tests/testthat/test-plot.R

In ggeffects: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

if (suppressWarnings(
  requiet("testthat") &&
  requiet("ggeffects") &&
  requiet("sjlabelled") &&
  requiet("sjmisc")
)) {
  # lm, linear regression ----

  data(efc, package = "ggeffects")
  efc$c172code <- to_label(efc$c172code)
  fit <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc)

  test_that("ggpredict, lm", {
    pr <- ggpredict(fit, "c12hour [20,30,40]")
    p <- suppressWarnings(plot(pr))
    p <- suppressWarnings(plot(pr, ci = FALSE))
    p <- suppressWarnings(plot(pr, ci = TRUE, ci.style = "dot"))
    p <- suppressWarnings(plot(pr, add.data = TRUE))
    p <- suppressWarnings(plot(pr, add.data = TRUE, jitter = FALSE))
    p <- suppressWarnings(plot(pr, colors = "bw"))
    p <- suppressWarnings(plot(pr, colors = "gs"))

    pr <- ggpredict(fit, c("c12hour", "c172code"))
    p <- suppressWarnings(plot(pr))
    p <- suppressWarnings(plot(pr, ci = FALSE))
    p <- suppressWarnings(plot(pr, ci = TRUE, ci.style = "dot"))
    p <- suppressWarnings(plot(pr, add.data = TRUE))
    p <- suppressWarnings(plot(pr, add.data = TRUE, jitter = 0))
    p <- suppressWarnings(plot(pr, facets = TRUE))
    p <- suppressWarnings(plot(pr, facets = FALSE))
    p <- suppressWarnings(plot(pr, use.theme = FALSE))
    p <- suppressWarnings(plot(pr, colors = "bw"))
    p <- suppressWarnings(plot(pr, colors = "gs"))
  })

  test_that("plot, correct x-labels order for character vector", {
    d_char <- data.frame(
      x = c("low", "low", "high", "high"),
      y = c(0, 1, 10, 12),
      stringsAsFactors = FALSE
    )
    m_char <- lm(y ~ x, data = d_char)
    preds <- ggpredict(m_char, terms = "x [all]")
    expect_identical(
      attributes(preds)$x.axis.labels,
      c("high", "low")
    )

    preds <- ggpredict(m_char, terms = "x")
    expect_identical(
      attributes(preds)$x.axis.labels,
      c("low", "high")
    )

    d_char <- data.frame(
      x = factor(c("low", "low", "high", "high")),
      y = c(0, 1, 10, 12),
      stringsAsFactors = FALSE
    )
    m_char <- lm(y ~ x, data = d_char)
    preds <- ggpredict(m_char, terms = "x [all]")
    expect_identical(
      attributes(preds)$x.axis.labels,
      c("high", "low")
    )
  })
}