Map a cross-validation fold scheme

Shows which fold each observation belongs to. This is the fastest way to see whether spatial blocks are actually separating the data, or whether the blocks are smaller than the autocorrelation range and therefore leaking. For "block_kfold" folds the block outlines are drawn too, from folds$params$blocks, so a fold can be seen to be one region or several and an empty block can be seen to be empty. The subtitle states the parameter that decides whether the scheme leaks, read from folds$params: the block size (and the estimated range when auto_range found one), the buffer, the number of location groups, or the median NNDM exclusion.

Usage

plot_folds(folds, points_sf, boundary = NULL, blocks = TRUE)

Arguments

folds

A list returned by make_folds().

points_sf

The sf layer the folds were built from.

boundary

Optional polygonal sf/sfc to draw underneath.

blocks

Logical; draw the block polygons when folds carries them. Default TRUE.

Value

A ggplot object.

See also

Other plotting: plot.aoa(), plot.block_size_sweep(), plot.feature_selection(), plot.gwr_model_selection(), plot.resolution_profile(), plot.sac_range(), plot.spatial_fit(), plot_calibration(), plot_cv_metrics()

Examples

if (requireNamespace("ggplot2", quietly = TRUE)) {
  library(sf)
  set.seed(1)
  n <- 80
  pts <- st_as_sf(
    data.frame(x = 5e5 + runif(n, 0, 1000), y = 5e6 + runif(n, 0, 1000)),
    coords = c("x", "y"), crs = 32632
  )
  f <- make_folds(pts, k = 5, method = "block_kfold", block_size = 300)
  plot_folds(f, pts)
}