Nothing

```
context("na.ma")
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_that( round(mean(na.ma( x, weighting="simple", k = 4 )), digits = 1), is_identical_to(275.2) )
expect_that( round(mean(na.ma( x, weighting="simple", k = 20 )), digits = 1), is_identical_to(276.1) )
expect_that( round(mean(na.ma( x, weighting="linear", k = 4 )), digits = 1), is_identical_to(275.0) )
expect_that( round(mean(na.ma( x, weighting="linear", k = 20 )), digits = 1), is_identical_to(276.1) )
expect_that( round(mean(na.ma( x, weighting="exponential", k = 4 )), digits = 1), is_identical_to(274.6) )
expect_that( round(mean(na.ma( x, weighting="exponential", k = 20 )), digits = 1), is_identical_to(274.7) )
})
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_that( round(mean(na.ma( x, weighting="simple", k = 4 )), digits = 1), is_identical_to(282.1) )
expect_that( round(mean(na.ma( x, weighting="simple", k = 20 )), digits = 1), is_identical_to(281.1) )
expect_that( round(mean(na.ma( x, weighting="linear", k = 4 )), digits = 1), is_identical_to(281.9) )
expect_that( round(mean(na.ma( x, weighting="linear", k = 20 )), digits = 1), is_identical_to(281.3) )
expect_that( round(mean(na.ma( x, weighting="exponential", k = 4 )), digits = 1), is_identical_to(281.7) )
expect_that( round(mean(na.ma( x, weighting="exponential", k = 20 )), digits = 1), is_identical_to(281.6) )
})
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_that( round(mean(na.ma( x, weighting="simple", k = 4 )), digits = 1), is_identical_to(281.5) )
expect_that( round(mean(na.ma( x, weighting="simple", k = 20 )), digits = 1), is_identical_to(280.7) )
expect_that( round(mean(na.ma( x, weighting="linear", k = 4 )), digits = 1), is_identical_to(281.3) )
expect_that( round(mean(na.ma( x, weighting="linear", k = 20 )), digits = 1), is_identical_to(280.9) )
expect_that( round(mean(na.ma( x, weighting="exponential", k = 4 )), digits = 1), is_identical_to(281.2) )
expect_that( round(mean(na.ma( x, weighting="exponential", k = 20 )), digits = 1), is_identical_to(281.1) )
})
test_that("Imputation works for data.frame",
{
#Checking if NAs remain in data.frame
x <- data.frame(tsAirgap, tsAirgap, tsAirgapComplete)
expect_that(anyNA(na.ma(x, weighting="simple", k = 4 )), is_false())
expect_that(anyNA(na.ma(x, weighting="simple", k = 20)), is_false())
expect_that(anyNA(na.ma(x, weighting="linear", k = 4 )), is_false())
expect_that(anyNA(na.ma(x, weighting="linear", k = 20)), is_false())
expect_that(anyNA(na.ma(x, weighting="exponential", k = 4 )), is_false())
expect_that(anyNA(na.ma(x, weighting="exponential", k = 20)), is_false())
})
test_that("Error for wrong input for k parameter",
{
expect_that( na.ma(tsAirgap, k = -1), throws_error())
})
test_that("Error for wrong input for weighting parameter",
{
expect_that( na.ma(tsAirgap, weighting ="Wrong"), throws_error())
})
test_that("Test NA at beginning",
{
x <- tsAirgap
x[1:2] <- NA
expect_that(anyNA(na.ma(x, k = 4, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x)), is_false())
})
test_that("Test NA at end",
{
x <- tsAirgap
x[143:144] <- NA
expect_that(anyNA(na.ma(x, k = 4, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x)), is_false())
})
test_that("Multiple NAs in a row",
{
x <- tsAirgap
x[40:80] <- NA
expect_that(anyNA(na.ma(x, k = 4, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x)), is_false())
})
test_that("Over 90% NAs",
{
x <- tsAirgap
x[10:140] <- NA
expect_that(anyNA(na.ma(x, k = 4, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "simple")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "linear")), is_false())
expect_that(anyNA(na.ma(x, k = 4, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 1, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x, k = 20, weighting = "exponential")), is_false())
expect_that(anyNA(na.ma(x)), is_false())
})
```

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