
library(testthat)

source("user_code.R")
library(testthat)

source("user_code.R")
test_that("scatter_plot_custom creates a plot with correct points", {
    x <- c(1, 2, 3, 4, 5)
    y <- c(2, 4, 6, 8, 10)
    expect_silent(scatter_plot_custom(x, y, "red", 16))
})

test_that("scatter_plot_custom uses the correct color", {
    x <- c(1, 2, 3, 4, 5)
    y <- c(2, 4, 6, 8, 10)
    # Open a new plot device to capture parameters
    grDevices::pdf(NULL)
    scatter_plot_custom(x, y, "green", 15)
    col_used <- as.character(par("col"))
    grDevices::dev.off()
    expect_true(col_used == "green" || col_used == "#00FF00", info = "Point color should be set to green.")
})

test_that("scatter_plot_custom uses the correct point shape", {
    x <- c(1, 2, 3, 4, 5)
    y <- c(2, 4, 6, 8, 10)
    grDevices::pdf(NULL)
    scatter_plot_custom(x, y, "black", 17)
    pch_used <- par("pch")
    grDevices::dev.off()
    expect_equal(pch_used, 17, info = "Point shape should be set to 17.")
})

test_main.R

Master the foundational techniques of data visualization in R. This course guides you through the most important plotting tools and concepts, helping you create clear, insightful, and publication-ready graphics using base R and popular visualization approaches.

Explore the essential plotting tools and visualization strategies in R, focusing on practical skills for creating and customizing a wide range of charts and graphs.

Challenge: Scatter Plots

Ratkaisu