Fix for no_suggest

NEWS.md

@@ -6,6 +6,7 @@ If you are viewing this file on CRAN, please check [the latest news on GitHub](h
 - Enhance: `decimate_points()` with `random()` now preserves the point ordering.
 - Fix: #757
 - Fix: algorithm `random_per_voxel` that was not working
+- Fix: `readLAScatalog` if `sp` is missing
 
 ## lidR v4.1.1 (Release date: 2024-02-03)
 

R/Class-LAScatalog.R

@@ -180,8 +180,9 @@ setMethod("initialize", "LAScatalog", function(.Object)
 {
   Raster = NULL
   stars = NULL
+  spatial = NULL
 
-  if (system.file(package='raster') != "")
+  if (system.file(package='raster') != "" && system.file(package='sp') != "")
   {
     Raster = list(
       write = raster::writeRaster,
@@ -201,9 +202,20 @@ setMethod("initialize", "LAScatalog", function(.Object)
       param = list(NA_value = -999999))
   }
 
+  if (system.file(package='sp') != "")
+  {
+    spatial = list(
+      write = writeSpatial,
+      extension = ".shp",
+      object = "x",
+      path = "filename",
+      param = list(overwrite = FALSE))
+  }
+
   drivers = list(
     Raster = Raster,
     stars = stars,
+    Spatial = spatial,
     SpatRaster = list(
       write = terra::writeRaster,
       extension = ".tif",
@@ -226,13 +238,6 @@ setMethod("initialize", "LAScatalog", function(.Object)
       path = "file",
       param = list()
     ),
-    Spatial = list(
-      write = writeSpatial,
-      extension = ".shp",
-      object = "x",
-      path = "filename",
-      param = list(overwrite = FALSE)
-    ),
     sf = list(
       write = sf::st_write,
       extension = ".shp",

R/algorithm-gnd.R

@@ -46,11 +46,14 @@
 #' @family ground segmentation algorithms
 #'
 #' @examples
+#' if (require(RMCC, quietly = TRUE))
+#' {
 #' LASfile <- system.file("extdata", "Topography.laz", package="lidR")
 #' las <- readLAS(LASfile, select = "xyzrn", filter = "-inside 273450 5274350 273550 5274450")
 #'
 #' las <- classify_ground(las, mcc(1.5,0.3))
 #' #plot(las, color = "Classification")
+#' }
 #' @export
 #' @name gnd_mcc
 mcc <- function(s = 1.5, t = 0.3)
@@ -180,12 +183,15 @@ pmf = function(ws, th)
 #' @family ground segmentation algorithms
 #'
 #' @examples
+#' if (require(RCSF, quietly = TRUE))
+#' {
 #' LASfile <- system.file("extdata", "Topography.laz", package="lidR")
 #' las <- readLAS(LASfile, select = "xyzrn")
 #'
 #' mycsf <- csf(TRUE, 1, 1, time_step = 1)
 #' las <- classify_ground(las, mycsf)
 #' #plot(las, color = "Classification")
+#' }
 #' @name gnd_csf
 csf = function(sloop_smooth = FALSE, class_threshold = 0.5, cloth_resolution = 0.5, rigidness = 1L, iterations = 500L, time_step = 0.65)
 {

R/catalog_apply.R

@@ -44,7 +44,7 @@
 #'
 #' - It represents a chunk of the file collection
 #' - The function \link{readLAS} can be used with a `LAScluster`
-#' - The function \link[raster:extent]{extent} or \link[sp:bbox]{bbox} or \link[sf:st_bbox]{st_bbox}
+#' - The function \link[raster:extent]{extent} or \link[sf:st_bbox]{st_bbox}
 #' can be used with a `LAScluster` and they return the bounding box of the chunk without the buffer.
 #' It must be used to clip the output and remove the buffered region (see examples).
 #'
@@ -210,7 +210,9 @@
 #' # 4. Apply a user-defined function to take advantage of the internal engine
 #' opt    <- list(need_buffer = TRUE)   # catalog_apply will throw an error if buffer = 0
 #' output <- catalog_map(ctg, my_tree_detection_method, ws = 5, .options = opt)
+#' }
 #'
+#' \dontrun{
 #' ## ===================================================
 #' ## Example 2: compute a rumple index on surface points
 #' ## ===================================================

R/classify.R

@@ -43,13 +43,16 @@
 #' # Classify ground
 #' # ===============
 #'
+#' if (require(RCSF, quietly = TRUE))
+#' {
 #' LASfile <- system.file("extdata", "Topography.laz", package="lidR")
 #' las <- readLAS(LASfile, select = "xyzrn", filter = "-inside 273450 5274350 273550 5274450")
 #'
 #' # (Parameters chosen mainly for speed)
 #' mycsf <- csf(TRUE, 1, 1, time_step = 1)
 #' las <- classify_ground(las, mycsf)
 #' #plot(las, color = "Classification")
+#' }
 #'
 #' # ===============
 #' # Classify noise

R/metrics_stdmetrics.R

@@ -441,6 +441,8 @@ NULL
 #' x <- runif(20, 0, 100)
 #' y <- runif(20, 0, 100)
 #'
+#' if (require(geometry, quietly = TRUE))
+#' {
 #' # Perfectly flat surface, rumple_index = 1
 #' z <- rep(10, 20)
 #' rumple_index(x, y, z)
@@ -456,6 +458,7 @@ NULL
 #' # Measure of roughness is scale-dependent
 #' rumple_index(x, y, z)
 #' rumple_index(x/10, y/10, z)
+#' }
 #' @md
 #' @references
 #' Jenness, J. S. (2004). Calculating landscape surface area from digital elevation

R/plot.R

@@ -199,6 +199,7 @@ plot.LAScatalog = function(x, y, mapview = FALSE, chunk_pattern = FALSE, overlap
     if (is.null(param$ylab)) param$ylab <- ""
     if (is.null(param$asp))  param$asp  <- 1
     if (!is.null(param$col)) col <- param$col
+    param$map.types = NULL
 
     param$col <- "white"
     param$x   <- xcenter
@@ -215,7 +216,7 @@ plot.LAScatalog = function(x, y, mapview = FALSE, chunk_pattern = FALSE, overlap
     }
     else
     {
-      plot(as.spatial(x), col = col)
+      plot(sf::st_geometry(sf::st_as_sf(x)), axes = TRUE)
       graphics::par(op)
     }
 

tests/testthat/test-classify_ground.R

@@ -41,6 +41,9 @@ test_that("classify_ground pmf works with LAScatalog", {
 })
 
 test_that("classify_ground csf works with LAS", {
+
+  skip_if_not_installed("RCSF")
+
   las <- classify_ground(las, mycsf)
 
   n = names(las)
@@ -51,6 +54,8 @@ test_that("classify_ground csf works with LAS", {
 })
 
 test_that("classify_ground csf works with LAScatalog", {
+
+  skip_if_not_installed("RCSF")
   skip_on_cran()
 
   opt_output_files(ctg) <- paste0(tempdir(), "/file_{XLEFT}_{YBOTTOM}_ground")
@@ -63,6 +68,9 @@ test_that("classify_ground csf works with LAScatalog", {
 })
 
 test_that("classify_ground csf works with last_returns = FALSE", {
+
+  skip_if_not_installed("RCSF")
+
   las <- lidR:::generate_las(500)
   las <- classify_ground(las, csf(), last_returns = FALSE)
 
@@ -74,6 +82,9 @@ test_that("classify_ground csf works with last_returns = FALSE", {
 })
 
 test_that("classify_ground works with last_returns = TRUE but attribute not properly populated", {
+
+  skip_if_not_installed("RCSF")
+
   las <- lidR:::generate_las(500)
   las@data$ReturnNumber <- 0
   las@data$Classification <- NULL