tests/testthat/test-findDuplicates.R

In Pandora-IsoMemo/iso-app: Pandora & IsoMemo spatiotemporal modeling

context("findDuplicates function with detectDuplicates Module")

test_that("findDuplicates", {
  testdata <- structure(list(
    id1 = c(
    "string1", "STRING1", "string2", "string2",
    "String2", "String3", "String3", "strIng3", "", "", "sstrIng3strIng3strIng3strIng3strIng3strIng3strIng3strIng3trIng3"
  ),
  id2 = c(1, 1, 1, 0, 1, 1, 1, 1.2, 1, 1, 1.2),
  id3 = c(1, 1, 1, 1, 1, 1, 1, 1.23, 1, 1, 1.23),
  id4 = c(1, 1, 1, 1, 1, 1, 1, 1.234, NA, NA, 1.234),
  id5 = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L),
  id6 = c(
    "string1", "STRING1", "string2", "string2",
    "String2", "String3", "String3", "strIng3", "", "", "strIng3"
  ),
  id7 = c(1, 1, 1, 0, 1, 1, 1, 1.2, 1, 1, 1.2),
  id8 = c(1, 1, 1, 1, 1, 1, 1, 1.23, 1, 1, 1.23),
  id9 = c(1, 1, 1, 1, 1, 1, 1, 1.234, NA, NA, 1.234),
  id10 = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L),
  id11 = c(
    "string1", "STRING1", "string2", "string2",
    "String2", "String3", "String3", "strIng3", "", "", "strIng3"
  ),
  id12 = c(1, 1, 1, 1, 1, 1, 1, 1.23, 1, 1, 1.23)),
  class = "data.frame",
  row.names = c(NA,-11L)
  )

  userSimilaritySelection <- data.frame(
    cols = c("id1"),
    textSimilarity = "Case Sensitive",
    specificString = "",
    numericSimilarity = NA,
    rounding = NA,
    ignoreEmpty = TRUE,
    ignoreSpaces = FALSE
  )

  findDuplicatesResult <- findDuplicates(
    data = testdata,
    userSimilaritySelection = userSimilaritySelection,
    addColumn = TRUE,
    keepFirst = TRUE
  )

  expect_equal(length(findDuplicatesResult), 4)
  expect_true(nrow(findDuplicatesResult$inputData) == 11)
  expect_true(nrow(findDuplicatesResult$allDuplicatesDF) == 4)
  expect_true(identical(findDuplicatesResult$allDuplicatesRows,as.integer(c(3,4,6,7))))
  expect_true(nrow(findDuplicatesResult$uniqueData) == 8)
  expect_true("duplicateRows" %in% names(findDuplicatesResult$inputData))
  expect_true("duplicateRows" %in% names(findDuplicatesResult$allDuplicatesDF))
  expect_true("duplicateRows" %in% names(findDuplicatesResult$uniqueData))

  userSimilaritySelection <- data.frame(
    cols = c("id4"),
    textSimilarity = NA,
    specificString = "",
    numericSimilarity = "Rounded Match",
    rounding = 1,
    ignoreEmpty = FALSE,
    ignoreSpaces = FALSE
  )

  findDuplicatesResult <- findDuplicates(
    data = testdata,
    userSimilaritySelection = userSimilaritySelection,
    addColumn = TRUE,
    keepFirst = TRUE
  )

  expect_equal(length(findDuplicatesResult), 4)
  expect_true(nrow(findDuplicatesResult$inputData) == 11)
  expect_true(nrow(findDuplicatesResult$allDuplicatesDF) == 11)
  expect_true(identical(findDuplicatesResult$allDuplicatesRows,as.integer(1:11)))
  expect_true(nrow(findDuplicatesResult$uniqueData) == 3)
  expect_true("duplicateRows" %in% names(findDuplicatesResult$inputData))
  expect_true("duplicateRows" %in% names(findDuplicatesResult$allDuplicatesDF))
  expect_true("duplicateRows" %in% names(findDuplicatesResult$uniqueData))
})