adding NA tests for AnomalyDetectionVec

tests/testthat/test-ts.R

@@ -4,44 +4,44 @@ context("Evaluation: AnomalyDetectionTs")
 test_that("last day, both directions, with plot", {
   results <- AnomalyDetectionTs(raw_data, max_anoms=0.02, direction='both', only_last='day', plot=T)
   expect_equal(length(results$anoms), 2)
-  expect_equal(length(results$anoms[[2]]), 25)
+  expect_equal(length(results$anoms[[2L]]), 25)
   expect_equal(class(results$plot), c("gg", "ggplot"))
 })
 
 test_that("both directions, e_value, with longterm", {
   results <- AnomalyDetectionTs(raw_data, max_anoms=0.02, direction='both', longterm=TRUE, e_value=TRUE)
   expect_equal(length(results$anoms), 3)
-  expect_equal(length(results$anoms[[2]]), 131)
+  expect_equal(length(results$anoms[[2L]]), 131)
   expect_equal(results$plot, NULL)
 })
 
 test_that("both directions, e_value, threshold set to med_max", {
   results <- AnomalyDetectionTs(raw_data, max_anoms=0.02, direction='both', threshold="med_max", e_value=TRUE)
   expect_equal(length(results$anoms), 3)
-  expect_equal(length(results$anoms[[2]]), 4)
+  expect_equal(length(results$anoms[[2L]]), 4)
   expect_equal(results$plot, NULL)
 })
 
 context("Evaluation: AnomalyDetectionVec")
 
 test_that("last period, both directions, with plot", {
-  results <- AnomalyDetectionVec(raw_data[[2]], max_anoms=0.02, direction='both', period=1440, only_last=TRUE, plot=T)
+  results <- AnomalyDetectionVec(raw_data[[2L]], max_anoms=0.02, direction='both', period=1440, only_last=TRUE, plot=T)
   expect_equal(length(results$anoms), 2)
-  expect_equal(length(results$anoms[[2]]), 25)
+  expect_equal(length(results$anoms[[2L]]), 25)
   expect_equal(class(results$plot), c("gg", "ggplot"))
 })
 
 test_that("both directions, e_value, with longterm", {
-  results <- AnomalyDetectionVec(raw_data[[2]], max_anoms=0.02, direction='both', period=1440, longterm_period=1440*14, e_value=TRUE)
+  results <- AnomalyDetectionVec(raw_data[[2L]], max_anoms=0.02, direction='both', period=1440, longterm_period=1440*14, e_value=TRUE)
   expect_equal(length(results$anoms), 3)
-  expect_equal(length(results$anoms[[2]]), 131)
+  expect_equal(length(results$anoms[[2L]]), 131)
   expect_equal(results$plot, NULL)
 })
 
 test_that("both directions, e_value, threshold set to med_max", {
-  results <- AnomalyDetectionVec(raw_data[[2]], max_anoms=0.02, direction='both', period=1440, threshold="med_max", e_value=TRUE)
+  results <- AnomalyDetectionVec(raw_data[[2L]], max_anoms=0.02, direction='both', period=1440, threshold="med_max", e_value=TRUE)
   expect_equal(length(results$anoms), 3)
-  expect_equal(length(results$anoms[[2]]), 6)
+  expect_equal(length(results$anoms[[2L]]), 6)
   expect_equal(results$plot, NULL)
 })
 
@@ -52,11 +52,25 @@ test_that("check handling of datasets with leading and trailing NAs", {
   raw_data[length(raw_data[[2L]]), "count"] <- NA
   results <- AnomalyDetectionTs(raw_data, max_anoms=0.02, direction='both', plot=T)
   expect_equal(length(results$anoms), 2)
-  expect_equal(length(results$anoms[[2]]), 131)
+  expect_equal(length(results$anoms[[2L]]), 131)
   expect_equal(class(results$plot), c("gg", "ggplot"))
 })
 
 test_that("check handling of datasets with NAs in the middle", {
   raw_data[floor(length(raw_data[[2L]])/2), "count"] <- NA
   expect_error(AnomalyDetectionTs(raw_data, max_anoms=0.02, direction='both'))
 })
+
+test_that("check handling of datasets with leading and trailing NAs", {
+  raw_data[1:10, "count"] <- NA
+  raw_data[length(raw_data[[2L]]), "count"] <- NA
+  results <- AnomalyDetectionVec(raw_data[[2]], max_anoms=0.02, period=1440, direction='both', plot=T)
+  expect_equal(length(results$anoms), 2)
+  expect_equal(length(results$anoms[[2L]]), 131)
+  expect_equal(class(results$plot), c("gg", "ggplot"))
+})
+
+test_that("check handling of datasets with NAs in the middle", {
+  raw_data[floor(length(raw_data[[2L]])/2), "count"] <- NA
+  expect_error(AnomalyDetectionVec(raw_data[[2L]], max_anoms=0.02, period=1440, direction='both'))
+})