Nothing
test_that("POR functions", {
# test POR functions on HyMETT::example_annual and HyMETT::example_preproc daily datasets
# expect data.frames or numeric doubles returned
r <- POR_apply_annual_hiflow_stats(example_annual[ , c("high_q1", "high_q3")])
expect_s3_class(r, class = "data.frame")
expect_true(length(r) == 3)
expect_true(nrow(r) == 4)
r <- POR_apply_annual_lowflow_stats(example_annual[ , c("low_q1", "low_q3")])
expect_s3_class(r, class = "data.frame")
expect_true(length(r) == 3)
expect_true(nrow(r) == 4)
r <- POR_calc_amp_and_phase(data = example_preproc, Date = "Date", value = "value")
expect_s3_class(r, class = "data.frame")
expect_true(length(r) == 2)
expect_true(nrow(r) == 2)
r <- POR_calc_AR1(data = example_preproc, Date = "Date", value = "value")
expect_type(r, "double")
expect_vector(r, size = 1)
r <- POR_calc_lp3_quantile(example_annual[["low_q1"]], p = 0.1)
expect_type(r, "double")
expect_vector(r, size = 1)
r <- POR_deseasonalize(data = example_preproc, Date = "Date", value = "value")
expect_type(r, "double")
expect_vector(r, size = nrow(example_preproc))
r <- POR_distribution_metrics(example_preproc$value)
expect_s3_class(r, class = "data.frame")
expect_true(length(r) == 2)
expect_true(nrow(r) == 17)
})
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