rcrunch: Crunch.io Data Tools

context("Multiple response cube specialness")

##########################################
### MR x CAT
##########################################
alldims <- list(
    pdl_gender = c("Male", "Female"),
    shower_thoughts_klima_2 = c(
        "Cupcakes are the best cakes",
        "Corgis are the future of dog shows",
        "I always ride a penny-farthing",
        "I never look at eclipses",
        "I never mess with Texas",
        "I don't mind pickles on my burger"
    )
)

mr_x_cat_wt <- loadCube(test_path("cubes/selected-crosstab-4.json"))

test_that("properties of a cube with for as_selected x cat: it looks 2D", {
    expect_equal(dim(showMissing(mr_x_cat_wt)), c(6L, 3L))
    expect_equal(dim(mr_x_cat_wt), c(6, 2))
    expect_equal(
        names(dimnames(mr_x_cat_wt)),
        c("shower_thoughts_klima_2", "pdl_gender")
    )
    expect_equal(
        aliases(variables(mr_x_cat_wt)),
        c("shower_thoughts_klima_2", "pdl_gender")
    )
    expect_equal(
        names(categories(variables(mr_x_cat_wt)[[2]])),
        c("Male", "Female", "No Data")
    )
})

test_that("as.array on cube with as_selected x cat", {
    expect_equal(
        as.array(mr_x_cat_wt),
        cubify(
            9928.20954289002, 11524.821237084192,
            9588.843313998908, 9801.254016136965,
            11697.435357575358, 13095.670425525452,
            9782.8995547749, 10531.918128023966,
            4417.596222134318, 3448.380316269752,
            6179.175512581436, 6490.427474934746,
            dims = alldims[c("shower_thoughts_klima_2", "pdl_gender")]
        )
    )
})

test_that("margin.table for as_selected x cat", {
    expect_equal(
        as.array(margin.table(mr_x_cat_wt, 1)),
        cubify(
            21453.03077997421,
            19390.097330135875,
            24793.105783100807,
            20314.817682798865,
            7865.976538404069,
            12669.602987516182,
            dims = alldims["shower_thoughts_klima_2"]
        )
    )
    expect_equal(
        as.array(margin.table(mr_x_cat_wt, 2)),
        cubify(14566.261567907562, 15607.301233922663,
            14456.513325488017, 15450.609903833058,
            14415.136475733132, 15405.898678070093,
            11485.661204663904, 11912.588886491172,
            11664.69933815247, 12110.196347286023,
            11547.413553551738, 11961.575582997419,
            dims = alldims[c("shower_thoughts_klima_2", "pdl_gender")]
        )
    )
    expect_error(margin.table(mr_x_cat_wt, 3),
        "Margin 3 exceeds Cube's number of dimensions (2)",
        fixed = TRUE
    )
    ## NULL margin is the same shape as margin 1 here but is sum of selected + not
    ## Note: not based on expectation from JS tests
    expect_equal(
        as.array(margin.table(mr_x_cat_wt)),
        cubify(
            30173.5628018302,
            29907.1232293211,
            29821.0351538032,
            23398.2500911551,
            23774.8956854385,
            23508.9891365492,
            dims = alldims["shower_thoughts_klima_2"]
        )
    )
})

test_that("prop.table(row) for as_selected x cat", {
    expect_equal(
        as.array(prop.table(mr_x_cat_wt, 1)),
        cubify(
            0.4627882020361299, 0.5372117979638701,
            0.4945227014975337, 0.5054772985024663,
            0.47180193800279874, 0.5281980619972013,
            0.481564723224583, 0.5184352767754171,
            0.5616081106479636, 0.4383918893520365,
            0.48771658580541166, 0.5122834141945883,
            dims = alldims[c("shower_thoughts_klima_2", "pdl_gender")]
        )
    )
})
test_that("prop.table(col) for as_selected x cat", {
    expect_equal(
        as.array(prop.table(mr_x_cat_wt, 2)),
        cubify(
            0.6815894041587091, 0.7384249886863752,
            0.6632887957217867, 0.6343603312193796,
            0.8114689290154947, 0.8500426167391849,
            0.8517489224566737, 0.8840998567462627,
            0.3787149667617584, 0.28475015741941767,
            0.535113381358101, 0.5426064007955989,
            dims = alldims[c("shower_thoughts_klima_2", "pdl_gender")]
        )
    )
})
test_that("prop.table(cell) for as_selected x cat", {
    ## Note: not based on expectation from JS tests
    expect_equal(
        as.array(prop.table(mr_x_cat_wt)),
        cubify(
            0.329036700375595, 0.381950958618156,
            0.320620717695708, 0.327723062528721,
            0.392254504152701, 0.439142047148397,
            0.418103897371069, 0.450115632023491,
            0.185809278853744, 0.14504292098248,
            0.262843097025161, 0.27608279697761,
            dims = alldims[c("shower_thoughts_klima_2", "pdl_gender")]
        )
    )
})

##########################################
### CAT x MR
##########################################
cat_x_mr <- loadCube(test_path("cubes/selected-crosstab-array-last.json"))
cat_x_mr_dims <- dimnames(cat_x_mr)
# drop the "No Data" category in animal
cat_x_mr_dims$fruit <- cat_x_mr_dims$fruit[cat_x_mr_dims$fruit != "No Data"]


test_that("margin.table for cat x as_selected", {
    expect_equal(
        as.array(margin.table(cat_x_mr, 1)),
        cubify(
            49.3701228167475, 48.4562012457907, 56.931621579619,
            116.632067482127, 93.411479439707, 124.061990989576,
            dims = cat_x_mr_dims
        )
    )
    expect_equal(
        as.array(margin.table(cat_x_mr, 2)),
        cubify(22.9672704148528, 45.7789165449064, 86.9728287914322,
            dims = cat_x_mr_dims["zoo"]
        )
    )
    ## NULL margin is the same shape as margin 1 here but is sum of selected + not
    expect_equal(
        as.array(margin.table(cat_x_mr)),
        cubify(
            166.002190298874, 141.867680685498, 180.993612569195,
            dims = cat_x_mr_dims["zoo"]
        )
    )
})

test_that("prop.table(row) for cat x as_selected", {
    expect_equal(
        as.array(prop.table(cat_x_mr, 1)),
        cubify(
            0.17136174576676, 0.355633666090444, 0.463598595422233,
            0.124383630449479, 0.305596916163552, 0.488299506632138,
            dims = cat_x_mr_dims
        )
    )
})
test_that("prop.table(col) for cat x as_selected", {
    expect_equal(
        as.array(prop.table(cat_x_mr, 2)),
        cubify(
            0.368356808701398, 0.376432161231965, 0.303467418114167,
            0.631643191298602, 0.623567838768035, 0.696532581885833,
            dims = cat_x_mr_dims
        )
    )
})
test_that("prop.table(cell) for cat x as_selected", {
    ## Note: not based on expectation from JS tests
    expect_equal(
        as.array(prop.table(cat_x_mr)),
        cubify(
            0.0509640892048795, 0.121469924725558, 0.145825145013507,
            0.0873911359490897, 0.201217500089628, 0.334704678977833,
            dims = cat_x_mr_dims
        )
    )
})


##########################################
### CAT x MR x MR
##########################################
cat_x_mr_x_mr <- loadCube(test_path("cubes/cat-x-mr-x-mr.json"))
cat_x_mr_x_mr_dims <- dimnames(cat_x_mr_x_mr)
# drop the "No Data" category in animal
cat_x_mr_x_mr_dims$animal <- cat_x_mr_x_mr_dims$animal[cat_x_mr_x_mr_dims$animal != "No Data"]

test_that("prop.table(row) for cat x MR x MR", {
    expect_equal(
        as.array(prop.table(cat_x_mr_x_mr, 1)),
        cubify(0.1159, 0.3597,
            0.0197, 0.0604,
            0.0192, 0.0582,
            0.0159, 0.0094,
            0.1182, 0.0625,
            0.1142, 0.0623,
            dims = cat_x_mr_x_mr_dims
        )
    )
})
test_that("prop.table(col) for cat x MR x MR", {
    expect_equal(
        as.array(prop.table(cat_x_mr_x_mr, 2)),
        cubify(0.166284074605452, 0.516068866571019,
            0.0280267463366055, 0.0859297197325366,
            0.0276657060518732, 0.0838616714697406,
            0.0228120516499283, 0.0134863701578192,
            0.168160478019633, 0.0889173424384692,
            0.164553314121037, 0.0897694524495677,
            dims = cat_x_mr_x_mr_dims
        )
    )
})
test_that("prop.table(cell) for cat x MR x MR", {
    expect_equal(
        as.array(prop.table(cat_x_mr_x_mr)),
        cubify(0.05795, 0.17985,
            0.00985, 0.0302,
            0.0096, 0.0291,
            0.00795, 0.0047,
            0.0591, 0.03125,
            0.0571, 0.03115,
            dims = cat_x_mr_x_mr_dims
        )
    )
})

##########################################
### Internal function tests
##########################################

test_that("user2realMargin translates cube margins with two categoricals", {
    cat_cat <- loadCube(test_path("cubes/cat-x-cat.json"))
    expect_equal(user2realMargin(1, cube = cat_cat), 1)
    expect_equal(user2realMargin(2, cube = cat_cat), 2)
    expect_equal(user2realMargin(c(1, 2), cube = cat_cat), c(1, 2))
    expect_null(user2realMargin(NULL, cube = cat_cat))

    expect_equal(mr_items_margins(1, cube = cat_cat), 1)
    expect_equal(mr_items_margins(2, cube = cat_cat), 2)
    expect_equal(mr_items_margins(c(1, 2), cube = cat_cat), c(1, 2))
    expect_null(mr_items_margins(NULL, cube = cat_cat))

    expect_equal(real2userMargin(1, cube = cat_cat), 1)
    expect_equal(real2userMargin(2, cube = cat_cat), 2)
    expect_equal(real2userMargin(c(1, 2), cube = cat_cat), c(1, 2))
    expect_null(real2userMargin(NULL, cube = cat_cat))

    expect_equal(mr_items_margins(1, cube = cat_cat, user_dims = TRUE), 1)
    expect_equal(mr_items_margins(2, cube = cat_cat, user_dims = TRUE), 2)
    expect_equal(mr_items_margins(c(1, 2), cube = cat_cat, user_dims = TRUE), c(1, 2))
    expect_null(mr_items_margins(NULL, cube = cat_cat, user_dims = TRUE))
})

test_that("user2realMargin translates cube margins with cat by mr by mr", {
    mr_cat <- loadCube(test_path("cubes/selected-crosstab-array-first.json"))
    expect_equal(user2realMargin(1, cube = mr_cat), c(1, 2))
    expect_equal(user2realMargin(2, cube = mr_cat), 3)
    expect_equal(user2realMargin(c(1, 2), cube = mr_cat), c(1, 2, 3))
    expect_null(user2realMargin(NULL, cube = mr_cat))

    # we can include all selections
    expect_equal(mr_items_margins(1, cube = mr_cat), 1)
    expect_equal(mr_items_margins(2, cube = mr_cat), c(1, 3))
    expect_equal(mr_items_margins(c(1, 2), cube = mr_cat), c(1, 3))
    expect_equal(mr_items_margins(NULL, cube = mr_cat), 1)

    expect_equal(real2userMargin(1, cube = mr_cat), 1)
    expect_equal(real2userMargin(2, cube = mr_cat), 1)
    expect_equal(real2userMargin(3, cube = mr_cat), 2)
    expect_equal(real2userMargin(c(1, 2), cube = mr_cat), 1)
    expect_null(real2userMargin(NULL, cube = mr_cat))

    expect_equal(mr_items_margins(1, cube = mr_cat, user_dims = TRUE), 1)
    expect_equal(mr_items_margins(2, cube = mr_cat, user_dims = TRUE), c(1, 2))
    expect_equal(mr_items_margins(c(1, 2), cube = mr_cat, user_dims = TRUE), c(1, 2))
    expect_equal(mr_items_margins(NULL, cube = mr_cat, user_dims = TRUE), 1)
})

test_that("user2realMargin translates cube margins with cat by mr by mr", {
    cat_mr_mr <- loadCube(test_path("cubes/cat-x-mr-x-mr.json"))
    expect_equal(user2realMargin(1, cube = cat_mr_mr), 1)
    expect_equal(user2realMargin(2, cube = cat_mr_mr), c(2, 3))
    expect_equal(user2realMargin(c(1, 2), cube = cat_mr_mr), c(1, 2, 3))
    expect_equal(user2realMargin(3, cube = cat_mr_mr), c(4, 5))
    expect_null(user2realMargin(NULL, cube = cat_mr_mr))

    # we can include all selections
    expect_equal(mr_items_margins(1, cube = cat_mr_mr), c(1, 2, 4))
    expect_equal(mr_items_margins(2, cube = cat_mr_mr), c(2, 4))
    expect_equal(mr_items_margins(c(1, 2), cube = cat_mr_mr), c(1, 2, 4))
    expect_equal(mr_items_margins(3, cube = cat_mr_mr), c(2, 4))
    expect_equal(mr_items_margins(NULL, cube = cat_mr_mr), c(2, 4))

    expect_equal(real2userMargin(1, cube = cat_mr_mr), 1)
    expect_equal(real2userMargin(2, cube = cat_mr_mr), 2)
    expect_equal(real2userMargin(3, cube = cat_mr_mr), 2)
    expect_equal(real2userMargin(4, cube = cat_mr_mr), 3)
    expect_equal(real2userMargin(5, cube = cat_mr_mr), 3)
    expect_equal(real2userMargin(c(1, 2), cube = cat_mr_mr), c(1, 2))
    expect_equal(real2userMargin(c(3, 4), cube = cat_mr_mr), c(2, 3))
    expect_null(real2userMargin(NULL, cube = cat_mr_mr))

    expect_equal(mr_items_margins(1, cube = cat_mr_mr, user_dims = TRUE), c(1, 2, 3))
    expect_equal(mr_items_margins(2, cube = cat_mr_mr, user_dims = TRUE), c(2, 3))
    expect_equal(mr_items_margins(c(1, 2), cube = cat_mr_mr, user_dims = TRUE), c(1, 2, 3))
    expect_equal(mr_items_margins(3, cube = cat_mr_mr, user_dims = TRUE), c(2, 3))
    expect_equal(mr_items_margins(NULL, cube = cat_mr_mr, user_dims = TRUE), c(2, 3))
})

test_that("user2realMargin translates cube margins with mr by cat by mr", {
    mrcatmr_types <- c("mr_items", "mr_selections", "categorical", "mr_items", "mr_selections")
    expect_equal(user2realMargin(1, mrcatmr_types), c(1, 2))
    expect_equal(user2realMargin(2, mrcatmr_types), 3)
    expect_equal(user2realMargin(c(1, 2), mrcatmr_types), c(1, 2, 3))
    expect_equal(user2realMargin(3, mrcatmr_types), c(4, 5))
    expect_equal(user2realMargin(c(2, 3), mrcatmr_types), c(3, 4, 5))
    expect_null(user2realMargin(NULL, mrcatmr_types))

    # we can include all selections
    expect_equal(mr_items_margins(1, mrcatmr_types), c(1, 4))
    expect_equal(mr_items_margins(2, mrcatmr_types), c(1, 3, 4))
    expect_equal(mr_items_margins(c(1, 2), mrcatmr_types), c(1, 3, 4))
    expect_equal(mr_items_margins(3, mrcatmr_types), c(1, 4))
    expect_equal(mr_items_margins(c(2, 3), mrcatmr_types), c(1, 3, 4))
    expect_equal(mr_items_margins(NULL, mrcatmr_types), c(1, 4))

    expect_equal(real2userMargin(1, mrcatmr_types), 1)
    expect_equal(real2userMargin(2, mrcatmr_types), 1)
    expect_equal(real2userMargin(3, mrcatmr_types), 2)
    expect_equal(real2userMargin(4, mrcatmr_types), 3)
    expect_equal(real2userMargin(5, mrcatmr_types), 3)
    expect_equal(real2userMargin(c(1, 2), mrcatmr_types), 1)
    expect_equal(real2userMargin(c(4, 5), mrcatmr_types), 3)
    expect_equal(real2userMargin(c(2, 3, 4), mrcatmr_types), c(1, 2, 3))
    expect_null(real2userMargin(NULL, mrcatmr_types))

    # if we request non-deduplication with MRs, we get the right values
    expect_equal(real2userMargin(c(1, 2), mrcatmr_types, dedupe = FALSE), c(1, 1))
    expect_equal(real2userMargin(c(4, 5), mrcatmr_types, dedupe = FALSE), c(3, 3))
    expect_equal(real2userMargin(c(2, 3, 4), mrcatmr_types, dedupe = FALSE), c(1, 2, 3))
    expect_equal(real2userMargin(c(1, 2, 3, 4, 5), mrcatmr_types, dedupe = FALSE), c(1, 1, 2, 3, 3))
    expect_null(real2userMargin(NULL, mrcatmr_types, dedupe = FALSE))

    expect_equal(mr_items_margins(1, mrcatmr_types, user_dims = TRUE), c(1, 3))
    expect_equal(mr_items_margins(2, mrcatmr_types, user_dims = TRUE), c(1, 2, 3))
    expect_equal(mr_items_margins(c(1, 2), mrcatmr_types, user_dims = TRUE), c(1, 2, 3))
    expect_equal(mr_items_margins(3, mrcatmr_types, user_dims = TRUE), c(1, 3))
    expect_equal(mr_items_margins(c(2, 3), mrcatmr_types, user_dims = TRUE), c(1, 2, 3))
    expect_equal(mr_items_margins(NULL, mrcatmr_types, user_dims = TRUE), c(1, 3))
})

test_that("user2realMargin translates cube margins with catarray by mr", {
    ca_mr <- loadCube(test_path("cubes/catarray-x-mr.json"))
    expect_equal(user2realMargin(1, cube = ca_mr), 1)
    expect_equal(user2realMargin(2, cube = ca_mr), 2)
    expect_equal(user2realMargin(3, cube = ca_mr), c(3, 4))
    expect_equal(user2realMargin(c(1, 2), cube = ca_mr), c(1, 2))
    expect_equal(user2realMargin(3, cube = ca_mr), c(3, 4))
    expect_null(user2realMargin(NULL, cube = ca_mr))

    expect_equal(mr_items_margins(1, cube = ca_mr), c(1, 3))
    expect_equal(mr_items_margins(2, cube = ca_mr), c(2, 3))
    expect_equal(mr_items_margins(3, cube = ca_mr), 3)
    expect_equal(mr_items_margins(c(1, 2), cube = ca_mr), c(1, 2, 3))
    expect_equal(mr_items_margins(3, cube = ca_mr), 3)
    expect_equal(mr_items_margins(NULL, cube = ca_mr), 3)

    expect_equal(real2userMargin(1, cube = ca_mr), 1)
    expect_equal(real2userMargin(2, cube = ca_mr), 2)
    expect_equal(real2userMargin(3, cube = ca_mr), 3)
    expect_equal(real2userMargin(4, cube = ca_mr), 3)
    expect_equal(real2userMargin(c(1, 2), cube = ca_mr), c(1, 2))
    expect_null(real2userMargin(NULL, cube = ca_mr))

    expect_equal(mr_items_margins(1, cube = ca_mr, user_dims = TRUE), c(1, 3))
    expect_equal(mr_items_margins(2, cube = ca_mr, user_dims = TRUE), c(2, 3))
    expect_equal(mr_items_margins(3, cube = ca_mr, user_dims = TRUE), 3)
    expect_equal(mr_items_margins(c(1, 2), cube = ca_mr, user_dims = TRUE), c(1, 2, 3))
    expect_equal(mr_items_margins(3, cube = ca_mr), 3, user_dims = TRUE)
    expect_equal(mr_items_margins(NULL, cube = ca_mr, user_dims = TRUE), 3)
})

test_that("user2realMargin translates cube margins with cat by mr by mr by mr", {
    catmrmrmr_types <- c(
        "categorical", "mr_items", "mr_selections",
        "mr_items", "mr_selections", "mr_items", "mr_selections"
    )
    expect_equal(user2realMargin(1, catmrmrmr_types), 1)
    expect_equal(user2realMargin(2, catmrmrmr_types), c(2, 3))
    expect_equal(user2realMargin(c(1, 2), catmrmrmr_types), c(1, 2, 3))
    expect_equal(user2realMargin(3, catmrmrmr_types), c(4, 5))
    expect_equal(user2realMargin(c(2, 3), catmrmrmr_types), c(2, 3, 4, 5))
    expect_equal(user2realMargin(4, catmrmrmr_types), c(6, 7))
    expect_null(user2realMargin(NULL, catmrmrmr_types))

    # we can include all selections
    expect_equal(mr_items_margins(1, catmrmrmr_types), c(1, 2, 4, 6))
    expect_equal(mr_items_margins(2, catmrmrmr_types), c(2, 4, 6))
    expect_equal(mr_items_margins(c(1, 2), catmrmrmr_types), c(1, 2, 4, 6))
    expect_equal(mr_items_margins(3, catmrmrmr_types), c(2, 4, 6))
    expect_equal(mr_items_margins(4, catmrmrmr_types), c(2, 4, 6))
    expect_equal(mr_items_margins(NULL, catmrmrmr_types), c(2, 4, 6))

    expect_equal(real2userMargin(1, catmrmrmr_types), 1)
    expect_equal(real2userMargin(2, catmrmrmr_types), 2)
    expect_equal(real2userMargin(3, catmrmrmr_types), 2)
    expect_equal(real2userMargin(4, catmrmrmr_types), 3)
    expect_equal(real2userMargin(5, catmrmrmr_types), 3)
    expect_equal(real2userMargin(6, catmrmrmr_types), 4)
    expect_equal(real2userMargin(7, catmrmrmr_types), 4)
    expect_equal(real2userMargin(c(1, 2), catmrmrmr_types), c(1, 2))
    expect_equal(real2userMargin(c(2, 3), catmrmrmr_types), 2)
    expect_null(real2userMargin(NULL, catmrmrmr_types))

    expect_equal(mr_items_margins(1, catmrmrmr_types, user_dims = TRUE), c(1, 2, 3, 4))
    expect_equal(mr_items_margins(2, catmrmrmr_types, user_dims = TRUE), c(2, 3, 4))
    expect_equal(mr_items_margins(c(1, 2), catmrmrmr_types, user_dims = TRUE), c(1, 2, 3, 4))
    expect_equal(mr_items_margins(3, catmrmrmr_types, user_dims = TRUE), c(2, 3, 4))
    expect_equal(mr_items_margins(4, catmrmrmr_types, user_dims = TRUE), c(2, 3, 4))
    expect_equal(mr_items_margins(NULL, catmrmrmr_types, user_dims = TRUE), c(2, 3, 4))
})

with_mock_crunch({
    ds <- cachedLoadDataset("test ds")

    test_that("crtabs use as_selected by default", {
        expect_GET(
            crtabs(~mymrset, data = ds),
            paste0(
                "https://app.crunch.io/api/datasets/1/cube/?query=%7B%22dimensions",
                "%22%3A%5B%7B%22function%22%3A%22dimension%22%2C%22args%22%3A%5B%7B%22",
                "function%22%3A%22as_selected%22%2C%22args%22%3A%5B%7B%22variable%22%3A%22",
                "https%3A%2F%2Fapp.crunch.io%2Fapi%2Fdatasets%2F1%2Fvariables%2Fmymrset%2F",
                "%22%7D%5D%7D%2C%7B%22value%22%3A%22subvariables%22%7D%5D%7D%2C%7B%22function",
                "%22%3A%22as_selected%22%2C%22args%22%3A%5B%7B%22variable%22%3A%22https%3A%2F%2F",
                "app.crunch.io%2Fapi%2Fdatasets%2F1%2Fvariables%2Fmymrset%2F%22%7D%5D%7D%5D%2C",
                "%22measures%22%3A%7B%22count%22%3A%7B%22function%22%3A%22cube_count%22%2C%22",
                "args%22%3A%5B%5D%7D%7D%2C%22weight%22%3Anull%7D&filter=%7B%7D"
            )
        )

        expect_GET(
            crtabs(~ mymrset + location, data = ds),
            paste0(
                "https://app.crunch.io/api/datasets/1/cube/?query=%7B%22dimensions",
                "%22%3A%5B%7B%22function%22%3A%22dimension%22%2C%22args%22%3A%5B%7B%22",
                "function%22%3A%22as_selected%22%2C%22args%22%3A%5B%7B%22variable%22%3A",
                "%22https%3A%2F%2Fapp.crunch.io%2Fapi%2Fdatasets%2F1%2Fvariables%2Fmymrset",
                "%2F%22%7D%5D%7D%2C%7B%22value%22%3A%22subvariables%22%7D%5D%7D%2C%7B%22function",
                "%22%3A%22as_selected%22%2C%22args%22%3A%5B%7B%22variable%22%3A%22https%3A%2F%2F",
                "app.crunch.io%2Fapi%2Fdatasets%2F1%2Fvariables%2Fmymrset%2F%22%7D%5D%7D%2C%7B%22",
                "variable%22%3A%22https%3A%2F%2Fapp.crunch.io%2Fapi%2Fdatasets%2F1%2Fvariables%2F",
                "location%2F%22%7D%5D%2C%22measures%22%3A%7B%22count%22%3A%7B%22function%22%3A%22",
                "cube_count%22%2C%22args%22%3A%5B%5D%7D%7D%2C%22weight%22%3Anull%7D&filter=%7B%7D"
            )
        )
    })
})

with_test_authentication({
    ds <- newDatasetFromFixture("apidocs")
    test_that("as_selected in cube query", {
        cub <- as.array(crtabs(~ as_selected(allpets), data = ds))
        expect_identical(
            dimnames(cub),
            list(
                allpets = c("Cat", "Dog", "Bird")
            )
        )
    })
})