tests/testthat/test-na_seadec.R

In imputeTS: Time Series Missing Value Imputation

context("na_seadec")

test_that("All NA vector throws error", {
  expect_error(na_seadec(c(NA, NA, NA, NA, NA)))
})

test_that("Correct results for all options with a modifed tsAirgap dataset (additionalNAs at end)", {
  skip_on_cran()
  # Using mean over resulting vector to check correctness
  # In order to avoid writing down the complete resulting vector
  # Using rounded version in order to avoid writing down all decimals
  x <- tsAirgap
  x[135:144] <- NA
  expect_equal(round(mean(na_seadec(x, algorithm = "interpolation")), digits = 1), 276.7)
  expect_equal(round(mean(na_seadec(x, algorithm = "locf")), digits = 1), 276.0)
  expect_equal(round(mean(na_seadec(x, algorithm = "mean")), digits = 1), 264.3)
  expect_true(round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima")), digits = 1) > 277 &
    round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima")), digits = 1) < 283)
  expect_equal(round(mean(na_seadec(x, algorithm = "ma")), digits = 1), 277.1)
})

test_that("Correct results for all options with a modifed tsAirgap dataset (additionalNAs at start)", {
  skip_on_cran()
  # Using mean over resulting vector to check correctness
  # In order to avoid writing down the complete resulting vector
  # Using rounded version in order to avoid writing down all decimals
  x <- tsAirgap
  x[1:5] <- NA
  expect_equal(round(mean(na_seadec(x, algorithm = "interpolation")), digits = 1), 279.9)
  expect_equal(round(mean(na_seadec(x, algorithm = "locf")), digits = 1), 279.2)
  expect_equal(round(mean(na_seadec(x, algorithm = "mean")), digits = 1), 284.1)
  expect_true(round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima")), digits = 1) > 282 &
    round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima")), digits = 1) < 288)
  expect_equal(round(mean(na_seadec(x, algorithm = "ma")), digits = 1), 280.0)
})

test_that("Given frequency is  overwritten by findFrequency=T", {
  x <- ts(data = c(1,1,99,99,1,1,99,99,1,NA,99,99,1,1,99,99,1,1,99,99,1,1,99,99,1,1), frequency = 12)
  imp <- na_seadec(x, find_frequency = TRUE) # new detected frequency = 4
  expect_equal(frequency(imp),4)
})

test_that("Correct results for all options with the tsAirgap dataset", {
  skip_on_cran()
  # Using mean over resulting vector to check correctness
  # In order to avoid writing down the complete resulting vector
  # Using rounded version in order to avoid writing down all decimals
  x <- tsAirgap
  expect_equal(round(mean(na_seadec(x, algorithm = "interpolation")), digits = 1), 280.4)
  expect_equal(round(mean(na_seadec(x, algorithm = "locf")), digits = 1), 279.7)
  expect_equal(round(mean(na_seadec(x, algorithm = "mean")), digits = 1), 279.5)
  expect_true(round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima")), digits = 1) > 277 &
    round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima")), digits = 1) < 283)
  expect_equal(round(mean(na_seadec(x, algorithm = "ma")), digits = 1), 280.6)
})

test_that("Imputation works for data.frame", {
  # Checking if NAs remain in data.frame
  x <- data.frame(tsAirgap, tsAirgap, tsAirgapComplete)
  expect_false(anyNA(na_seadec(x, algorithm = "interpolation")))
  expect_false(anyNA(na_seadec(x, algorithm = "locf")))
  expect_false(anyNA(na_seadec(x, algorithm = "mean")))
  expect_false(anyNA(na_seadec(x, algorithm = "random")))
  expect_false(anyNA(na_seadec(x, algorithm = "kalman")))
  expect_false(anyNA(na_seadec(x, algorithm = "ma")))
})


test_that("Warning for wrong input for algorithm parameter", {
  expect_error(na_seadec(tsAirgap, algorithm = "wrong"))
})



test_that("Test NA at beginning", {
  x <- tsAirgap
  x[1:2] <- NA
  expect_false(anyNA(na_seadec(x, algorithm = "interpolation")))
  expect_false(anyNA(na_seadec(x, algorithm = "kalman")))
  expect_false(anyNA(na_seadec(x, algorithm = "locf")))
  expect_false(anyNA(na_seadec(x, algorithm = "ma")))
  expect_false(anyNA(na_seadec(x, algorithm = "mean")))
  expect_false(anyNA(na_seadec(x, algorithm = "random")))
  expect_false(anyNA(na_seadec(x)))
})

test_that("Test NA at end", {
  x <- tsAirgap
  x[143:144] <- NA
  expect_false(anyNA(na_seadec(x, algorithm = "interpolation")))
  expect_false(anyNA(na_seadec(x, algorithm = "kalman")))
  expect_false(anyNA(na_seadec(x, algorithm = "locf")))
  expect_false(anyNA(na_seadec(x, algorithm = "ma")))
  expect_false(anyNA(na_seadec(x, algorithm = "mean")))
  expect_false(anyNA(na_seadec(x, algorithm = "random")))
  expect_false(anyNA(na_seadec(x)))
})

test_that("Multiple NAs in a row", {
  x <- tsAirgap
  x[40:80] <- NA
  expect_false(anyNA(na_seadec(x, algorithm = "interpolation")))
  expect_false(anyNA(na_seadec(x, algorithm = "kalman")))
  expect_false(anyNA(na_seadec(x, algorithm = "locf")))
  expect_false(anyNA(na_seadec(x, algorithm = "ma")))
  expect_false(anyNA(na_seadec(x, algorithm = "mean")))
  expect_false(anyNA(na_seadec(x, algorithm = "random")))
  expect_false(anyNA(na_seadec(x)))
})

test_that("Over 90% NAs", {
  x <- tsAirgap
  x[10:140] <- NA
  expect_false(anyNA(na_seadec(x, algorithm = "interpolation")))
  expect_false(anyNA(na_seadec(x, algorithm = "kalman")))
  expect_false(anyNA(na_seadec(x, algorithm = "locf")))
  expect_false(anyNA(na_seadec(x, algorithm = "ma")))
  expect_false(anyNA(na_seadec(x, algorithm = "mean")))
  expect_false(anyNA(na_seadec(x, algorithm = "random")))
  expect_false(anyNA(na_seadec(x)))
})
test_that("No Seasonality in series", {
  x <- ts(c(3, 5, 6, 7, 8, 4, 5, 6, NA, NA, 5, 7, 4, 2, NA, NA, 5, 7, 8))
  expect_false(anyNA(na_seadec(x, algorithm = "interpolation")))
  expect_false(anyNA(na_seadec(x, algorithm = "kalman")))
  expect_false(anyNA(na_seadec(x, algorithm = "locf")))
  expect_false(anyNA(na_seadec(x, algorithm = "ma")))
  expect_false(anyNA(na_seadec(x, algorithm = "mean")))
  expect_false(anyNA(na_seadec(x, algorithm = "random")))
  expect_false(anyNA(na_seadec(x)))
})

test_that("Handling for no NAs", {
  x <- tsAirgapComplete
  expect_false(anyNA(na_seadec(x)))
})


test_that("Correct results for all options with the tsAirgap dataset with find frequency", {
  skip_on_cran()
  # Using mean over resulting vector to check correctness
  # In order to avoid writing down the complete resulting vector
  # Using rounded version in order to avoid writing down all decimals
  x <- as.vector(tsAirgap)
  expect_equal(round(mean(na_seadec(x, algorithm = "interpolation", find_frequency = TRUE)), digits = 1), 280.4)
  expect_equal(round(mean(na_seadec(x, algorithm = "interpolation", find_frequency = FALSE)), digits = 1), 280.7)

  # Test if set frequencys are accepted as expected for find_frequency= F
  expect_equal(round(mean(na_seadec(ts(x, frequency = 2), algorithm = "interpolation", find_frequency = FALSE)), digits = 1), 280.8)

  # Test if find_frequency works
  expect_equal(round(mean(na_seadec(ts(x, frequency = 2), algorithm = "interpolation", find_frequency = TRUE)), digits = 1), 280.4)


  expect_equal(round(mean(na_seadec(x, algorithm = "locf", find_frequency = TRUE)), digits = 1), 279.7)
  expect_equal(round(mean(na_seadec(x, algorithm = "locf", find_frequency = FALSE)), digits = 1), 278.8)

  expect_equal(round(mean(na_seadec(x, algorithm = "mean", find_frequency = TRUE)), digits = 1), 279.5)
  expect_equal(round(mean(na_seadec(x, algorithm = "mean", find_frequency = FALSE)), digits = 1), 279.8)

  expect_true(round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima", find_frequency = TRUE)), digits = 1) > 277 &
    round(mean(na_seadec(x, algorithm = "kalman", model = "auto.arima", find_frequency = TRUE)), digits = 1) < 283)

  expect_equal(round(mean(na_seadec(x, algorithm = "ma", find_frequency = TRUE)), digits = 1), 280.6)
  expect_equal(round(mean(na_seadec(x, algorithm = "ma", find_frequency = FALSE)), digits = 1), 281.2)
})