Build cost matrix for matching — build_cost

This is the main entry point for distance computation.

Usage

build_cost_matrix(
  left,
  right,
  vars,
  distance = "euclidean",
  weights = NULL,
  scale = FALSE,
  sigma = NULL,
  memory_mode = "auto",
  caller_supports_lazy = TRUE
)

Arguments

memory_mode: One of "auto" (default), "dense", or "lazy". "auto" warns (or, when the caller supports it, switches) when the dense matrix would consume a large fraction of free system RAM. memory_mode = "lazy" returns a lazy_cost_spec instead of a matrix when the calling path and distance metric support it (built-in metrics via assignment() with method = "jv"/"auction"); otherwise it errors clearly rather than silently falling back to dense.
caller_supports_lazy: Whether the calling code path can actually consume a lazy_cost_spec result. Defaults to TRUE; callers whose downstream solve path has not been made lazy-aware (e.g. full_match(), which uses an entirely different min-cost-flow backend) pass FALSE so memory_mode = "auto" never promotes to lazy for them, and an explicit memory_mode = "lazy" request errors clearly instead of returning a lazy_cost_spec the caller cannot use.

Value

Numeric matrix of distances with optional scaling/weights applied.