Nothing
test_that("deseason behaviour", {
spp_data <- matrix(nrow = 5*12, ncol = 5)
seasonal_cycle <- 20*sin(2*pi*(1:5*12)/12)
spp_data <- sapply(1:dim(spp_data)[2], function(x){
spp_data[,x] <- ts(rnorm(5*12,mean = 20, sd = 3) + seasonal_cycle, freq = 12, start = c(2000, 1)) #add seasonal cycle to random noise
})
test.data <- cbind("time" = base::seq(base::as.Date('2000/01/01'),
base::as.Date('2004/12/01'), by = "month"),
as.data.frame(spp_data))
eg.deseason1 <- deseason_ts(test.data, increment = "month", method = "average", order = "ymd")
eg.deseason2 <- deseason_ts(test.data, increment = "month",method = "stl", order = "ymd")
eg.deseason3 <- deseason_ts(test.data, increment = "month", method = "decompose", order = "ymd")
expect_equal(dim(eg.deseason1),dim(test.data))
expect_equal(dim(eg.deseason2),dim(test.data))
expect_equal(dim(eg.deseason3),dim(test.data))
expect_false(any(is.na(eg.deseason1)))
expect_false(any(is.na(eg.deseason2)))
expect_true(all(is.na(head(eg.deseason3[,-1])) & is.na(head(eg.deseason3[,-1])) & !all(is.na(eg.deseason3[10:16,-1]))))
expect_error(deseason_ts(test.data[,1], method = "average"))
expect_error(deseason_ts(test.data, increment = "month", method = "average"))
expect_error(deseason_ts(test.data, method = "average", order = "ym"))
})
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