Builds a compact one-row diagnostic table for a fitted local polynomial smoother. The table records the requested backend, the backend actually used, the requested chart-dimension rule, the resolved chart dimension, selected tuning parameters, and whether the fit follows the current deployable local-PCA auto-dimension contract.
Value
A one-row data.frame with backend, chart-dimension, selection,
candidate-count, and policy fields.
Details
The current backend policy is conservative: backend = "auto" uses the
C++ backend for ambient-coordinate LPS, but uses the R reference backend for
coordinate.method = "local.pca". The native local-PCA backend
"cpp.local.pca" remains an explicit opt-in backend. This helper
makes that policy visible in reports and downstream experiment manifests
without changing the default.
For real-data local-PCA runs, the deployable chart-dimension contract is
the ordinary local.chart.method = "pca" path with
chart.dim = "auto" or "local.auto" and observed-covariate
auto-dimension diagnostics.
In P7-style experiments this is paired with
auto.chart.support.metric = "both" and
auto.chart.selection.metric = "operator". The experimental
"second.order.svd" chart path is reported explicitly but is not
certified by this deployable local-PCA contract. For LPS itself, which uses
coordinate supports, the operator-support diagnostic is currently equivalent
to the coordinate-support diagnostic; the fields are still recorded so the
same manifest schema can be shared with LPL-TF and S-LPL-TF experiments.
Examples
X <- matrix(seq(0, 1, length.out = 16), ncol = 1)
fit <- fit.lps(X, X[, 1]^2, support.grid = 6L, degree.grid = 1L,
kernel.grid = "gaussian", cv.folds = 2L, backend = "R")
lps.backend.diagnostics(fit)
#> method.id outcome.family coordinate.method local.chart.method
#> 1 lps gaussian coordinates pca
#> local.chart.method.effective backend.requested backend.used
#> 1 none R R
#> backend.auto.policy requested.chart.dim resolved.chart.dim chart.dim.auto
#> 1 explicit_R NULL 1 FALSE
#> chart.dim.local.auto chart.dim.mode chart.dim.by.anchor.n
#> 1 FALSE ambient 16
#> chart.dim.by.anchor.min chart.dim.by.anchor.max auto.chart.support.metric
#> 1 1 1 coordinates
#> auto.chart.selection.metric auto.chart.support.metric.selected
#> 1 coordinates <NA>
#> auto.chart.fallback.used auto.chart.n.anchors auto.chart.median.local.dim
#> 1 NA NA NA
#> selected.support.size selected.degree selected.kernel
#> 1 6 1 gaussian
#> selected.bandwidth.multiplier selected.cv.rmse.observed
#> 1 1 0.07000098
#> selected.cv.brier.observed selected.cv.logloss.observed
#> 1 NA NA
#> design.basis design.drop.tol ridge.multiplier.grid
#> 1 orthogonal.polynomial.drop 1e-08 0;1e-10;1e-08
#> ridge.condition.max bandwidth.multiplier.grid unstable.action candidate.count
#> 1 1e+12 1 na 1
#> local.pca.real.data.contract
#> 1 FALSE