v1.1.0

DESCRIPTION

@@ -1,19 +1,16 @@
 Type: Package
 Package: GeoThinneR
 Title: Simple Spatial Thinning for Ecological and Spatial Analysis
-Version: 1.0.0
+Version: 1.1.0
 Authors@R: 
     person("Jorge", "Mestre-Tomás", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-8983-3417"))
 Description: Provides efficient geospatial thinning algorithms to reduce
     the density of coordinate data while maintaining spatial
-    relationships. Implements K-D Tree Approximate Nearest Neighbors
-    (ANN), R-Tree, and brute force thinning methods. It uses a modified version 
-    of the R-tree structure from the 'rtree' package 
-    <https://github.com/akoyabio/rtree>. The modified version can be downloaded 
-    from <https://github.com/jmestret/rtree>.
-    For more information on the methods, see 
-    Elseberg et al. (2012) <https://hdl.handle.net/10446/86202>.
+    relationships. Implements K-D Tree and brute-force distance-based
+    thinning, as well as grid-based and precision-based thinning methods.
+    For more information on the methods, see Elseberg et al. (2012)
+    <https://hdl.handle.net/10446/86202>.
 License: MIT + file LICENSE
 URL: https://github.com/jmestret/GeoThinneR,
     https://jmestret.github.io/GeoThinneR/
@@ -32,14 +29,11 @@ Suggests:
     ggplot2,
     knitr,
     rmarkdown,
-    rtree,
     sf,
     testthat (>= 3.0.0),
     tibble
 LinkingTo: 
     Rcpp
-Remotes:
-    jmestret/rtree
 VignetteBuilder: 
     knitr
 BuildVignettes: true

NEWS.md

@@ -1,5 +1,10 @@
 # GeoThinneR (development version)
 
+# GeoThinneR 1.1.0
+
+* Removed non-CRAN dependency (`rtree`) and associated functions related to R-Trees structure thinning method (`r_tree_thinning()`).
+* Minor improvements to documentation.
+
 # GeoThinneR 1.0.0 
 
 * Initial release!

R/thin_points.R

@@ -9,7 +9,7 @@
 #' @param long_col Name of the column with longitude coordinates (default: "decimalLongitude").
 #' @param lat_col Name of the column with latitude coordinates (default: "decimalLatitude").
 #' @param group_col Name of the column for grouping points (e.g., species name, year). If NULL, no grouping is applied.
-#' @param method Thinning method to use `c("brute_force", "kd_tree", "r_tree", "round_hash", "grid", "precision")`.
+#' @param method Thinning method to use `c("brute_force", "kd_tree", "round_hash", "grid", "precision")`.
 #' @param trials Number of thinning iterations to perform (default: 10).
 #' @param all_trials If TRUE, returns results of all attempts; if FALSE, returns the best attempt with the most points retained (default: FALSE).
 #' @param target_points Optional; a numeric value specifying the exact number of points to keep. If NULL (default), maximizes the number of kept points.
@@ -23,7 +23,6 @@
 #' The thinning methods available are:
 #' - `brute_force`: Uses a brute force approach to thin points.
 #' - `kd_tree`: Uses K-D trees for thinning.
-#' - `r_tree`: Uses R-trees for thinning.
 #' - `round_hash`: Uses rounding and hashing for efficient thinning.
 #' - `grid`: Applies a grid-based thinning method.
 #' - `precision`: Utilizes precision-based thinning.
@@ -32,7 +31,6 @@
 #' - `brute_force_thinning()`
 #' - `grid_thinning()`
 #' - `kd_tree_thinning()`
-#' - `r_tree_thinning()`
 #' - `rounding_hashing_thinning()`
 #' - `precision_thinning()`
 #'
@@ -63,7 +61,7 @@
 #'
 #' @export
 thin_points <- function(data, long_col = NULL, lat_col = NULL, group_col = NULL,
-                        method = c("brute_force", "kd_tree", "r_tree", "round_hash", "grid", "precision"),
+                        method = c("brute_force", "kd_tree", "round_hash", "grid", "precision"),
                         trials = 10, all_trials = FALSE,
                         target_points = NULL, seed = NULL, verbose = FALSE, ...) {
 
@@ -126,7 +124,6 @@ thin_points <- function(data, long_col = NULL, lat_col = NULL, group_col = NULL,
       method,
       "brute_force"    = brute_force_thinning(coordinates, trials = trials, all_trials = all_trials, ...),
       "kd_tree"        = kd_tree_thinning(coordinates, trials = trials, all_trials = all_trials, ...),
-      "r_tree"         = r_tree_thinning(coordinates, trials = trials, all_trials = all_trials, ...),
       "round_hash"     = rounding_hashing_thinning(coordinates,  trials = trials, all_trials = all_trials, seed = seed, ...),
       "grid"      = grid_thinning(coordinates, trials = trials, all_trials = all_trials, ...),
       "precision" = precision_thinning(coordinates, trials = trials, all_trials = all_trials, ...),

README.Rmd

@@ -40,12 +40,6 @@ To install the development version of GeoThinneR from GitHub, use:
 devtools::install_github("jmestret/GeoThinneR")
 ```
 
-Optionally, to use R-trees you need to install:
-
-```r
-devtools::install_github("jmestret/rtree")
-```
-
 ## How to Use GeoThinneR
 
 The documentation can be found at <https://jmestret.github.io/GeoThinneR/>. Below are some examples demonstrating how to use the package for different spatial thinning methods.
@@ -188,4 +182,4 @@ We welcome contributions! If you have suggestions for improvements or new featur
 
 The GeoThinneR paper is currently in progress. Meanwhile, you can reference the GitHub repository as follows:
 
-Mestre-Tomás, J. (2024). GeoThinneR: An R package for simple spatial thinning methods in ecological and spatial analysis. R package version 1.0.0, https://github.com/jmestret/GeoThinneR
+Mestre-Tomás, J. (2024). GeoThinneR: An R package for simple spatial thinning methods in ecological and spatial analysis. R package version 1.1.0, https://github.com/jmestret/GeoThinneR

README.md

@@ -40,12 +40,6 @@ To install the development version of GeoThinneR from GitHub, use:
 devtools::install_github("jmestret/GeoThinneR")
 ```
 
-Optionally, to use R-trees you need to install:
-
-``` r
-devtools::install_github("jmestret/rtree")
-```
-
 ## How to Use GeoThinneR
 
 The documentation can be found at
@@ -167,4 +161,4 @@ reference the GitHub repository as follows:
 
 Mestre-Tomás, J. (2024). GeoThinneR: An R package for simple spatial
 thinning methods in ecological and spatial analysis. R package version
-1.0.0, <https://github.com/jmestret/GeoThinneR>
+1.1.0, <https://github.com/jmestret/GeoThinneR>

_pkgdown.yml

@@ -22,7 +22,6 @@ reference:
   contents:
   - '`brute_force_thinning`'
   - '`kd_tree_thinning`'
-  - '`r_tree_thinning`'
   - '`rounding_hashing_thinning`'
   - '`grid_thinning`'
   - '`precision_thinning`'

cran-comments.md

@@ -2,13 +2,40 @@
 
 This is a resubmission to address the feedback from the previous CRAN submission.
 
-* Moved the Note to the Description field in the DESCRIPTION file as requested.
-* Shortened the package title to meet the 65-character limit.
-* Replaced `\dontrun{}` with `\donttest{}` for examples that can be executed.
-* Wrapped examples that require packages in `Suggests` using `if(requireNamespace("pkgname", quietly = TRUE)){}` to avoid errors if those packages are not installed.
+* The non-CRAN package `rtree` has been removed from `Suggests`.
+* Associated functionalities depending on `rtree` have been removed or adjusted accordingly.
+
+## Test environments
+
+The package was tested on the following environments:
+
+* Windows Server 2022 x64 (build 20348)
+* Debian GNU/Linux trixie/sid
 
 ## R CMD check results
 
-0 errors | 0 warnings | 1 note
+The package passed `R CMD check` on all tested platforms with the following results.
+There was one NOTE:
+
+```
+New submission
+
+Package was archived on CRAN
+
+Possibly misspelled words in DESCRIPTION:
+  Elseberg (12:46)
+  al (12:58)
+  et (12:55)
+  geospatial (8:33)
+```
+
+* This is a new submission after the package was archived.
+* The flagged words in the DESCRIPTION are proper nouns or standard terminology.
+
+```
+CRAN repository db overrides:
+  X-CRAN-Comment: Archived on 2024-09-18 as issues were not corrected
+    in time.
+```
 
-* This is a new release.
+* All previously noted issues have now been corrected, and the package is ready for resubmission.