context("Cube subsets")

# Skip tests on windows (because they're slow and CRAN complains)
if (tolower(Sys.info()[["sysname"]]) != "windows") {
    test_that("replaceMissingWithTRUE", {
        expect_identical(
            replaceMissingWithTRUE(alist(, 1)),
            list(TRUE, 1)
        )
        expect_error(
            replaceMissingWithTRUE(alist(, non_object))[[2]],
            "object 'non_object' not found"
        )
    })

    test_that("replaceCharWithNumeric", {
        dimnames <- c("cats", "dogs", "llamas")
        expect_equal(
            replaceCharWithNumeric(dimnames, c("dogs", "cats", "llamas")),
            c(2, 1, 3)
        )
        expect_equal(
            replaceCharWithNumeric(dimnames, c("cats", "llamas"), visible = c(T, F, T)),
            c(1, 2)
        )
        expect_error(
            replaceCharWithNumeric(dimnames, c("apple", "bananas")),
            "Invalid categories: apple and bananas"
        )

        expect_error(
            replaceCharWithNumeric(dimnames, c("dogs", "dogs", "cats")),
            "Index is not unique. Cube subetting is only supported for unique indices."
        )
        expect_error(
            replaceCharWithNumeric(dimnames, c(1, 1, 1, 1)),
            "Index is not unique. Cube subetting is only supported for unique indices."
        )
        expect_error(
            replaceCharWithNumeric(
                c("cats", "cats", "cats"),
                c("cats"),
                "Duplicate categories detected, please use a numeric or logical subset."
            )
        )
    })


    test_that("translateHidden", {
        not_hidden <- c(T, T, F, F)
        expect_equal(translateHidden(1:2, not_hidden), c(1, 2))
        expect_equal(translateHidden(2:1, not_hidden), c(2, 1))
        expect_equal(translateHidden(1, not_hidden, drop = FALSE), c(1, 3, 4))
        expect_equal(translateHidden(2, not_hidden, drop = FALSE), c(2, 3, 4))

        not_hidden <- c(F, T, F, F, T, T)
        expect_equal(translateHidden(1:2, not_hidden), c(2, 5))
        expect_equal(translateHidden(c(3, 1), not_hidden), c(6, 2))
        expect_equal(translateHidden(c(3, 1, 2), not_hidden), c(6, 2, 5))
        expect_error(translateHidden(1:20, not_hidden), "Incorrect number of dimensions")

        not_hidden <- c(F, T, T)
        expect_equal(translateHidden(2, not_hidden, drop = TRUE), 3)
        expect_equal(translateHidden(2, not_hidden, drop = FALSE), c(1, 3))
        expect_equal(translateHidden(1:2, not_hidden, drop = TRUE), c(2, 3))
    })

    test_that("translate hidden handles ifAny", {
        not_hidden <- c(F, T, T, F)
        # in the ifAny case, there are some categories which are hidden, but are
        # visible because there are some cases.
        visible <- c(T, T, T, F)
        expect_equal(translateHidden(c(1, 2), not_hidden), c(2, 3))
        expect_equal(translateHidden(c(1, 2), not_hidden, vis = visible), c(1, 2))
    })



    cat_x_mr_x_mr <- loadCube(test_path("cubes/cat-x-mr-x-mr.json"))
    catarray_x_mr <- loadCube(test_path("cubes/catarray-x-mr.json"))

    test_that("subsetArrayDimension categorical dimension", {
        expected <- list(
            name = c("cats", "No Data"),
            missing = c(FALSE, TRUE),
            references = list(
                alias = "animal",
                name = "animal",
                type = "categorical",
                categories = list(
                    list(
                        numeric_value = 1L,
                        missing = FALSE,
                        id = 1L, name = "cats"
                    ),
                    list(
                        numeric_value = NULL,
                        missing = TRUE,
                        id = -1L,
                        name = "No Data"
                    )
                )
            )
        )
        expect_identical(subsetArrayDimension(cat_x_mr_x_mr@dims[[1]], 1:2, "categorical"), expected)
    })

    test_that("subsetArrayDimension MR dimension", {
        expected <- list(
            name = c("rest_opinion", "play_opinion"),
            missing = c(FALSE, FALSE),
            references = list(
                description = "",
                format = list(
                    summary = list(digits = 0L)
                ),
                subreferences = list(
                    "rest_opinion__1" = list(alias = "rest_opinion__1", name = "rest_opinion"),
                    "play_opinion__1" = list(alias = "play_opinion__1", name = "play_opinion")
                ),
                notes = "",
                name = "opinion MR",
                discarded = FALSE,
                alias = "opinion_mr",
                view = list(
                    show_counts = FALSE,
                    include_missing = FALSE,
                    column_width = NULL
                ),
                type = "subvariable_items",
                subvariables = c("food_opinion__1/", "rest_opinion__1/", "play_opinion__1/")
            )
        )
        expect_identical(subsetArrayDimension(cat_x_mr_x_mr@dims[[2]], 2:3, "mr_items"), expected)
    })

    test_that("subsetArrayDimension categorical array dimension", {
        expected <- list(
            name = c("cat_feeling"),
            missing = c(FALSE),
            references = list(
                subreferences = list(
                    "cat_feeling" = list(alias = "cat_feeling", name = "cat_feeling")
                ),
                name = "feeling CA",
                alias = "feeling_ca",
                type = "subvariable_items",
                subvariables = c("cat_feeling/", "dog_feeling/")
            )
        )
        expect_identical(subsetArrayDimension(catarray_x_mr@dims[[1]], 1, "ca_items"), expected)

        expected <- list(
            name = c("Somewhat Happy", "Neutral"),
            missing = c(FALSE, FALSE),
            references = list(
                subreferences = list(
                    "cat_feeling" = list(alias = "cat_feeling", name = "cat_feeling"),
                    "dog_feeling" = list(alias = "dog_feeling", name = "dog_feeling")
                ),
                name = "feeling CA",
                alias = "feeling_ca",
                type = "categorical",
                subvariables = c("cat_feeling/", "dog_feeling/"),
                categories = list(
                    list(
                        numeric_value = 2L,
                        id = 2L,
                        name = "Somewhat Happy",
                        missing = FALSE
                    ),
                    list(
                        numeric_value = 3L,
                        id = 3L,
                        name = "Neutral",
                        missing = FALSE
                    )
                )
            )
        )
        expect_identical(
            subsetArrayDimension(catarray_x_mr@dims[[2]], c(2:3), "ca_categories"),
            expected
        )
    })

    test_that("translateCubeIndex", {
        expect_identical(
            translateCubeIndex(cat_x_mr_x_mr, alist(1, , ), drop = FALSE),
            alist(1, , TRUE, , TRUE)
        )
        expect_identical(
            translateCubeIndex(cat_x_mr_x_mr, alist(1:2, 1:2, 1:2), drop = FALSE),
            alist(1:2, 1:2, TRUE, 1:2, TRUE)
        )
        expect_identical(
            translateCubeIndex(cat_x_mr_x_mr, alist(1:2, 1, 2), drop = FALSE),
            alist(1:2, 1, TRUE, 2, TRUE)
        )

        # MR selection entries are set to index 1 when the indicator is dropped
        expect_identical(
            translateCubeIndex(cat_x_mr_x_mr, alist(1:2, 1, 2), drop = TRUE),
            alist(1:2, 1, 1, 2, 1)
        )

        expect_identical(
            translateCubeIndex(cat_x_mr_x_mr,
                               alist(c(TRUE, FALSE, TRUE), c(TRUE, FALSE, TRUE), c(TRUE, FALSE)),
                               drop = TRUE
            ),
            alist(c(TRUE, FALSE, TRUE), c(TRUE, FALSE, TRUE), TRUE, c(TRUE, FALSE), TRUE)
        )
    })

    test_that("cube [ method errors correctly", {
        cube <- cat_x_mr_x_mr
        expect_equal(length(dim(cube)), 3)
        expect_error(
            cube[1, 2, 3, 4, 5, 6],
            paste0(
                "You must supply 3 dimensions to subset a 3 ",
                "dimensional cube; you supplied 6."
            )
        )
        err <- paste0(c(
            "Invalid subset:",
            "- At position 1 you tried to select element 3 when the dimension has 2 elements.",
            "- At position 2 you tried to select element 4 when the dimension has 3 elements."
        ),
        collapse = "\n"
        )
        expect_error(cube[3, 4, 1], err)
        expect_error(cube[rep(TRUE, 3), 4, 1], err)
        expect_silent(showMissing(cube)[3, 1, 1])
    })

    test_that("[ method for cat by cat cubes", {
        cube <- cube_withNA <- loadCube(test_path("cubes/cat-x-cat.json"))
        cube_withNA@useNA <- "always"

        subset_cube <- showMissing(cube)[1:2, ] # drop the No Data row
        expect_is(subset_cube, "CrunchCube")
        expect_equal(dim(subset_cube), c(2, 4))

        expect_equal(dim(subset_cube), c(2, 4))
        expect_equal(as.array(subset_cube), as.array(showMissing(cube))[1:2, ])

        # drop a non-missing row
        subset_cube <- cube[1, , drop = FALSE] # drop the second row (C)
        expect_is(subset_cube, "CrunchCube")
        expect_equal(dim(subset_cube), c(1, 2))

        # since the cube retains the missing dimension, it defaults behavior to
        # `drop = FALSE`, though this isn't true of the the array since only one
        # element is being selected from that dimension
        expect_equal(as.array(subset_cube), as.array(cube)[1, , drop = FALSE])

        # check that useNA doesn't impact
        subset_cube_withNA <- cube_withNA[c(1, 3), ] # drop the second row (C)
        expect_equal(as.array(subset_cube_withNA), as.array(cube_withNA)[c(1, 3), ])

        # drop, selecting a missing category on columns
        drop_cube <- cube[1:2, 1:2]
        expect_is(subset_cube, "CrunchCube")
        expect_equal(dim(drop_cube), c(2, 2))

        expect_equal(as.array(drop_cube), as.array(cube)[1:2, 1:2, drop = FALSE])

        # no drop, selecting a missing category on columns
        no_drop_cube <- cube[1, 1:2, drop = FALSE]
        expect_is(no_drop_cube, "CrunchCube")
        expect_equal(dim(no_drop_cube), c(1, 2))
        expect_equal(as.array(no_drop_cube), as.array(cube)[1, 1:2, drop = FALSE])
    })

    test_that("[ method for MR cubes", {
        cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr
        cat_x_mr_x_mr_withNA@useNA <- "always"
        # subset rows
        # drop the No Data row which is #2 here! d
        subset_cat_x_mr_x_mr <- showMissing(cat_x_mr_x_mr)[c(1, 3), , ]
        expect_is(subset_cat_x_mr_x_mr, "CrunchCube")
        expect_equal(dim(subset_cat_x_mr_x_mr), c(2, 3, 2))
        expect_equal(as.array(subset_cat_x_mr_x_mr), as.array(cat_x_mr_x_mr)[1:2, , ])

        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[c(1, 3), , ]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[c(1, 3), , ])
        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[c(1, 2), , ]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[c(1, 2), , ])

        # subset cols
        # drop the No Data row which is #2 here!
        subset_cat_x_mr_x_mr <- cat_x_mr_x_mr[, c(1, 3), ]
        expect_is(subset_cat_x_mr_x_mr, "CrunchCube")
        expect_equal(dim(showMissing(subset_cat_x_mr_x_mr)), c(3, 2, 2))

        expect_equal(as.array(subset_cat_x_mr_x_mr), as.array(cat_x_mr_x_mr)[, c(1, 3), ])

        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[, c(1, 3), ]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[, c(1, 3), ])
        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[, c(1, 2), ]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[, c(1, 2), ])

        # subset cols with drop
        subset_cat_x_mr_x_mr <- cat_x_mr_x_mr[, 3, ]
        expect_is(subset_cat_x_mr_x_mr, "CrunchCube")
        expect_equal(dim(subset_cat_x_mr_x_mr), c(2, 2))
        expect_equal(as.array(subset_cat_x_mr_x_mr), as.array(cat_x_mr_x_mr)[, 3, ])

        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[, 3, ]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[, 3, ])
        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[, 2, ]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[, 2, ])

        # subset slices
        subset_cat_x_mr_x_mr <- cat_x_mr_x_mr[, , 2]
        expect_is(subset_cat_x_mr_x_mr, "CrunchCube")
        expect_equal(dim(subset_cat_x_mr_x_mr), c(2, 3))
        expect_equal(as.array(subset_cat_x_mr_x_mr), as.array(cat_x_mr_x_mr)[, , 2])

        subset_cat_x_mr_x_mr_withNA <- cat_x_mr_x_mr_withNA[, , 2]
        expect_equal(as.array(subset_cat_x_mr_x_mr_withNA), as.array(cat_x_mr_x_mr_withNA)[, , 2])
    })

    test_that("[ method for cat array cubes", {
        cube <- cube_withNA <- loadCube(test_path("cubes/catarray-x-cat.json"))
        cube_withNA@useNA <- "always"

        # subset rows
        # drop the No Data row which is #2 here!
        subset_cube <- cube[2, , ]
        expect_is(subset_cube, "CrunchCube")
        expect_equal(dim(subset_cube), c(5, 2))
        expect_equal(as.array(subset_cube), as.array(cube)[2, , ])

        subset_cube_withNA <- cube_withNA[2, , ]
        expect_equal(as.array(subset_cube_withNA), as.array(cube_withNA)[2, , ])

        # subset cols
        subset_cube <- cube[, c(1, 3), ]
        expect_is(subset_cube, "CrunchCube")
        expect_equal(dim(subset_cube), c(2, 2, 2))
        expect_equal(as.array(subset_cube), as.array(cube)[, c(1, 3), ])

        subset_cube_withNA <- cube_withNA[, c(1, 3), ]
        expect_equal(as.array(subset_cube_withNA), as.array(cube_withNA)[, c(1, 3), ])
        subset_cube_withNA <- cube_withNA[, c(1, 2), ]
        expect_equal(as.array(subset_cube_withNA), as.array(cube_withNA)[, c(1, 2), ])

        # subset cols with drop
        subset_cube <- cube[, 3, ]
        expect_is(subset_cube, "CrunchCube")

        expect_equal(dim(subset_cube), c(2, 2))
        expect_equal(as.array(subset_cube), as.array(cube)[, 3, ])

        subset_cube_withNA <- cube_withNA[, 3, ]
        expect_equal(as.array(subset_cube_withNA), as.array(cube_withNA)[, 3, ])


        # subset slices
        subset_cube <- cube[, , 1:2]
        expect_is(subset_cube, "CrunchCube")
        expect_equal(dim(subset_cube), c(2, 5, 2))
        expect_equal(dim(showMissing(subset_cube)), c(2, 6, 2))
        expect_equal(as.array(subset_cube), as.array(cube)[, , 1:2])

        subset_cube_withNA <- cube_withNA[, , 1:2]
        expect_equal(as.array(subset_cube_withNA), as.array(cube_withNA)[, , 1:2])
    })


    test_that("subsetting with reordering works", {
        cat_x_cat <- loadCube(test_path("cubes/cat-x-cat.json"))
        expect_equal(as.array(cat_x_cat[c(2, 1), ]), as.array(cat_x_cat)[c(2, 1), ])
        expect_equal(as.array(cat_x_cat[c(2, 1), c(2, 1)]), as.array(cat_x_cat)[c(2, 1), c(2, 1)])

        catarray_x_mr <- loadCube(test_path("cubes/catarray-x-mr.json"))
        expect_equal(
            as.array(catarray_x_mr[c(2, 1), , ]),
            as.array(catarray_x_mr)[c(2, 1), , ]
        )
        expect_equal(
            as.array(catarray_x_mr[, , c(3, 1, 2)]),
            as.array(catarray_x_mr)[, , c(3, 1, 2)]
        )
        expect_equal(
            as.array(catarray_x_mr[, 5:2, ]),
            as.array(catarray_x_mr)[, 5:2, ]
        )

        expect_equal(
            as.array(catarray_x_mr[, 5:2, ]),
            as.array(catarray_x_mr)[, 5:2, ]
        )
        expect_equal(
            as.array(catarray_x_mr[2:1, c("Extremely Happy", "Somewhat Happy"), 1:2]),
            as.array(catarray_x_mr)[2:1, c("Extremely Happy", "Somewhat Happy"), 1:2]
        )
        catarray_x_mr_ifany <- catarray_x_mr
        expect_equal(
            as.array(catarray_x_mr_ifany[2:1, 2:3, 1:2]),
            as.array(catarray_x_mr_ifany)[2:1, 2:3, 1:2]
        )
    })

    test_that("subsetting works when @useNA == 'ifany'", {
        cube <- loadCube("cubes/univariate-categorical.json")
        expect_equal(dim(cube), 2)
        cube_ifany <- showIfAny(cube)
        expect_equal(dim(cube_ifany), 3)
        expect_equal(as.array(cube_ifany[1]), as.array(cube_ifany)[1])
        expect_equal(as.array(cube_ifany[1:2]), as.array(cube_ifany)[1:2])

        # multivariate
        cube <- loadCube("cubes/cat-x-cat.json")
        expect_equal(dim(cube), c(2, 2))
        cube_ifany <- showIfAny(cube)
        expect_equal(dim(cube_ifany), c(2, 3))
        expect_equal(as.array(cube_ifany[1:2, ]), as.array(cube_ifany)[1:2, ])
        expect_equal(as.array(cube_ifany[1:2, 1]), as.array(cube_ifany)[1:2, 1])

        # make sure hidden categories are not displayed when output is a vector
        expect_equal(as.array(cube_ifany[1, ]), as.array(cube_ifany)[1, ])
        expect_equal(as.array(cube[1, ]), as.array(cube)[1, ])
    })


    test_that("[ method with variables because `eval` needs the right frame", {
        cube <- cube_withNA <- loadCube("cubes/cat-x-cat.json")

        x <- 1
        y <- 2
        subset_cube <- cube[, c(x, y)] # drop the No Data row
        expect_equal(as.array(subset_cube), as.array(cube)[, c(1, 2)])

        inside_function <- function() {
            x_new <- 1
            y_new <- 2
            return(cube[, c(x_new, y_new)])
        }
        expect_equal(as.array(inside_function()), as.array(cube)[, c(1, 2)])
    })
}