLTD::.cpp.nbthreads) > 2) {
nb_threads_in_test = .Call(likeLTD::.cpp.nbthreads)
.Call(likeLTD::.cpp.set_nbthreads, as.integer(2))
}
}
.tearDown <-
function () {
## Specific actions for svUnit: clean up context
if ("package:svUnit" %in% search()) {
.Log$..Unit <- ""
.Log$..File <- ""
.Log$..Obj <- ""
.Log$..Tag <- ""
.Log$..Msg <- ""
rm(..Test, envir = .Log)
}
# Reset number of threads to what it was.
if('nb_threads_in_test' %in% ls()) {
.Call(likeLTD::.cpp.set_nbthreads, as.integer(nb_threads_in_test))
rm(nb_threads_in_test)
}
}
###############################################################
# Then data functions
###############################################################
ref.data.path <- function() {
path = Reduce(file.path, c("extdata", "hammer", "hammer-reference.csv"))
system.file(path, package="likeLTD")
}
csp.data.path <- function() {
path = Reduce(file.path, c("extdata", "hammer", "hammer-CSP.csv"))
system.file(path, package="likeLTD")
}
###################################
# Finally, the unit-test themselves
###################################
test_estimates <- svTest(function() {
cspProfile = read.csp.profile(csp.data.path())
knownProfiles = read.known.profiles(ref.data.path())
if(! "estimates" %in% ls(.GlobalEnv))
estimates <- getFromNamespace("estimates", "likeLTD")
checkEquals(array(c(0.575, 0.500)),
estimates(knownProfiles[1, ], cspProfile))
checkEquals(array(c(0.625, 0.500)),
estimates(knownProfiles[2, ], cspProfile))
checkEquals(array(c(0.750, 0.675)),
estimates(knownProfiles[3, ], cspProfile))
})
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