context("Scatter plots")
test_that("Colour by works", {
expect_is(
iNZightPlot(Sepal.Width, Sepal.Length,
colby = Species, data = iris,
plot = FALSE),
"inzplotoutput"
)
expect_is(
iNZightPlot(Sepal.Width, Sepal.Length,
colby = Petal.Length, data = iris,
plot = FALSE),
"inzplotoutput"
)
expect_is(
iNZightPlot(Sepal.Width, Sepal.Length,
colby = Petal.Length, col.method = "rank", data = iris,
plot = FALSE),
"inzplotoutput"
)
})
test_that("Adding inference information", {
p <- iNZightPlot(Sepal.Width, Sepal.Length, data = iris,
trend = c("linear", "quadratic", "cubic"),
inference.type = "conf",
plot = FALSE
)
expect_is(p, "inzplotoutput")
p <- iNZightPlot(Sepal.Width, Sepal.Length, data = iris,
colby = Species,
trend = "linear",
trend.by = TRUE, trend.parallel = FALSE,
inference.type = "conf",
plot = FALSE
)
expect_is(p, "inzplotoutput")
p <- iNZightPlot(Sepal.Width, Sepal.Length, data = iris,
colby = Species,
trend = "linear",
trend.by = TRUE, trend.parallel = TRUE,
inference.type = "conf",
plot = FALSE
)
expect_is(p, "inzplotoutput")
p <- iNZightPlot(Sepal.Width, Sepal.Length, data = iris,
trend = "linear",
inference.type = "conf",
bs.inference = TRUE,
plot = FALSE
)
expect_is(p, "inzplotoutput")
p <- iNZightPlot(Sepal.Width, Sepal.Length, data = iris,
colby = Species,
trend = "linear",
trend.by = TRUE, trend.parallel = FALSE,
inference.type = "conf",
bs.inference = TRUE,
plot = FALSE
)
expect_is(p, "inzplotoutput")
p <- iNZightPlot(Sepal.Width, Sepal.Length, data = iris,
colby = Species,
trend = "linear",
trend.by = TRUE, trend.parallel = TRUE,
inference.type = "conf",
bs.inference = TRUE,
plot = FALSE
)
expect_is(p, "inzplotoutput")
})
test_that("Scatter plot with single unique x/y value", {
d <- data.frame(x = rep(10, 10), y = rnorm(10))
expect_is(inzplot(y ~ x, data = d, plot = FALSE), "inzplotoutput")
expect_is(inzplot(x ~ y, data = d, plot = FALSE), "inzplotoutput")
})
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