# This file takes too long
testthat::skip_on_cran()

data(tips)
data(nasa)
nas <- subset(nasa, x <= 2 & y == 1)

test_that("denstrip", {
  expect_message(
    suppressWarnings(print(ggally_denstrip(tips, mapping = aes(!!as.name("sex"), !!as.name("tip"))))),
    "`stat_bin()` using `bins = 30`",
    fixed = TRUE
  )
  expect_message(
    suppressWarnings(print(ggally_denstrip(tips, mapping = aes(!!as.name("tip"), !!as.name("sex"))))),
    "`stat_bin()` using `bins = 30`",
    fixed = TRUE
  )
})


test_that("density", {
  p <- ggally_density(
    tips,
    mapping = ggplot2::aes(x = !!as.name("total_bill"), y = !!as.name("tip"), fill = after_stat(level))
  ) + ggplot2::scale_fill_gradient(breaks = c(0.05, 0.1, 0.15, 0.2))
  expect_equal(p$labels$fill, "level")
})

test_that("cor", {
  ti <- tips
  class(ti) <- c("NOTFOUND", "data.frame")
  p <- ggally_cor(ti, ggplot2::aes(x = total_bill, y = tip, color = day), use = "complete.obs")
  expect_equal(mapping_string(get("mapping", envir = p$layers[[2]])$colour), "labelp")

  p <- ggally_cor(
    ti,
    ggplot2::aes(x = total_bill, y = tip, color = I("blue")),
    use = "complete.obs"
  )
  expect_equal(mapping_string(get("mapping", envir = p$layers[[1]])$colour), "I(\"blue\")")

  expect_err <- function(..., msg = NULL) {
    expect_error(
      ggally_cor(
        ti, ggplot2::aes(x = total_bill, y = tip),
        ...
      ),
      msg
    )
  }

  vdiffr::expect_doppelganger(
    "cor-green",
    ggally_cor(ti, ggplot2::aes(x = total_bill, y = tip, color = I("green")))
  )

  ti3 <- ti2 <- ti
  ti2[2, "total_bill"] <- NA

  ti3[2, "total_bill"] <- NA
  ti3[3, "tip"] <- NA
  ti3[4, "total_bill"] <- NA
  ti3[4, "tip"] <- NA

  expect_warn <- function(data, msg) {
    expect_warning(
      ggally_cor(data, ggplot2::aes(x = total_bill, y = tip)),
      msg
    )
  }
  expect_warn(ti2, "Removing 1 row that")
  expect_warn(ti3, "Removed 3 rows containing")

  expect_error(
    ggally_cor(
      ti,
      ggplot2::aes(x = total_bill, y = tip, color = size)
    ),
    "must be categorical"
  )
  expect_silent(
    ggally_cor(
      ti,
      ggplot2::aes(x = total_bill, y = tip, color = as.factor(size))
    )
  )
})

test_that("diagAxis", {
  p <- ggally_diagAxis(iris, ggplot2::aes(x = Petal.Width))
  pDat1 <- get("data", envir = p$layers[[2]])
  attr(pDat1, "out.attrs") <- NULL
  testDt1 <- data.frame(
    xPos = c(0.076, 0.076, 0.076, 0.076, 0.076, 0.076, 0.500, 1.000, 1.500, 2.000, 2.500),
    yPos = c(0.500, 1.000, 1.500, 2.000, 2.500, 0.076, 0.076, 0.076, 0.076, 0.076, 0.076),
    lab = as.character(c(0.5, 1, 1.5, 2, 2.5, 0, 0.5, 1, 1.5, 2, 2.5)),
    hjust = c(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5, 0.5, 0.5, 0.5, 0.5),
    vjust = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0),
    stringsAsFactors = FALSE
  )
  rownames(testDt1) <- 2:12
  expect_equal(pDat1, testDt1)

  p <- ggally_diagAxis(iris, ggplot2::aes(x = Species))
  pDat2 <- get("data", envir = p$layers[[2]])
  attr(pDat2, "out.attrs") <- NULL
  testDt2 <- data.frame(
    x = c(0.125, 0.500, 0.875),
    y = c(0.875, 0.500, 0.125),
    lab = c("setosa", "versicolor", "virginica")
  )
  expect_equal(pDat2, testDt2)


  expect_error(
    {
      ggally_diagAxis(iris, mapping = ggplot2::aes(y = Sepal.Length))
    },
    "mapping\\$x is null."
  ) # nolint
})

test_that("dates", {
  class(nas) <- c("NOTFOUND", "data.frame")
  p <- ggally_cor(nas, ggplot2::aes(x = date, y = ozone))
  expect_equal(get("aes_params", envir = p$layers[[1]])$label, "Corr:\n0.278***")
  p <- ggally_barDiag(nas, ggplot2::aes(x = date))
  expect_equal(mapping_string(p$mapping$x), "date")
  expect_equal(as.character(p$labels$y), "count")
})

test_that("cor stars are aligned", {
  p <- ggally_cor(iris, ggplot2::aes(x = Sepal.Length, y = Petal.Width, color = as.factor(Species)))
  expect_equal(get("aes_params", envir = p$layers[[1]])$label, "Corr: 0.818***")
  # expect_equal(get("aes_params", envir = p$layers[[1]])$family, "mono")

  labels <- eval_data_col(p$layers[[2]]$data, p$layers[[2]]$mapping$label)
  expect_equal(as.character(labels), c("    setosa: 0.278.  ", "versicolor: 0.546***", " virginica: 0.281*  "))
})

test_that("ggally_statistic handles factors", {
  simple_chisq <- function(x, y) {
    scales::number(chisq.test(x, y)$p.value, accuracy = .001)
  }
  expect_silent({
    p <- ggally_statistic(tips, aes(x = sex, y = day), text_fn = simple_chisq, title = "Chi^2")
  })
})

test_that("rescale", {
  p <- ggally_densityDiag(tips, mapping = ggplot2::aes(x = day), rescale = FALSE)
  expect_true(p$labels$y == "density")
  vdiffr::expect_doppelganger("rescale-false", p)

  p <- ggally_densityDiag(tips, mapping = ggplot2::aes(x = day), rescale = TRUE)
  expect_true(!identical(p$labels$y, "density"))
  vdiffr::expect_doppelganger("rescale-true", p)


  p <- ggally_barDiag(tips, mapping = ggplot2::aes(x = tip), binwidth = 0.25, rescale = FALSE)
  expect_true(p$labels$y == "count")
  vdiffr::expect_doppelganger("rescale-false-binwidth", p)

  p <- ggally_barDiag(tips, mapping = ggplot2::aes(x = tip), binwidth = 0.25, rescale = TRUE)
  expect_true(!identical(p$labels$y, "count"))
  vdiffr::expect_doppelganger("rescale-true-binwidth", p)
})



test_that("shrink", {
  p <- ggally_smooth_loess(iris, mapping = ggplot2::aes(Sepal.Width, Petal.Length))
  expect_true(!is.null(p$coordinates$limits$y))
  vdiffr::expect_doppelganger("shrink-true", p)

  p <- ggally_smooth_loess(iris, mapping = ggplot2::aes(Sepal.Width, Petal.Length), shrink = FALSE)
  expect_true(is.null(p$coordinates$limits$y))
  vdiffr::expect_doppelganger("shrink-false", p)
})

test_that("smooth_se", {
  p <- ggally_smooth_loess(iris, mapping = ggplot2::aes(Sepal.Width, Petal.Length), se = TRUE)
  expect_equal(p$layers[[2]]$stat_params$se, TRUE)
  vdiffr::expect_doppelganger("smooth-se-true", p)

  p <- ggally_smooth_loess(iris, mapping = ggplot2::aes(Sepal.Width, Petal.Length), se = FALSE)
  expect_equal(p$layers[[2]]$stat_params$se, FALSE)
  vdiffr::expect_doppelganger("smooth-se-false", p)
})


test_that("ggally_count", {
  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Class, y = Survived, weight = Freq)
  )
  vdiffr::expect_doppelganger("titanic-count", p)

  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Class, y = Survived, weight = Freq),
    fill = "red"
  )
  vdiffr::expect_doppelganger("titanic-count-red", p)

  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Class, y = Survived, weight = Freq, fill = Sex)
  )
  vdiffr::expect_doppelganger("titanic-count-sex", p)

  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Class, y = Survived, weight = Freq, fill = Class)
  )
  vdiffr::expect_doppelganger("titanic-count-class", p)

  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Survived, y = interaction(Sex, Age), weight = Freq, fill = Class)
  )
  vdiffr::expect_doppelganger("titanic-count-interaction", p)

  # check that y character vectors are rendering
  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Class, y = toupper(Survived), weight = Freq, fill = Class)
  )
  vdiffr::expect_doppelganger("titanic-count-toupper", p)

  # check countDiag
  p <- ggally_countDiag(
    as.data.frame(Titanic),
    ggplot2::aes(x = Survived, weight = Freq, fill = Class)
  )
  vdiffr::expect_doppelganger("titanic-count-diag", p)

  # change size of tiles
  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = Class, y = Survived, weight = Freq, fill = Class),
    x.width = .5
  )
  vdiffr::expect_doppelganger("titanic-count-diag-class", p)

  # no warnings expected if na.rm = TRUE
  p <- ggally_count(
    as.data.frame(Titanic),
    ggplot2::aes(x = interaction(Class, Age), y = Survived, weight = Freq, fill = Class),
    na.rm = TRUE
  )
  vdiffr::expect_doppelganger("titanic-count-diag-interaction", p)
})