Correctly sample points in nndm

Fixes #160

NEWS.md

@@ -1,5 +1,8 @@
 # spatialsample (development version)
 
+* Fixed bug where passing a polygon to `spatial_nndm_cv()` forced leave-one-out
+  CV, rather than the intended sampling of prediction points from the polygon.
+
 # spatialsample 0.5.1
 
 * `spatial_block_cv()` now adds an `expand_bbox` attribute to the resulting rset

R/spatial_nndm_cv.R

@@ -126,15 +126,15 @@ spatial_nndm_cv <- function(data, prediction_sites, ...,
   )
 
   if (use_provided_points) {
-    sample_points <- prediction_sites
+    prediction_sites <- prediction_sites
   } else if (sample_provided_poly) {
-    sample_points <- sf::st_sample(
+    prediction_sites <- sf::st_sample(
       x = sf::st_geometry(prediction_sites),
       size = prediction_sample_size,
       ...
     )
   } else {
-    sample_points <- sf::st_sample(
+    prediction_sites <- sf::st_sample(
       x = sf::st_as_sfc(sf::st_bbox(prediction_sites)),
       size = prediction_sample_size,
       ...
@@ -145,9 +145,9 @@ spatial_nndm_cv <- function(data, prediction_sites, ...,
   # and will _sometimes_ warn instead (systematic sampling)
   # but will _often_ strip CRS from the returned data;
   # enforce here that our output prediction sites share a CRS with input data
-  if (is.na(sf::st_crs(sample_points))) {
+  if (is.na(sf::st_crs(prediction_sites))) {
     prediction_sites <- sf::st_set_crs(
-      sample_points,
+      prediction_sites,
       sf::st_crs(prediction_sites)
     )
   }

tests/testthat/test-spatial_nndm_cv.R

@@ -115,3 +115,24 @@ test_that("rsplit labels", {
   original_id <- rs[, grepl("^id", names(rs))]
   expect_equal(all_labs, original_id)
 })
+
+test_that("passing a polygon works correctly", {
+  ames_sf <- sf::st_as_sf(
+    modeldata::ames,
+    coords = c("Longitude", "Latitude"), 
+    crs = 4326
+  )
+  ch <- st_concave_hull(st_union(ames_sf), ratio = 0.4, allow_holes = TRUE)
+
+  withr::with_seed(
+    123,
+    pts <- sf::st_sample(ch, 1000)
+  )
+  nndm_1 <- spatial_nndm_cv(ames_sf[1:100, ], pts)
+  attr(nndm_1, "prediction_sites") <- ch
+  withr::with_seed(
+    123,
+    nndm_2 <- spatial_nndm_cv(ames_sf[1:100, ], ch)
+  )
+  expect_identical(nndm_1, nndm_2)
+})