tests/testthat/test_prepare_results_MCA.R

In juba/explor: Interactive Interfaces for Results Exploration

skip_if_not(require("FactoMineR"))
context("prepare_results.MCA")

data(hobbies)
mca <- FactoMineR::MCA(hobbies[1:1000, c(1:8, 21:23)],
  quali.sup = 9:10,
  quanti.sup = 11, ind.sup = 1:100, excl = c(5, 8),
  graph = FALSE
)
res <- prepare_results(mca)

test_that("Eigenvalues are equals", {
  expect_equal(unname(mca$eig[, "percentage of variance"]), res$eig$percent)
})

test_that("Variables results are equal", {
  expect_equal(
    as.vector(round(mca$var$coord[, 1], 3)),
    res$vars[res$vars$Type == "Active" & res$vars$Axis == "1", "Coord"]
  )
  expect_equal(
    as.vector(round(mca$var$cos2[, 2], 3)),
    res$vars[res$vars$Type == "Active" & res$vars$Axis == "2", "Cos2"]
  )
  expect_equal(
    as.vector(round(mca$var$contrib[, 3], 3)),
    res$vars[res$vars$Type == "Active" & res$vars$Axis == "3", "Contrib"]
  )
  expect_equal(
    as.vector(mca$var$eta2[, 5]),
    data.frame(res$vareta2)[res$vareta2$Type == "Active" &
      res$vareta2$Axis == "5", "eta2", drop = TRUE]
  )
})

test_that("Qualitative supplementary variables results are equal", {
  expect_equal(
    as.vector(round(mca$quali.sup$coord[, 1], 3)),
    res$vars[res$vars$Type == "Supplementary" &
      res$vars$Class == "Qualitative" & res$vars$Axis == "1", "Coord"]
  )
  expect_equal(
    as.vector(round(mca$quali.sup$cos2[, 2], 3)),
    res$vars[res$vars$Type == "Supplementary" &
      res$vars$Class == "Qualitative" & res$vars$Axis == "2", "Cos2"]
  )
  expect_equal(
    as.vector(round(mca$quali.sup$v.test[, 3], 2)),
    res$vars[res$vars$Type == "Supplementary" &
      res$vars$Class == "Qualitative" & res$vars$Axis == "3", "V.test"]
  )
  expect_equal(
    as.vector(mca$quali.sup$eta2[, 2]),
    data.frame(res$vareta2)[res$vareta2$Type == "Supplementary" &
      res$vareta2$Class == "Qualitative" &
      res$vareta2$Axis == "2", "eta2", drop = TRUE]
  )
})

test_that("Quantitative supplementary variables results are equal", {
  expect_equal(
    as.vector(round(mca$quanti.sup$coord[, 1], 3)),
    res$vars[res$vars$Type == "Supplementary" &
      res$vars$Class == "Quantitative" & res$vars$Axis == "1", "Coord"]
  )
})

test_that("Individuals results are equal", {
  expect_equal(
    as.vector(round(mca$ind$coord[, 1], 3)),
    data.frame(res$ind)[res$ind$Type == "Active" & res$ind$Axis == "1", "Coord"]
  )
  expect_equal(
    as.vector(round(mca$ind$contrib[, 3], 3)),
    data.frame(res$ind)[res$ind$Type == "Active" & res$ind$Axis == "3", "Contrib"]
  )
  expect_equal(
    as.vector(round(mca$ind$cos2[, 5], 3)),
    data.frame(res$ind)[res$ind$Type == "Active" & res$ind$Axis == "5", "Cos2"]
  )
})

test_that("Supplementary individuals results are equal", {
  expect_equal(
    as.vector(round(mca$ind.sup$coord[, 4], 3)),
    data.frame(res$ind)[res$ind$Type == "Supplementary" & res$ind$Axis == "4", "Coord"]
  )
  expect_equal(
    as.vector(round(mca$ind.sup$cos2[, 2], 3)),
    data.frame(res$ind)[res$ind$Type == "Supplementary" & res$ind$Axis == "2", "Cos2"]
  )
})

test_that("Qualitative data are equal", {
  ids <- c("11000210", "11009110", "21052910", "21063810", "22007510")
  expect_equal(
    as.character(res$quali_data$`Marital status`[res$quali_data$Name %in% ids]),
    as.character(hobbies[ids, "Marital status"])
  )
})

test_that("Counts are equal", {
  expect_equal(
    res$vars$Count[res$vars$Level == "Show_0" & res$vars$Axis == 1],
    as.numeric(table(hobbies[101:1000, "Show"])["0"])
  )
  expect_equal(
    res$vars$Count[res$vars$Level == "Employee" & res$vars$Axis == 3],
    as.numeric(table(hobbies[101:1000, "Profession"])["Employee"])
  )
})