context("stat_sum")
test_that("handles grouping correctly", {
d <- diamonds[1:1000, ]
all_ones <- function(x) all.equal(mean(x), 1)
base <- ggplot(d, aes(cut, clarity))
ret <- layer_data(base + stat_sum())
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), nrow(d))
expect_true(all_ones(ret$prop))
ret <- layer_data(base + stat_sum(aes(group = 1)))
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), nrow(d))
expect_equal(sum(ret$prop), 1)
ret <- layer_data(base + stat_sum(aes(group = cut)))
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), nrow(d))
expect_true(all_ones(tapply(ret$prop, ret$x, FUN = sum)))
ret <- layer_data(base + stat_sum(aes(group = cut, colour = cut)))
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), nrow(d))
expect_true(all_ones(tapply(ret$prop, ret$x, FUN = sum)))
ret <- layer_data(base + stat_sum(aes(group = clarity)))
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), nrow(d))
expect_true(all_ones(tapply(ret$prop, ret$y, FUN = sum)))
ret <- layer_data(base + stat_sum(aes(group = clarity, colour = cut)))
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), nrow(d))
expect_true(all_ones(tapply(ret$prop, ret$y, FUN = sum)))
ret <- layer_data(base + stat_sum(aes(group = 1, weight = price)))
expect_equal(nrow(ret), 38)
expect_equal(sum(ret$n), sum(d$price))
expect_equal(sum(ret$prop), 1)
})
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