library("testthat")
library("stringr")
library("dplyr")
# I need to include this for unknown reason or the test fails in R CMD check mode

data("Loblolly")

set.seed(1)
Loblolly$young <- Loblolly$age < 10
Loblolly$young <- factor(Loblolly$young, label = c("Yes", "No"))
Loblolly$fvar <- factor(sample(letters[1:3], size = nrow(Loblolly), replace = TRUE))
Loblolly$young_w_missing <- Loblolly$young
Loblolly$young_w_missing[sample(1:nrow(Loblolly), size = 4)] <- NA
Loblolly$fvar_w_missing <- Loblolly$fvar
Loblolly$fvar_w_missing[sample(1:nrow(Loblolly), size = 4)] <- NA
Loblolly$height_w_missing <- Loblolly$height
Loblolly$height_w_missing[sample(1:nrow(Loblolly), size = 4)] <- NA

test_that("Check mean function", {
  stats <- by(Loblolly$height, Loblolly$young, mean)
  a <- getDescriptionStatsBy(Loblolly$height,
                             Loblolly$young,
                             statistics = TRUE,
                             digits = 2,
                             statistics.sig_lim = 10^-4)
  # Check that it contains the true mean
  expect_true(grepl(round(stats[["No"]], 2), a[1, "No"]),
    info = "Expected the mean"
  )
  expect_true(grepl(round(stats[["Yes"]], 2), a[1, "Yes"]),
    info = "Expected the mean"
  )

  # Check that it contains the sd
  stats <- by(Loblolly$height, Loblolly$young, sd)
  expect_true(grepl(round(stats[["No"]], 2), a[1, "No"]),
    info = "Expected the sd"
  )
  expect_true(grepl(round(stats[["Yes"]], 2), a[1, "Yes"]),
    info = "Expected the sd"
  )

  true_wilc_pv <- txtPval(wilcox.test(Loblolly$height ~ Loblolly$young)$p.value,
    statistics.sig_lim = 10^-4
  )
  expect_equal(
    as.character(a[1, "P-value"]),
    true_wilc_pv
  )

  # Check P-value without truncation
  a <- getDescriptionStatsBy(Loblolly$height, Loblolly$age == 10,
    statistics = TRUE,
    digits = 2, statistics.sig_lim = 10^-4
  )
  true_wilc_pv <- txtPval(wilcox.test(Loblolly$height ~ Loblolly$age == 10)$p.value,
    statistics.sig_lim = 10^-4
  )
  expect_equal(
    as.character(a[1, "P-value"]),
    true_wilc_pv
  )
})

test_that("Check median function", {
  stats <- by(Loblolly$height, Loblolly$young, median)
  a <- getDescriptionStatsBy(Loblolly$height, Loblolly$young,
    continuous_fn = describeMedian,
    statistics = TRUE,
    digits = 2, statistics.sig_lim = 10^-4
  )
  # Check that it contains the true mean
  expect_true(grepl(round(stats[["No"]], 2), a[1, "No"]),
    info = "Expected the median"
  )
  expect_true(grepl(round(stats[["Yes"]], 2), a[1, "Yes"]),
    info = "Expected the median"
  )

  # Check that it contains the sd
  stats <- by(
    Loblolly$height, Loblolly$young,
    function(x) {
      str_trim(paste(format(quantile(x, probs = c(.25, .75)),
        digits = 2,
        nsmall = 2
      ), collapse = " - "))
    }
  )
  expect_true(grepl(stats[["No"]], a[1, "No"]),
    info = "Expected the iqr range"
  )
  expect_true(grepl(stats[["Yes"]], a[1, "Yes"]),
    info = "Expected the iqr range"
  )

  true_wilc_pv <- txtPval(wilcox.test(Loblolly$height ~ Loblolly$young)$p.value,
    statistics.sig_lim = 10^-4
  )
  expect_equal(
    as.character(a[1, "P-value"]),
    true_wilc_pv
  )

  a <- getDescriptionStatsBy(Loblolly$height, Loblolly$young,
    continuous_fn = function(...) {
      describeMedian(..., iqr = FALSE)
    },
    statistics = TRUE,
    digits = 2, statistics.sig_lim = 10^-4
  )

  # Check that it contains the sd
  stats <- by(
    Loblolly$height, Loblolly$young,
    function(x) paste(round(range(x), 2), collapse = " - ")
  )
  expect_true(grepl(stats[["No"]], a[1, "No"]),
    info = "Expected the range"
  )
  expect_true(grepl(stats[["Yes"]], a[1, "Yes"]),
    info = "Expected the range"
  )
})

test_that("Check small proportions", {
  n <- 1e4
  a <- getDescriptionStatsBy(LETTERS[c(rep(1, times = (n - 4)), rep(2, times = 4))],
                             letters[c(rep(1, times = (n - 10)), rep(2, times = 10))],
                             hrzl_prop = TRUE,
                             statistics = TRUE,
                             digits = 0,
                             digits.nonzero = 2,
                             statistics.sig_lim = 10^-4)
  expect_equivalent(as.character(a["A", "b"]), "6 (0.06%)")

  a <- getDescriptionStatsBy(LETTERS[c(rep(1, times = (n - 4)), rep(2, times = 4))],
                             letters[c(rep(1, times = (n - 10)), rep(2, times = 10))],
                             hrzl_prop = TRUE,
                             statistics = TRUE,
                             digits = 0,
                             statistics.sig_lim = 10^-4)
  expect_equivalent(as.character(a["A", "b"]), "6 (0%)")

  # Make sure to handle character input and make it default to the
  # first factor level
  set.seed(1)
  fake_data <- data.frame(Large = sample(LETTERS[1:2], size = n, replace = TRUE),
                          Small = sample(letters[1:2], size = n, replace = TRUE))
  fake_data$Small_factor <- factor(fake_data$Small)
  a <- getDescriptionStatsBy(fake_data$Large,
                             by = fake_data$Small)
  b <- getDescriptionStatsBy(fake_data$Large,
                             by = fake_data$Small_factor)
  attr(a, "raw_data") <- NULL
  attr(b, "raw_data") <- NULL
  expect_identical(a, b)
})

test_that("Check factor function", {
  stats <- table(Loblolly$fvar, Loblolly$young)
  a <- getDescriptionStatsBy(Loblolly$fvar,
                             Loblolly$young,
                             statistics = TRUE,
                             digits = 2,
                             statistics.sig_lim = 10^-4)
  # Check that it contains the true mean
  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], as.character(stats[rn, cn]),
        info = "Factor count don't match"
      )
    }
  }

  # Check that character input is handled similarly
  b <- getDescriptionStatsBy(as.character(Loblolly$fvar),
                             as.character(Loblolly$young),
                             statistics = TRUE,
                             digits = 2,
                             statistics.sig_lim = 10^-4)
  label(a) <- ""
  label(b) <- ""
  for (colname in colnames(b)) {
    expect_equal(a[,colname], b[, colname])
  }
  vertical_perc_stats <- format(apply(stats, 2, function(x) {
    x / sum(x) * 100
  }), nsmall = 2, digits = 2)
  horizontal_perc_stats <- t(format(apply(stats, 1, function(x) {
    x / sum(x) * 100
  }), nsmall = 2, digits = 2))
  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], sprintf("%s%%", vertical_perc_stats[rn, cn]),
        info = "Factor percentagess don't match in vertical mode"
      )
    }
  }

  a <- getDescriptionStatsBy(Loblolly$fvar,
                             Loblolly$young,
                             hrzl_prop = TRUE,
                             statistics = TRUE,
                             digits = 2,
                             statistics.sig_lim = 10^-4)
  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], sprintf("%s%%", horizontal_perc_stats[rn, cn]),
        info = "Factor percentagess don't match in horizontal mode"
      )
    }
  }
})

test_that("Check total column position", {
  a <- getDescriptionStatsBy(Loblolly$fvar,
                             Loblolly$young,
                             hrzl_prop = TRUE, add_total_col = TRUE,
                             continuous_fn = describeMedian,
                             statistics = TRUE,
                             digits = 2, statistics.sig_lim = 10^-4)
  expect_equivalent(colnames(a)[1], "Total")
  expect_equivalent(ncol(a), 4)

  a <- getDescriptionStatsBy(Loblolly$fvar, Loblolly$young,
    hrzl_prop = TRUE,
    add_total_col = "last",
    continuous_fn = describeMedian,
    digits = 2, statistics.sig_lim = 10^-4
  )
  expect_equivalent(tail(colnames(a), 1), "Total",
    info = "The last column without statistics should be the total column when the add_total_col is set to last"
  )
  expect_equivalent(ncol(a), 3)

  a <- getDescriptionStatsBy(Loblolly$fvar, Loblolly$young,
    statistics = TRUE,
    hrzl_prop = TRUE,
    add_total_col = "last"
  )
  expect_equivalent(tail(colnames(a), 2)[1], "Total",
    info = "The last should be the p-value if statistics is specified"
  )
  expect_equivalent(ncol(a), 4)
})

test_that("Check factor function with missing", {
  stats <- table(Loblolly$fvar, Loblolly$young_w_missing, useNA = "ifany")
  a <- expect_warning(getDescriptionStatsBy(Loblolly$fvar,
                                            Loblolly$young_w_missing,
                                            statistics = TRUE,
                                            digits = 2,
                                            statistics.sig_lim = 10^-4
  ))

  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], as.character(stats[rn, cn]),
        info = "Factor count don't match"
      )
    }
  }


  stats <- table(Loblolly$fvar, Loblolly$young_w_missing, useNA = "no")
  vertical_perc_stats <-
    format(apply(stats, 2, function(x) {
      x / sum(x) * 100
    }), nsmall = 2, digits = 2)
  horizontal_perc_stats <-
    t(format(apply(stats, 1, function(x) {
      x / sum(x) * 100
    }), nsmall = 2, digits = 2))

  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], sprintf("%s%%", vertical_perc_stats[rn, cn]),
        info = "Factor vertical percentages don't match"
      )
    }
  }

  a <- suppressWarnings(getDescriptionStatsBy(Loblolly$fvar,
                                              Loblolly$young_w_missing,
                                              hrzl_prop = TRUE,
                                              statistics = TRUE,
                                              digits = 2,
                                              statistics.sig_lim = 10^-4))

  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], sprintf("%s%%", horizontal_perc_stats[rn, cn]),
        info = "Factor percentages don't match in horizontal mode"
      )
    }
  }

  a <- suppressWarnings(getDescriptionStatsBy(Loblolly$fvar_w_missing,
                                              Loblolly$young_w_missing,
                                              useNA = "no",
                                              digits = 2,
                                              statistics.sig_lim = 10^-4))
  stats <- table(Loblolly$fvar_w_missing, Loblolly$young_w_missing, useNA = "no")
  vertical_perc_stats <-
    format(apply(stats, 2, function(x) {
      x / sum(x) * 100
    }), nsmall = 2, digits = 2)

  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], as.character(stats[rn, cn]),
        info = sprintf(
          "Factor '%s':'%s' count don't match",
          rn, cn
        )
      )
      expect_match(a[rn, cn], sprintf("%s%%", vertical_perc_stats[rn, cn]),
        info = sprintf(
          "Factor '%s':'%s' vertical percentages don't match",
          rn, cn
        )
      )
    }
  }

  a <- suppressWarnings(getDescriptionStatsBy(Loblolly$fvar_w_missing,
                                              Loblolly$young_w_missing,
                                              digits = 2,
                                              statistics.sig_lim = 10^-4))
  stats <- table(Loblolly$fvar_w_missing, Loblolly$young_w_missing, useNA = "ifany")
  stats <- stats[, !is.na(colnames(stats))]
  rownames(stats)[is.na(rownames(stats))] <- "Missing"
  vertical_perc_stats <-
    format(apply(stats, 2, function(x) {
      x / sum(x) * 100
    }), nsmall = 2, digits = 2)
  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], as.character(stats[rn, cn]),
        info = sprintf(
          "Factor '%s':'%s' count don't match",
          rn, cn
        )
      )
      expect_match(a[rn, cn], sprintf("%s%%", str_trim(vertical_perc_stats[rn, cn])),
        info = sprintf(
          "Factor '%s':'%s' vertical percentages don't match",
          rn, cn
        )
      )
    }
  }

  a <- suppressWarnings(getDescriptionStatsBy(Loblolly$fvar_w_missing,
                                              Loblolly$young_w_missing,
                                              hrzl_prop = TRUE,
                                              digits = 2,
                                              statistics.sig_lim = 10^-4))
  horizontal_perc_stats <-
    t(format(apply(stats, 1, function(x) {
      x / sum(x) * 100
    }), nsmall = 2, digits = 2))


  for (rn in rownames(a)) {
    for (cn in levels(Loblolly$young)) {
      expect_match(a[rn, cn], sprintf("%s%%", str_trim(horizontal_perc_stats[rn, cn])),
        info = "Factor vertical percentages don't match"
      )
    }
  }

  # When
  # - `x` has exactly 2 levels and some NAs
  # - add_total_col = TRUE
  # - show_missing = "no"
  # - show_all_values = FALSE
  # Then prGetStatistics should return the count of just the first factor level
  # use example:
  #   a <- getDescriptionStatsBy(Loblolly$young_w_missing, Loblolly$fvar,
  #                              useNA = "no", digits = 2,
  #                              add_total_col = TRUE)
  a <- prGetStatistics(Loblolly$young_w_missing,
                       useNA = "no",
                       show_all_values = FALSE)
  lvl <- levels(Loblolly$young_w_missing)[1]
  target <- sum(stats[, lvl])
  names(target) <- lvl
  expect_equal(a, target)
})

test_that("Check txtInt application", {
  # Check for factors
  set.seed(10)
  test_var <- factor(sample(1:3, size = 10^4, replace = TRUE))
  out <- prGetStatistics(test_var,
                         useNA = "no",
                         show_all_values = FALSE)
  expect_true(any(grepl(",", out)))
})

test_that("Problem with boolean x", {
  set.seed(1)
  aa <- factor(sample(c("No", "Yes"), size = 50, replace = TRUE))
  aaa <- sample(c(TRUE, FALSE), size = 50, replace = TRUE)
  ret <- getDescriptionStatsBy(x = aaa, by = aa, numbers_first = TRUE)
  expect_equivalent(nrow(ret), 1,
    info = "There should only be one alternative returned"
  )
  expect_equivalent(ncol(ret), 2,
    info = "There should be two columns"
  )
  expect_match(ret[TRUE, "No"], sprintf("^%d", table(aaa, aa)["TRUE", "No"]),
    info = "The value does not seem to match the raw table"
  )
})

test_that("test header", {
  data(mtcars)

  mtcars$am <- factor(mtcars$am, levels = 0:1, labels = c("Automatic", "Manual"))
  Hmisc::label(mtcars$am) <- "Transmission"
  set.seed(666)
  mtcars$col <- factor(sample(c("red", "black", "silver"),
    size = NROW(mtcars), replace = TRUE
  ))

  out <- getDescriptionStatsBy(
    x = mtcars$col,
    by = mtcars$am,
    header_count = TRUE,
    add_total_col = TRUE,
    statistics = TRUE
  )
  expect_match(
    colnames(out)[1],
    sprintf("No. %d", nrow(mtcars))
  )
  expect_match(
    colnames(out)[2],
    sprintf(
      "No. %d",
      sum(mtcars$am == levels(mtcars$am)[1])
    )
  )
  expect_match(
    colnames(out)[3],
    sprintf(
      "No. %d",
      sum(mtcars$am != levels(mtcars$am)[1])
    )
  )


  out <- getDescriptionStatsBy(
    x = mtcars$col,
    by = mtcars$am,
    header_count = "(n = %s)", # custom header
    add_total_col = TRUE,
    statistics = TRUE
  )

  expect_match(
    colnames(out)[1],
    sprintf("\\(n = %d\\)", nrow(mtcars))
  )
  expect_match(
    colnames(out)[2],
    sprintf(
      "\\(n = %d\\)",
      sum(mtcars$am == levels(mtcars$am)[1])
    )
  )
  expect_match(
    colnames(out)[3],
    sprintf(
      "\\(n = %d\\)",
      sum(mtcars$am != levels(mtcars$am)[1])
    )
  )
})

test_that("Test use_units", {
  data(mtcars)

  mtcars$am <- factor(mtcars$am, levels = 0:1, labels = c("Automatic", "Manual"))
  Hmisc::label(mtcars$am) <- "Transmission"
  set.seed(666)
  units(mtcars$mpg) <- "mpg"

  out1 <- suppressWarnings(
    getDescriptionStatsBy(
      x = mtcars$mpg,
      by = mtcars$am,
      header_count = TRUE,
      add_total_col = TRUE,
      statistics = TRUE
    )
  )

  out2 <- suppressWarnings(
    getDescriptionStatsBy(
      x = mtcars$mpg,
      by = mtcars$am,
      use_units = TRUE,
      header_count = TRUE,
      add_total_col = TRUE,
      statistics = TRUE
    )
  )

  expect_equal(ncol(out1) + 1, ncol(out2))

  out3 <- suppressWarnings(
    getDescriptionStatsBy(
      x = mtcars$mpg,
      by = mtcars$am,
      use_units = "name",
      header_count = TRUE,
      add_total_col = TRUE,
      statistics = TRUE
    )
  )
  expect_match(Hmisc::label(out3), "\\(mpg\\)")
  expect_false(grepl("\\(mpg\\)", label(out2)))
})

data("mtcars")
test_that("Non-factor variables where values are missing in only one of the by-groups", {
  table(as.character(mtcars$am), mtcars$gear)
  retAll <- getDescriptionStatsBy(
    as.character(mtcars$am), mtcars$gear,
    show_all_values = TRUE
  )
  retOne <- getDescriptionStatsBy(
    as.character(mtcars$am), mtcars$gear,
    show_all_values = FALSE
  )

  retAllRowDefault <- retAll["0", ]
  retAllRowOther <- retAll["1", ]
  # Delete label as the
  attributes(retAllRowDefault) <- NULL
  attributes(retAllRowOther) <- NULL
  attributes(retOne) <- NULL
  expect_equal(retAllRowDefault, retOne)
  expect_false(all(retAllRowOther == retOne))
})

### checks for issue #32: display of p-values for multi-row summaries
cars_missing <- mtcars
cars_missing$mpg[3] <- NA
test_that("p-values are displayed in multi-row summaries when rgroup and n.rgroup are specified", {
  expected <- structure(
    c(
      "27.1 (&plusmn;4.6)", "1 (9.1%)", "19.7 (&plusmn;1.5)",
      "0 (0%)", "15.1 (&plusmn;2.6)", "0 (0%)", "", ""
    ),
    .Dim = c(2L, 4L),
    .Dimnames = list(
      c("Mean (SD)", "Missing"),
      c("4", "6", "8", "P-value")
    ),
    rgroup = structure("Gas",
      add = structure(list(`1` = "&lt; 0.0001"),
        .Names = "1"
      )
    ),
    n.rgroup = 2,
    htmlTable_args = structure(list(), .Names = character(0)),
    class = c("descMrg", class(matrix(1)))
  )

  out <- mergeDesc(getDescriptionStatsBy(
    x = cars_missing$mpg,
    by = cars_missing$cyl,
    statistics = TRUE
  ),
  htmlTable_args = list(rgroup = c("Gas"), n.rgroup = 2)
  )
  expect_equivalent(out, expected)
})


test_that("Factors with 0 observations should be reported when show_all_values=TRUE, issue #61", {
  set.seed(1)
  n = 20
  d <- data.frame(single = sample(LETTERS[1], size = n, replace = TRUE),
                  two = sample(LETTERS[1:2], size = n, replace = TRUE),
                  three = sample(LETTERS[1:3], size = n, replace = TRUE),
                  by = sample(letters[1:2], size = n, replace = TRUE)) %>%
    mutate(across(everything(), function(x) factor(x, levels = c(unique(x), "no observation"))))

  out <- d %>%
    getDescriptionStatsBy(single,
                          two,
                          three,
                          by = by,
                          show_all_values = TRUE)
  expect_true(all(sapply(out, function(x) "no observation" %in% rownames(x))))

  out <- d %>%
    getDescriptionStatsBy(single,
                          two,
                          three,
                          by = by,
                          show_all_values = FALSE)
  expect_false("no observation" %in% rownames(out[[1]]))
  expect_true(all(sapply(out[2:3], function(x) "no observation" %in% rownames(x))))
})