tests/testthat/test_tidiers_hw.R

In business-science/sweep: Tidy Tools for Forecasting

# FUNCTION: sw_*.HoltWinters -----
test_that("sw_*.HoltWinters test returns tibble with correct rows and columns.", {

    # HoltWinters()  ----
    fit_hw <- USAccDeaths %>%
        HoltWinters()

    # sw_tidy ----
    test <- sw_tidy(fit_hw)
    expect_s3_class(test, "tbl")
    expect_equal(nrow(test), 17)
    expect_equal(ncol(test), 2)

    # sw_glance ----
    test <- sw_glance(fit_hw)
    expect_s3_class(test, "tbl")
    expect_equal(nrow(test), 1)
    expect_equal(ncol(test), 12)

    # sw_augment ----
    # Test normal
    test <- sw_augment(fit_hw, rename_index = "date")
    expect_s3_class(test, "tbl")
    expect_equal(nrow(test), 72)
    expect_equal(ncol(test), 4)

    # Test passing data
    test <- sw_augment(fit_hw, data = USAccDeaths, rename_index = "date")
    expect_s3_class(test, "tbl")
    expect_equal(nrow(test), 72)
    expect_equal(ncol(test), 4)

    # Test passing incorrect data
    expect_warning(sw_augment(fit_hw,
                              data = timetk::tk_ts(USAccDeaths[1:50], frequency = 12, start = 1973),
                              rename_index = "date")
    )

    # sw_tidy_decomp ----
    test <- sw_tidy_decomp(fit_hw)
    expect_s3_class(test, "tbl")
    expect_equal(nrow(test), 72)
    expect_equal(ncol(test), 6)


    # timetk index tests -----

    # Check warning if no timetk index exists
    expect_warning(
        USAccDeaths %>%
            stats::HoltWinters() %>%
            sw_augment(timetk_idx = TRUE)
    )

    # Check integration with tk_make_future_timeseries()
    monthly_bike_sales <- bike_sales %>%
        dplyr::mutate(month.date = lubridate::as_date(zoo::as.yearmon(order.date))) %>%
        dplyr::group_by(month.date) %>%
        dplyr::summarize(total.daily.sales = sum(price.ext))

    monthly_bike_sales_ts <- tk_ts(monthly_bike_sales, start = 2011, freq = 12, silent = TRUE)

    fit <- stats::HoltWinters(monthly_bike_sales_ts)

    # timetk_idx sw_augment ----
    test <- fit %>% sw_augment()
    expect_s3_class(test$index, "yearmon")

    test <- fit %>% sw_augment(timetk_idx = TRUE)
    expect_s3_class(test$index, "Date")

    # timetk_idx sw_tidy_decomp -----
    test <- fit %>% sw_tidy_decomp()
    expect_s3_class(test$index, "yearmon")

    test <- fit %>% sw_tidy_decomp(timetk_idx = TRUE)
    expect_s3_class(test$index, "Date")

})