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Extract layout data for plotting a CTA tree

cta_plot_data.Rd

Returns a pure-data list describing tree topology and layout coordinates. No graphics are produced. Use this as input to plot.cta_tree or to custom rendering code.

Layout algorithm: leaves receive sequential integer x-positions in depth-first (left-to-right) order; internal nodes are centred over their children. y = -depth so the root sits at the top.

Target-class enrichment: when target_class is supplied, each terminal leaf is joined to cta_staging_table and annotated with target-class counts, proportions, and a continuous display color derived from the endpoint's rank among all endpoints by ascending target-class proportion. Colors encode relative position within this tree's endpoint distribution and do not imply clinical thresholds or categories.

Usage

cta_plot_data(tree, target_class = NULL, class_labels = NULL,
              digits = 1, endpoint_palette = NULL)

Arguments

tree

A cta_tree from oda_cta_fit.

target_class

Integer (or NULL); the class label treated as the target when enriching endpoint annotations. NULL (default) returns the structural layout only - no endpoint enrichment columns are added.

class_labels

Optional character vector of display names for class labels. Supply as a named vector, e.g. c("0" = "Alive", "1" = "Deceased"), or as a positional vector (index \(k+1\) maps to class \(k\)). NULL (default) uses "class=C" formatting.

digits

Integer number of decimal places for percentage formatting in endpoint_label. Default 1.

endpoint_palette

Palette for endpoint fill colors, used only when target_class is supplied. Accepts NULL (default gradient: warm pink to pale yellow to soft green), a palette function(n) returning n color strings, or a character vector of colors interpolated via colorRampPalette.

Value

When target_class = NULL: a list with elements nodes, edges, no_tree, has_weights.

When target_class is supplied: the same list plus endpoints (a staging data.frame with layout coordinates) and target_class_used (the integer target class used).

nodes

A data.frame with one row per node. Always-present columns: node_id (integer), parent_id (integer), depth (integer), x (numeric), y (numeric), leaf (logical), attribute (character; NA for leaves), n_obs (integer), majority_class (integer), ess (numeric; NA for leaves), label (character multi-line display text).

Additional columns present when target_class is supplied (values are NA on split nodes): endpoint_id (integer), stage (integer), target_class (integer), target_n (numeric), denominator (numeric), target_proportion (numeric; raw continuous proportion, not binned), target_rank (integer; ascending rank of proportion, ties broken by ties.method = "first"), endpoint_fill_color (character hex color assigned by rank within this tree - does not imply clinical thresholds or categories), predicted_label (character), target_label (character), endpoint_label (character multi-line display text).

edges

A data.frame with one row per parent-to-child edge and columns from_node_id (integer), to_node_id (integer), x0, y0, x1, y1 (numeric centre-to-centre coordinates), label (character branch condition, e.g. "V14<=0.5").

endpoints

(target_class only) A data.frame with one row per endpoint, ordered by ascending stage. Columns include all staging fields from cta_staging_table plus layout coordinates x, y, display columns predicted_label, target_label, endpoint_fill_color, and integer target_rank.

target_class_used

(target_class only) The integer target_class argument used for enrichment.

no_tree

Logical; TRUE for leaf-only fits.

has_weights

Logical; TRUE when case weights are active.

See also

plot.cta_tree, cta_staging_table, oda_cta_fit

Examples

data(mtcars)
X    <- mtcars[, c("cyl", "disp", "hp", "wt")]
y    <- as.integer(mtcars$am)
tree <- suppressMessages(
  oda_cta_fit(X, y, mindenom = 5L, mc_iter = 500L, mc_seed = 42L,
              loo = "off")
)

# Structural layout only
pd <- cta_plot_data(tree)
head(pd$nodes)
#>   node_id parent_id depth   x  y  leaf attribute n_obs majority_class      ess
#> 1       1         0     1 1.5 -1 FALSE        wt    32              0 81.78138
#> 2       2         1     2 1.0 -2  TRUE      <NA>    14              1       NA
#> 3       3         1     2 2.0 -2  TRUE      <NA>    18              0       NA
#>   p_mc loo_p loo_status               label
#> 1    0    NA        OFF wt\nESS=81.8%\nn=32
#> 2   NA    NA       <NA>       class=1\nn=14
#> 3   NA    NA       <NA>       class=0\nn=18
pd$edges
#>   from_node_id to_node_id  x0 y0 x1 y1    label
#> 1            1          2 1.5 -1  1 -2  wt>3.18
#> 2            1          3 1.5 -1  2 -2 wt<=3.18

# Target-class enrichment
pd2 <- cta_plot_data(tree, target_class = 1L,
                     class_labels = c("0" = "Manual", "1" = "Auto"))
pd2$endpoints[, c("stage", "target_proportion", "endpoint_fill_color")]
#>   stage target_proportion endpoint_fill_color
#> 1     1        0.05555556             #FFEBEE
#> 2     2        0.85714286             #E8F5E9