context("stat_summary_xy")

library(ggplot2)

test_that("stat_summary_xy", {
  tst.df <- data.frame(
    x = c(2.2, -0.2, -0.2, -2.5, -0.6, -0.1),
    y = c(1.1, -0.6, -0.9, -1.6, 0.3, 1.6),
    group = c("A", "A", "A", "B", "B", "B")
  )
  tst.df.na <- data.frame(
    x = c(2.2, -0.2, -0.2, -2.5, -0.6, 1.1, 0.1),
    y = c(1.1, -0.6, -0.9, -1.6, 0.3, 1.6, 1.6),
    group = c("A", "A", "A", "B", "B", "B", "B")
  )
  result <- ggplot(tst.df, aes(x, y)) +
    stat_summary_xy(.fun.x = mean)
  result <- ggplot2::layer_data(result)
  result <- result$x
  expected <- mean(tst.df$x)
  expect_identical(result, expected)

  result <- ggplot(tst.df, aes(x, y)) +
    stat_summary_xy(.fun.y = mean_se)
  result <- ggplot2::layer_data(result)
  result <- result[, c("y", "ymin", "ymax")]
  expected <- mean_se(tst.df$y)
  expect_identical(result, expected)

  result <- ggplot(tst.df, aes(x, y)) +
    stat_summary_xy(.fun.x = min)
  result <- ggplot2::layer_data(result)
  result <- result$x
  expected <- min(tst.df$x)
  expect_identical(result, expected)

  result <- ggplot(tst.df.na, aes(x, y)) +
    stat_summary_xy(
      .fun.y = mean,
      .fun.x = mean,
      .fun.y.args = list(na.rm = TRUE),
      .fun.x.args = list(na.rm = TRUE)
    )
  result <- ggplot2::layer_data(result)
  result <- result[, c("x", "y")]
  expected <- as.data.frame(lapply(na.omit(tst.df.na[, c("x", "y")]), mean, na.rm = TRUE))
  expect_identical(result, expected)

  function_passed <- "mean_se"
  result <- ggplot(tst.df, aes(x, y)) +
    stat_summary_xy(.fun.y = function_passed)
  result <- ggplot2::layer_data(result)
  result <- result[, c("y", "ymin", "ymax")]
  expected <- mean_se(tst.df$y)
  expect_identical(result, expected)

  result <- ggplot(tst.df, aes(x, y)) +
    stat_summary_xy(.fun.y = function(x) mean(x))
  result <- ggplot2::layer_data(result)
  result <- result$y
  expected <- mean(tst.df$y)
  expect_identical(result, expected)
})

# could do with additional tests
test_that("stat_apply_group", {
  tst.df <- data.frame(
    x = c(2.2, -0.2, -0.2, -2.5, -0.6, -0.1),
    y = c(1.1, -0.6, -0.9, -1.6, 0.3, 1.6),
    group = c("A", "A", "A", "B", "B", "B")
  )
  result <- ggplot(tst.df, aes(x, y, group = group)) +
    stat_apply_group(.fun.x = mean)
  result <- ggplot2::layer_data(result)
  result <- result$x
  expected <- c(mean(tst.df$x[1:3]), mean(tst.df$x[4:6]))
  expect_identical(result, expected)

  result <- ggplot(tst.df, aes(x, y, group = group)) +
    stat_apply_group(.fun.x = min)
  result <- ggplot2::layer_data(result)
  result <- result$x
  expected <- c(min(tst.df$x[1:3]), min(tst.df$x[4:6]))
  expect_identical(result, expected)

})