Compute the Venn region map for a [`VennDataset-class`] and bind it to a model.
Arguments
- dataset
A [`VennDataset-class`] (from one of the `load_*` functions).
- model
Model identifier. `"auto"` picks the canonical model for the dataset's set count (alphabetical first match), e.g. 4 sets -> `venn-4-set`. `"proportional"` requests an area-proportional layout (only supports 2-3 sets, added in Phase 3). Otherwise pass an explicit name from [list_models()].
Value
A [`RegionResult-class`] with the per-region item membership, set sizes, and (lazily) `statistics(result)`.
Examples
ds <- methods::new("VennDataset",
set_names = c("A", "B"),
items = list(A = c("x", "y"), B = c("y", "z")),
item_order = c("x", "y", "z"),
universe_size = 10L, source_path = NULL, format = "csv")
result <- analyze(ds)
result@model
#> [1] "venn-2-set"
# \donttest{
ds <- load_sample("dataset_real_cancer_drivers_4")
result <- analyze(ds, model = "auto")
result@model
#> [1] "venn-4-set"
# }