Compute a layered layout for a bass-ackwards diagram

Returns tidy node coordinates and the edge table needed to render a bass-ackwards diagram. The layout is a layered (Sugiyama-style) barycenter algorithm in two stages:

Usage

ba_layout(x, min_sep = 1, order = NULL)

Arguments

x: An ackwards object.
min_sep: Minimum horizontal separation between adjacent nodes at the same level. Default 1.0. Increase for wider diagrams.
order: Optional manual left-to-right ordering of the deepest (k_max) level, overriding Stage 1. Supply either a character vector of the deepest level's factor IDs in the desired order, or a named list with an entry for the deepest level (keyed by the level number as a string, e.g. list("5" = c("m5f2", "m5f1", ...))). Fixing the leaf order propagates upward: every upper factor stays at the mean-x of its primary children, so any arrangement of the primary forest is reachable from the leaf order. Entries for non-deepest levels are ignored with a warning (an upper factor's position is derived, not free). The vector must be a permutation of the deepest level's IDs. NULL (default) uses the automatic ordering.

Value

A list with two data frames:

nodes: One row per factor: id, level, x, y, label. y = -level so level 1 is at the top.
edges: The tidy edge table from x$edges$tidy.

Details

Ordering – determines the left-to-right order of factors at each level. Two candidate orderings are scored and the crossing-minimising one kept: a single top-down |r|-weighted barycenter sweep (the historical order), and a primary-forest traversal – each factor has exactly one primary parent, so the primary edges form a forest, and a depth-first, subtree-contiguous leaf order lays every subtree out as an unbroken run. In deep hierarchies (k >= 10) the traversal drives primary-tree crossings to zero (the "bent levels" a single pass leaves behind); keep-best scoring (lexicographic: primary crossings, then all crossings) means shallow layouts are never made worse.
X-assignment – assigns actual x coordinates bottom-up. The deepest level is spread evenly; every upper-level factor is placed at the simple mean x of its primary children: a factor with one primary child lands directly above it; a factor with two primary children lands exactly halfway between them. Falls back to |r|-weighted mean of all children for factors with no primary children. Spreading resolves any remaining overlaps.

After both stages the layout is shifted so that the single level-1 node is always at x = 0. The result is fully deterministic.

Examples

x <- ackwards(sim16, k_max = 5)
lay <- ba_layout(x)
head(lay$nodes)
#>     id level      x  y label
#> 1 m1f1     1  0.000 -1  m1f1
#> 2 m2f1     2 -1.125 -2  m2f1
#> 3 m2f2     2  1.125 -2  m2f2
#> 4 m3f1     3  1.125 -3  m3f1
#> 5 m3f2     3 -0.625 -3  m3f2
#> 6 m3f3     3 -1.625 -3  m3f3