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test_that("6 different automatic lty converted to plotly's 6 types", {
d <- expand.grid(x=1:6, y=1:6)
gg <- ggplot() +
geom_line(aes(x=x, y=y, group=x, linetype=as.factor(x)), data=d)
expected <-
c("solid",
"dash",
"dot",
"dashdot",
"longdash",
"longdashdot")
info <- expect_doppelganger_built(gg, "linetype-types")
generated <- sapply(info$data[1:6], function(L) L$line$dash)
expect_true(all(generated %in% expected))
expect_true(all(expected %in% generated))
})
test_that("different colored lines become different colored traces", {
## http://stackoverflow.com/questions/2564258/plot-2-graphs-in-same-plot-in-r/19039094#19039094
## original data in a 'wide' format
x <- seq(-2, 2, 0.05)
y1 <- pnorm(x)
y2 <- pnorm(x, 1, 1)
df <- rbind(data.frame(x, variable="y1", value=y1),
data.frame(x, variable="y2", value=y2))
## plot, using the aesthetics argument 'colour'
gg <- ggplot(data = df, aes(x = x, y = value, colour = variable))+
geom_line()+
scale_color_manual(values=c(y1="blue", y2="red"))
info <- expect_doppelganger_built(gg, "linetype-colors")
expect_equivalent(length(info$data), 2)
expect_identical(info$data[[1]]$line$color, toRGB("blue"))
n <- length(x)
expect_identical(info$data[[1]]$y[1:n], y1)
expect_identical(info$data[[1]]$x[1:n], x)
expect_identical(info$data[[2]]$line$color, toRGB("red"))
expect_identical(info$data[[2]]$y[1:n], y2)
expect_identical(info$data[[2]]$x[1:n], x)
})
test_that("Milliseconds are preserved with dynamic ticks", {
d <- data.frame(
t = as.POSIXct("1970-01-01 00:00") + (0:999) / 10,
y = sin((0:999) * 4 * pi / 1000)
)
gg <- ggplot(d, aes(t, y)) + geom_line()
p <- ggplotly(gg, dynamicTicks = TRUE)
j <- plotly_json(p, jsonedit = FALSE)
t2 <- jsonlite::fromJSON(j)$data$x[[1]] %>%
as.POSIXct(format = "%Y-%m-%d %H:%M:%OS", origin = "1970-01-01 00:00:00")
expect_equal(as.numeric(mean(diff(t2))), 0.1, tolerance = 0.01)
expect_doppelganger_built(p, "line-milliseconds")
})
test_that("Translates both dates and datetimes (with dynamic ticks) correctly", {
dates <- seq(
as.Date("2002-01-01"),
by = "1 month",
length.out = 100
)
d <- data.frame(
value = rnorm(100),
date = dates
)
p <- ggplot(d, aes(date, value)) + geom_line()
l <- plotly_build(ggplotly(p, dynamicTicks = TRUE))$x
d2 <- data.frame(
value = rnorm(100),
date = as.POSIXct(dates)
)
p2 <- ggplot(d2, aes(date, value)) + geom_line()
l2 <- plotly_build(ggplotly(p2, dynamicTicks = TRUE))$x
# since these are dynamic ticks, let plotly.js generate the ticks
axisType <- with(l$layout$xaxis, list(type, tickmode, autorange))
expect_equivalent(axisType, list("date", "auto", TRUE))
axisType2 <- with(l2$layout$xaxis, list(type, tickmode, autorange))
expect_equivalent(axisType2, list("date", "auto", TRUE))
# range and data have been reverse transformed
expect_is(l$layout$xaxis$range, "Date")
expect_is(l$data[[1]]$x, "Date")
expect_is(l2$layout$xaxis$range, "POSIXct")
expect_is(l2$data[[1]]$x, "POSIXct")
# check the hovertext
dates1 <- sapply(strsplit(l$data[[1]]$text, br()), "[[", 1)
dates2 <- sapply(strsplit(l2$data[[1]]$text, br()), "[[", 1)
expect_equivalent(paste("date:", d$date), dates1)
expect_equivalent(paste("date:", d2$date), dates2)
})
test_that("geom_linerange() without a y aesthetic translates to a path", {
d <- data.frame(
x = 1:5,
ymax = 1:5,
ymin = 0
)
p <- ggplot(d, aes(x, ymax = ymax, ymin = ymin)) +
geom_linerange()
l <- plotly_build(p)$x
expect_length(l$data, 1)
expect_equivalent(l$data[[1]]$type, "scatter")
expect_equivalent(
l$data[[1]]$x,
c(1, 1, NA, 2, 2, NA, 3, 3, NA, 4, 4, NA, 5, 5)
)
expect_equivalent(
l$data[[1]]$y,
c(0, 1, NA, 0, 2, NA, 0, 3, NA, 0, 4, NA, 0, 5)
)
expect_equivalent(
unlist(l$data[[1]]$text),
c(
'x: 1<br />ymax: 1<br />ymin: 0', 'x: 1<br />ymax: 1<br />ymin: 0', NA,
'x: 2<br />ymax: 2<br />ymin: 0', 'x: 2<br />ymax: 2<br />ymin: 0', NA,
'x: 3<br />ymax: 3<br />ymin: 0', 'x: 3<br />ymax: 3<br />ymin: 0', NA,
'x: 4<br />ymax: 4<br />ymin: 0', 'x: 4<br />ymax: 4<br />ymin: 0', NA,
'x: 5<br />ymax: 5<br />ymin: 0', 'x: 5<br />ymax: 5<br />ymin: 0'
)
)
})
test_that("NA values do not cause a lot of warnings when ploting (#1299)", {
df <- data.frame(x=1:2, y=NA)
p <- plot_ly(df, x=~x, y=~y)
expect_warning(plotly_build(p), "Ignoring")
expect_failure(expect_warning(plotly_build(p), "structure"))
})
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