test_that("plotting works", { set.seed(1) xy <- SLOPE:::randomProblem(100, 5) # one parameter fit <- SLOPE(xy$x, xy$y, alpha = 0.2) expect_silent(dont_plot(fit)) # more parameters fit <- SLOPE(xy$x, xy$y, path_length = 100) expect_silent(dont_plot(fit)) }) test_that("plot.SLOPE works as expected", { fit <- SLOPE(heart$x, heart$y) expect_silent(dont_plot(fit)) expect_silent(dont_plot( fit, intercept = TRUE, x_variable = "deviance_ratio" )) fit <- SLOPE(wine$x, wine$y, family = "multinomial") expect_silent(dont_plot(fit)) }) test_that("plot.trainedSLOPE works as expected", { set.seed(123) tune <- cvSLOPE( subset(mtcars, select = c("mpg", "drat", "wt")), mtcars$hp, q = c(0.1, 0.2), n_folds = 10 ) expect_silent(dont_plot(tune, ci_col = "salmon")) tune <- cvSLOPE( subset(mtcars, select = c("mpg", "drat", "wt")), mtcars$hp, q = 0.4, n_folds = 10 ) expect_silent(dont_plot(tune, ci_col = "salmon")) })