context("Scales")
test_that("buidling a plot does not affect its scales", {
dat <- data.frame(x = rnorm(20), y = rnorm(20))
p <- ggplot(dat, aes(x, y)) + geom_point()
expect_equal(length(p$scales$scales), 0)
ggplot_build(p)
expect_equal(length(p$scales$scales), 0)
})
test_that("ranges update only for variables listed in aesthetics", {
sc <- scale_alpha()
sc$train_df(data.frame(alpha = 1:10))
expect_equal(sc$range$range, c(1, 10))
sc$train_df(data.frame(alpha = 50))
expect_equal(sc$range$range, c(1, 50))
sc$train_df(data.frame(beta = 100))
expect_equal(sc$range$range, c(1, 50))
sc$train_df(data.frame())
expect_equal(sc$range$range, c(1, 50))
})
test_that("mapping works", {
sc <- scale_alpha(range = c(0, 1), na.value = 0)
sc$train_df(data.frame(alpha = 1:10))
expect_equal(
sc$map_df(data.frame(alpha = 1:10))[[1]],
seq(0, 1, length.out = 10)
)
expect_equal(sc$map_df(data.frame(alpha = NA))[[1]], 0)
expect_equal(
sc$map_df(data.frame(alpha = c(-10, 11)))[[1]],
c(0, 0))
})
test_that("identity scale preserves input values", {
df <- data.frame(
x = 1:3, z = letters[1:3],
stringsAsFactors=TRUE)
p1 <- ggplot(df,
aes(x, z, colour = z, fill = z, shape = z, size = x, alpha = x)) +
geom_point() +
scale_colour_identity() +
scale_fill_identity() +
scale_shape_identity() +
scale_size_identity() +
scale_alpha_identity()
d1 <- layer_data(p1)
expect_equal(d1$colour, as.character(df$z))
expect_equal(d1$fill, as.character(df$z))
expect_equal(d1$shape, as.character(df$z))
expect_equal(d1$size, as.numeric(df$z))
expect_equal(d1$alpha, as.numeric(df$z))
})
test_that("position scales updated by all position aesthetics", {
df <- data.frame(x = 1:3, y = 1:3)
aesthetics <- list(
aes(xend = x, yend = x),
aes(xmin = x, ymin = x),
aes(xmax = x, ymax = x),
aes(xintercept = x, yintercept = y)
)
base <- ggplot(df, aes(x = 1, y = 1)) + geom_point()
plots <- lapply(aesthetics, function(x) base %+% x)
ranges <- lapply(plots, pranges)
lapply(ranges, function(range) {
expect_equal(range$x[[1]], c(1, 3))
expect_equal(range$y[[1]], c(1, 3))
})
})
test_that("position scales generate after stats", {
df <- data.frame(x = factor(c(1, 1, 1)))
plot <- ggplot(df, aes(x)) + geom_bar()
ranges <- pranges(plot)
expect_equal(ranges$x[[1]], c("1"))
expect_equal(ranges$y[[1]], c(0, 3))
})
test_that("oob affects position values", {
dat <- data.frame(
x = c("a", "b", "c"),
y = c(1, 5, 10),
stringsAsFactors=TRUE)
base <- ggplot(dat, aes(x, y)) +
geom_bar(stat = "identity") +
annotate("point", x = "a", y = c(-Inf, Inf))
y_scale <- function(limits, oob = scales::censor) {
scale_y_continuous(limits = limits, oob = oob, expand = c(0, 0))
}
base + scale_y_continuous(limits = c(-0,5))
expect_warning({
low_censor <- cdata(
base + y_scale(c(0, 5), scales::censor))
}, "Removed 1 rows containing missing values")
expect_warning({
mid_censor <- cdata(
base + y_scale(c(3, 7), scales::censor))
}, "Removed 2 rows containing missing values")
low_squish <- cdata(base + y_scale(c(0, 5), scales::squish))
mid_squish <- cdata(base + y_scale(c(3, 7), scales::squish))
# Points are always at the top and bottom
expect_equal(low_censor[[2]]$y, c(0, 1))
expect_equal(mid_censor[[2]]$y, c(0, 1))
expect_equal(low_squish[[2]]$y, c(0, 1))
expect_equal(mid_squish[[2]]$y, c(0, 1))
# Bars depend on limits and oob
expect_equal(low_censor[[1]]$y, c(0.2, 1))
expect_equal(mid_censor[[1]]$y, c(0.5))
expect_equal(low_squish[[1]]$y, c(0.2, 1, 1))
expect_equal(mid_squish[[1]]$y, c(0, 0.5, 1))
})
test_that("scales looked for in appropriate place", {
xlabel <- function(x) ggplot_build(x)$panel$x_scales[[1]]$name
p0 <- qplot(mpg, wt, data = mtcars) + scale_x_continuous("0")
expect_equal(xlabel(p0), "0")
scale_x_continuous <- function(...) animint2::scale_x_continuous("1")
p1 <- qplot(mpg, wt, data = mtcars)
expect_equal(xlabel(p1), "1")
f <- function() {
scale_x_continuous <- function(...) animint2::scale_x_continuous("2")
qplot(mpg, wt, data = mtcars)
}
p2 <- f()
expect_equal(xlabel(p2), "2")
rm(scale_x_continuous)
p4 <- qplot(mpg, wt, data = mtcars)
expect_equal(xlabel(p4), waiver())
})
test_that("find_global searches in the right places", {
testenv <- new.env(parent = globalenv())
# This should find the scale object in the package environment
expect_identical(find_global("scale_colour_hue", testenv),
scale_colour_hue)
# Set an object with the same name in the environment
testenv$scale_colour_hue <- "foo"
# Now it should return the new object
expect_identical(find_global("scale_colour_hue", testenv), "foo")
# If we search in the empty env, we should end up with the object
# from the ggplot2 namespace
expect_identical(find_global("scale_colour_hue", emptyenv()),
scale_colour_hue)
})
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