expect_names <- c(
    "folds_list",
    "k",
    "column",
    "size",
    "presence_bg",
    "records"
)


pa_data <- sf::st_as_sf(
    read.csv(system.file("extdata/", "species.csv", package = "blockCV")),
    coords = c("x", "y"),
    crs = 7845
)
pa_data <- pa_data[1:200, ]

test_that("test that cv_buffer function works properly with presence-absence data",
          {
              bloo <- cv_buffer(
                  x = pa_data,
                  column = "occ",
                  size = 250000,
                  presence_bg = FALSE,
                  progress = TRUE
              )

              expect_true(exists("bloo"))
              expect_s3_class(bloo, "cv_buffer")
              expect_equal(names(bloo), expect_names)
              expect_equal(length(bloo$folds_list), nrow(pa_data))
              expect_type(bloo$folds_list, "list")
              expect_type(bloo$k, "integer")
              expect_type(bloo$column, "character")
              expect_type(bloo$size, "double")
              expect_equal(bloo$presence_bg, FALSE)
              expect_equal(dim(bloo$records), c(nrow(pa_data), 4))
              expect_true(!all(bloo$records == 0))

          })


test_that("test that cv_buffer function works properly with presence-background data",
          {
              bloo <- cv_buffer(
                  x = pa_data,
                  column = "occ",
                  size = 250000,
                  presence_bg = TRUE,
                  progress = FALSE
              )

              expect_true(exists("bloo"))
              expect_s3_class(bloo, "cv_buffer")
              expect_equal(names(bloo), expect_names)
              expect_equal(length(bloo$folds_list), sum(pa_data$occ))
              expect_type(bloo$folds_list, "list")
              expect_type(bloo$k, "integer")
              expect_type(bloo$column, "character")
              expect_type(bloo$size, "double")
              expect_equal(bloo$presence_bg, TRUE)
              expect_equal(dim(bloo$records), c(sum(pa_data$occ), 4))
              expect_true(!all(bloo$records == 0))

          })

test_that("test that cv_buffer function works properly with no species specified",
          {
              bloo <- cv_buffer(
                  x = pa_data,
                  size = 250000
              )

              expect_true(exists("bloo"))
              expect_s3_class(bloo, "cv_buffer")
              expect_equal(names(bloo), expect_names)
              expect_equal(length(bloo$folds_list), nrow(pa_data))
              expect_type(bloo$folds_list, "list")
              expect_type(bloo$k, "integer")
              expect_null(bloo$species)
              expect_type(bloo$size, "double")
              expect_equal(bloo$presence_bg, FALSE)
              expect_equal(dim(bloo$records), c(nrow(pa_data), 2))
              expect_true(!all(bloo$records == 0))

              expect_output(print(bloo), "blockCV cv_buffer")
              expect_output(summary(bloo))

          })


test_that("test cv_buffer function with no matching species column", {
    expect_warning(
        bloo <- cv_buffer(
            x = pa_data,
            column = "response",
            size = 250000,
            presence_bg = FALSE,
            progress = TRUE
        )
    )

    expect_true(exists("bloo"))
    expect_equal(dim(bloo$records), c(nrow(pa_data), 2))
    expect_true(!all(bloo$records == 0))

})

test_that("test cv_buffer function with no spatial column data", {
    expect_error(
        cv_buffer(
            x = "pa_data",
            size = 250000
        )
    )

})

test_that("test cv_buffer function to have sptial points with no CRS", {
    sf::st_crs(pa_data) <- NA

    expect_error(
        cv_buffer(
            x = pa_data,
            column = "occ",
            size = 250000
        )
    )

})

test_that("cv_buffer bins a continuous column into quantiles in the report", {
    cont_data <- pa_data
    set.seed(301)
    cont_data$biomass <- stats::rnorm(nrow(cont_data))

    bloo <- cv_buffer(
        x = cont_data,
        column = "biomass",
        size = 250000,
        presence_bg = FALSE,
        num_bins = 4,
        progress = FALSE
    )

    expect_equal(
        names(bloo$records),
        c(paste0("train_Q", 1:4), paste0("test_Q", 1:4))
    )
    bins <- attr(bloo$records, "column_bins")
    expect_equal(nrow(bins), 4)
    expect_equal(attr(bins, "requested_bins"), 4L)

})