Produces an HTML file with interactive charts (loading Chart.js from its
public CDN). For fits created with the default gnn = FALSE, the
report describes baseline-only imputation. For fits created with
gnn = TRUE, it also compares the GNN against the phylogenetic
baseline and includes training history. Per-trait metrics, gate values,
and held-out diagnostic conformal coverage are included when available.
Usage
pigauto_report(
fit,
data = NULL,
splits = NULL,
output_path = "pigauto_report.html",
title = "pigauto Imputation Report",
open = TRUE
)Arguments
- fit
A
pigauto_fitobject (or apigauto_resultfromimpute).- data
Optional
pigauto_dataobject. Extracted automatically whenfitis apigauto_result. When supplied it must match the fit (species and traits).- splits
Optional splits object from
make_missing_splits. Extracted automatically whenfitis apigauto_result. When supplied it must match the fit.- output_path
Character of length 1. File path for the HTML report (default
"pigauto_report.html"in the working directory).- title
Character of length 1. Report title (HTML-escaped on write).
- open
Logical of length 1. Open the report in a browser when done (default
TRUE).
Examples
# \donttest{
data(avonet300, tree300)
tree <- ape::keep.tip(tree300, tree300$tip.label[seq_len(30L)])
traits <- avonet300[match(tree$tip.label, avonet300$Species_Key),
c("Mass", "Wing.Length"), drop = FALSE]
rownames(traits) <- tree$tip.label
traits$Mass[seq_len(3L)] <- NA_real_
result <- impute(traits, tree, epochs = 5L, verbose = FALSE)
#> Warning: Small validation set for 2 trait(s): Mass (n=4), Wing.Length (n=3). Calibrated gate and conformal scores will be noisy for these trait(s). 95% split-conformal coverage is NOT achievable for 2 trait(s) with fewer than 19 validation cells (Mass (n=4), Wing.Length (n=3)): the achievable ceiling is n_val / (n_val + 1), which only reaches 0.95 at n_val >= 19. See `?fit_pigauto` under 'Calibration at small n' for smoothing options.
pigauto_report(result, output_path = tempfile(fileext = ".html"),
open = FALSE)
# }
