`misf.geodesic.kk()` runs a multiscale MISF-based geodesic-KK pipeline. It solves the top MISF graph with either full GKK or sparse LGKK, inserts lower-level vertices with the existing MISF placement helpers, refines each active MISF level under a GKK/LGKK objective, and finishes with a final full-graph polish.
misf.geodesic.kk(
prepared = NULL,
edges = NULL,
n = NULL,
adj_list = NULL,
weight_list = NULL,
edge_weights = NULL,
tie_mode = NULL,
num_init = 24L,
num_nbrs = 20L,
dim = NULL,
top_level_pair_mode = NULL,
top_level_full_limit = NULL,
top_level_local_nbrs = NULL,
top_level_landmark_count = NULL,
top_level_restarts = NULL,
top_level_max_iter = NULL,
top_level_init = NULL,
insertion_anchor_policy = NULL,
insertion_anchor_count = NULL,
insertion_anchor_weight_mode = NULL,
insertion_max_iter = NULL,
insertion_mode = NULL,
insertion_layout_k = NULL,
insertion_weighted_preset = NULL,
insertion_grip_args = NULL,
insertion_weighted_args = NULL,
insertion_fr_niter = NULL,
refinement_pair_mode = NULL,
refinement_full_limit = NULL,
refinement_local_nbrs = NULL,
refinement_landmark_count = NULL,
refinement_anchor_weight = NULL,
refinement_anchor_weight_end = NULL,
refinement_continuation = NULL,
refinement_max_iter = NULL,
final_pair_mode = NULL,
final_full_limit = NULL,
final_local_nbrs = NULL,
final_landmark_count = NULL,
final_max_iter = NULL,
stiffness = 1,
distance_floor = 1e-08,
edge_length_epsilon = 1e-08,
initial_step = 1,
step_shrink = 0.5,
armijo_factor = 1e-04,
grad_tol = 1e-08,
min_step = 1e-08,
recenter = TRUE,
return_trace = FALSE,
return_frames = FALSE,
seed = 6L
)A list with `coords`, `prepared`, the per-stage multiscale results, the stage trace, optional trace/frame details, timing, and the final MISF score summary.
Optional prepared object. This can be either a full geodesic-KK prepared object or a MISF-GKK prepared object.
Two-column integer matrix of edges (1-based vertex ids).
Number of vertices. If omitted with `adj_list`, defaults to `length(adj_list)`. If omitted with `edges`, defaults to `max(edges)`.
Adjacency list (1-based) for an undirected graph.
Optional parallel list of positive edge weights.
Optional positive edge-weight vector parallel to `edges`.
Shortest-path aggregation mode inherited from [prepare.geodesic.kk()].
Target top-level active-set size passed to `build.misf`.
Per-level local-neighborhood schedule metadata passed to `build.misf`.
Target embedding dimension (`2` or `3`) for the multiscale solve.
Optional override for the top-level pair policy.
Optional override for the top-level exact/sparse threshold.
Optional override for the sparse top-level local neighborhood size.
Optional override for the sparse top-level landmark count.
Number of top-level restarts used by the coarse MISF-GKK solve.
Top-level iteration budget.
Optional override for the top-level initializer.
Optional insertion anchor policy.
Optional insertion anchor count.
Optional insertion anchor weighting mode.
Optional per-vertex insertion iteration budget.
Optional insertion warm-start mode.
Optional active-level layout graph size used by layout-based insertion modes.
Optional weighted preset forwarded by future weighted insertion modes.
Optional named list of extra arguments for future combinatorial GRIP insertion modes.
Optional named list of extra arguments for future weighted GRIP insertion modes.
Optional FR iteration budget for future FR-based insertion modes.
Optional active-level pair policy.
Optional active-level exact/sparse threshold.
Optional active-level sparse local neighborhood size.
Optional active-level sparse landmark count.
Optional initial anchor weight used to pin inactive and coarser-level vertices during KK refinement.
Optional final anchor weight used at the end of the active-level continuation schedule.
Optional continuation schedule used for the active-level anchor penalty.
Optional active-level refinement iteration budget.
Optional final full-graph pair policy.
Optional final full-graph exact/sparse threshold.
Optional final full-graph sparse local neighborhood size.
Optional final full-graph sparse landmark count.
Optional final polish iteration budget.
Global stiffness constant \(K\).
Small positive floor used in
k_ij = K / max(g_ij, distance_floor)^2.
Small positive stabilizer added inside each embedded edge length.
Initial line-search step size.
Multiplicative shrink factor in `(0, 1)` for backtracking.
Non-negative Armijo decrease constant.
Non-negative stopping tolerance on the gradient norm.
Positive minimum accepted line-search step before giving up.
If `TRUE`, recenter accepted proposals to zero mean after each accepted step.
If `TRUE`, retain detailed stage traces.
If `TRUE`, retain intermediate coordinate frames.
Optional integer seed reused for MISF extraction.