library(GGIR)
context("g.part5.classifyNaps")
test_that("is able to classifyNaps", {
starttimes = c("2020-04-04 10:15:00", "2020-04-04 12:00:00",
"2020-04-04 12:18:00", "2020-04-04 19:39:00")
endtimes = c("2020-04-04 10:40:00", "2020-04-04 12:16:00",
"2020-04-04 12:47:00", "2020-04-04 19:59:00")
sibreport = data.frame(ID = 1:4, type = rep("sib", 4),
start = starttimes,
end = endtimes,
mean_acc_1min_before = c(2, 2, 100, 100), mean_acc_1min_after = c(2, 2, 100, 100))
sibreport$start = as.POSIXct(sibreport$start)
sibreport$end = as.POSIXct(sibreport$end)
sibreport$duration = sibreport$end - sibreport$start
classifiedNAPS = g.part5.classifyNaps(sibreport = sibreport, desiredtz = "",
possible_nap_window = c(9, 18),
possible_nap_dur = c(15, 240),
nap_model = "hip3yr", HASIB.algo = "vanHees2015")
expect_equal(nrow(classifiedNAPS), 2)
expect_equal(ncol(classifiedNAPS), 12)
expect_equal(classifiedNAPS$probability_nap, c(1, 0))
expect_equal(classifiedNAPS$mean_acc_1min_after, c(2, 100))
expect_equal(classifiedNAPS$mean_acc_1min_before, c(2, 2))
expect_equal(classifiedNAPS$gap2next, c(4800, 120))
})
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