tests/testthat/test-na_kalman.R

In imputeTS: Time Series Missing Value Imputation

context("na_kalman")

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

test_that("Workaround solution for constant values for StructTS works", {
  x <- c(4,4,4,4,NA,4,4,4)
  expect_equal(round(mean(na_kalman(x, model = "StructTS", smooth = T)), digits = 1), 4)
})

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_kalman(x, model = "auto.arima", smooth = T)), digits = 1), 280.3)
  expect_equal(round(mean(na_kalman(x, model = "auto.arima", smooth = F)), digits = 1), 279.2)
})

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_kalman(x, model = "auto.arima", smooth = T)), digits = 1), 284.8)
  expect_equal(round(mean(na_kalman(x, model = "auto.arima", smooth = F)), digits = 1), 291.6)
})


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_kalman(x, model = "auto.arima", smooth = T)), digits = 1), 280.2)
  expect_equal(round(mean(na_kalman(x, model = "auto.arima", smooth = F)), digits = 1), 279.8)
})

test_that("Imputation works for data.frame", {
  # Checking if NAs remain in data.frame
  x <- data.frame(tsAirgap, tsAirgap, tsAirgapComplete)
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = F)))
})

test_that("Warning for wrong input for model parameter", {
  expect_error(na_kalman(tsAirgap, model = "wrongModel"))
})

test_that("Warning for wrong input for smooth parameter", {
  expect_error(na_kalman(tsAirgap, smooth = "Wrong"))
})


test_that("Test NA at beginning", {
  x <- tsAirgap
  x[1:2] <- NA
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = F)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = F)))
  expect_false(anyNA(na_kalman(x)))
})

test_that("Test NA at end", {
  x <- tsAirgap
  x[143:144] <- NA
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = F)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = F)))
  expect_false(anyNA(na_kalman(x)))
})

test_that("Multiple NAs in a row", {
  x <- tsAirgap
  x[40:80] <- NA
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = F)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = F)))
  expect_false(anyNA(na_kalman(x)))
})

test_that("Over 50% NAs", {
  x <- tsAirgap
  x[30:100] <- NA
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "auto.arima", smooth = F)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = T)))
  expect_false(anyNA(na_kalman(x, model = "StructTS", smooth = F)))
  expect_false(anyNA(na_kalman(x)))
})