Creates a validated benchmark object that is consumed by simulations, refinement runs, and benchmarking utilities. All fields are aligned by spot index, so every function in the package sees the same coordinates, labels, and optional evaluation masks.
Usage
spatial_benchmark(
xy,
labels,
truth,
samples = NULL,
boundary = NULL,
regions = NULL,
sparse = NULL,
name = NULL,
metadata = list()
)Arguments
- xy
Numeric matrix containing two or three spatial coordinates per observation.
- labels
Initial cluster assignments.
- truth
Reference assignments used only for evaluation.
- samples
Optional tissue or section identifier.
- boundary
Optional logical vector marking boundary observations.
- regions
Optional region identifier used for defining sparse-versus-dense accuracy when `sparse` is not supplied.
- sparse
Optional logical vector marking a user-provided sparse subset.
- name
Optional benchmark name.
- metadata
Optional named list with provenance or scenario information.
Examples
sim <- simulate_spatial_domains(n = 500, pattern = "jagged_stripes")
bench <- spatial_benchmark(
sim$xy, sim$labels, sim$truth, sim$samples,
boundary = sim$boundary, regions = sim$region
)