library(testthat)
library(AutoEDA)
library(ggplot2)

#==========================================================
# outlier_detection()
#==========================================================

test_that("outlier_detection returns OutlierSummary", {

  x <- outlier_detection(iris)

  expect_s3_class(
    x,
    "OutlierSummary"
  )

})

test_that("outlier_detection accepts IQR", {

  expect_no_error(
    outlier_detection(
      iris,
      method = "IQR"
    )
  )

})

test_that("outlier_detection accepts ZScore", {

  expect_no_error(
    outlier_detection(
      iris,
      method = "ZScore"
    )
  )

})

test_that("outlier_detection accepts MAD", {

  expect_no_error(
    outlier_detection(
      iris,
      method = "MAD"
    )
  )

})

test_that("outlier_detection rejects invalid method", {

  expect_error(
    outlier_detection(
      iris,
      method = "ABC"
    )
  )

})

test_that("outlier_detection rejects invalid threshold", {

  expect_error(
    outlier_detection(
      iris,
      threshold = 0
    )
  )

})

test_that("outlier_detection rejects non-data.frame", {

  expect_error(
    outlier_detection(
      1:10
    )
  )

})

test_that("outlier_detection rejects empty data.frame", {

  expect_error(
    outlier_detection(
      data.frame()
    )
  )

})

#==========================================================
# outlier_summary()
#==========================================================

test_that("outlier_summary returns OutlierSummary", {

  x <- outlier_summary(iris)

  expect_s3_class(
    x,
    "OutlierSummary"
  )

})

test_that("outlier_summary accepts valid data", {

  expect_no_error(
    outlier_summary(iris)
  )

})

test_that("outlier_summary rejects invalid input", {

  expect_error(
    outlier_summary(1:10)
  )

})

#==========================================================
# plot_outliers()
#==========================================================

test_that("plot_outliers returns ggplot", {

  p <- plot_outliers(iris)

  expect_s3_class(
    p,
    "ggplot"
  )

})

test_that("plot_outliers accepts valid data", {

  expect_no_error(
    plot_outliers(iris)
  )

})

test_that("plot_outliers rejects invalid input", {

  expect_error(
    plot_outliers(1:10)
  )

})

#==========================================================
# outlier_values()
#==========================================================

test_that("outlier_values returns data.frame", {

  x <- outlier_values(
    iris,
    "Sepal.Length"
  )

  expect_s3_class(
    x,
    "data.frame"
  )

})

test_that("outlier_values accepts valid input", {

  expect_no_error(
    outlier_values(
      iris,
      "Sepal.Length"
    )
  )

})

test_that("outlier_values preserves columns", {

  x <- outlier_values(
    iris,
    "Sepal.Length"
  )

  expect_equal(
    names(x),
    names(iris)
  )

})

test_that("outlier_values returns zero or more rows", {

  x <- outlier_values(
    iris,
    "Sepal.Length"
  )

  expect_gte(
    nrow(x),
    0
  )

})

test_that("outlier_values handles missing values", {

  d <- iris

  d$Sepal.Length[1:5] <- NA

  expect_no_error(
    outlier_values(
      d,
      "Sepal.Length"
    )
  )

})

test_that("outlier_values works when no outliers exist", {

  d <- data.frame(
    x = c(10,11,12,13,14,15)
  )

  x <- outlier_values(
    d,
    "x"
  )

  expect_equal(
    nrow(x),
    0
  )

})

test_that("outlier_values rejects non-data.frame", {

  expect_error(
    outlier_values(
      1:10,
      "x"
    )
  )

})

test_that("outlier_values rejects empty data.frame", {

  expect_error(
    outlier_values(
      data.frame(),
      "x"
    )
  )

})

test_that("outlier_values rejects invalid variable", {

  expect_error(
    outlier_values(
      iris,
      "ABC"
    )
  )

})

test_that("outlier_values rejects categorical variable", {

  expect_error(
    outlier_values(
      iris,
      "Species"
    )
  )

})