Nothing
local({
d <- mfrmr:::sample_mfrm_data(seed = 2026)
.marg_fit <<- suppressWarnings(
fit_mfrm(
d,
"Person",
c("Rater", "Task", "Criterion"),
"Score",
method = "MML",
model = "RSM",
quad_points = 7,
maxit = 30
)
)
.marg_diag <<- diagnose_mfrm(.marg_fit, residual_pca = "none", diagnostic_mode = "both")
.marg_diag_legacy <<- diagnose_mfrm(.marg_fit, residual_pca = "none", diagnostic_mode = "legacy")
})
with_null_device_local <- function(expr) {
grDevices::pdf(NULL)
on.exit(grDevices::dev.off(), add = TRUE)
testthat::expect_gt(grDevices::dev.cur(), 1)
value <- force(expr)
invisible(value)
}
test_that("plot_marginal_fit returns reusable plot payload", {
p <- plot_marginal_fit(.marg_diag, draw = FALSE, preset = "publication")
p_prop <- plot_marginal_fit(.marg_fit, diagnostics = .marg_diag, plot_type = "prop_diff", draw = FALSE)
expect_s3_class(p, "mfrm_plot_data")
expect_identical(p$name, "marginal_fit")
expect_identical(as.character(p$data$preset), "publication")
expect_true(all(c(
"plot", "table", "full_table", "summary", "facet_summary",
"step_summary", "guidance", "thresholds",
"title", "subtitle", "legend", "reference_lines"
) %in% names(p$data)))
expect_gt(nrow(p$data$table), 0)
expect_s3_class(p_prop, "mfrm_plot_data")
expect_identical(as.character(p_prop$data$plot), "prop_diff")
})
test_that("plot_marginal_pairwise returns reusable plot payload", {
p <- plot_marginal_pairwise(.marg_diag, draw = FALSE, preset = "publication")
p_adj <- plot_marginal_pairwise(
.marg_fit,
diagnostics = .marg_diag,
metric = "adjacent",
facet = "Rater",
draw = FALSE
)
expect_s3_class(p, "mfrm_plot_data")
expect_identical(p$name, "marginal_pairwise")
expect_identical(as.character(p$data$preset), "publication")
expect_true(all(c(
"plot", "table", "full_table", "summary", "pair_stats",
"guidance", "thresholds", "title", "subtitle",
"legend", "reference_lines"
) %in% names(p$data)))
expect_gt(nrow(p$data$table), 0)
expect_s3_class(p_adj, "mfrm_plot_data")
expect_identical(as.character(p_adj$data$plot), "adjacent")
expect_true(all(as.character(p_adj$data$table$Facet) == "Rater"))
})
test_that("plot_marginal helpers require strict marginal diagnostics", {
expect_error(
plot_marginal_fit(.marg_diag_legacy, draw = FALSE),
"Strict marginal diagnostics are not available",
fixed = TRUE
)
expect_error(
plot_marginal_pairwise(.marg_diag_legacy, draw = FALSE),
"Strict marginal diagnostics are not available",
fixed = TRUE
)
})
test_that("plot_marginal helpers draw on a null graphics device", {
p_fit <- with_null_device_local(
plot_marginal_fit(.marg_diag, draw = TRUE)
)
p_pair <- with_null_device_local(
plot_marginal_pairwise(.marg_diag, metric = "adjacent", draw = TRUE)
)
expect_s3_class(p_fit, "mfrm_plot_data")
expect_s3_class(p_pair, "mfrm_plot_data")
})
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