Merge pull request #19 from stscl/dev

update `hclustgeo_disc()`

NEWS.md

@@ -1,5 +1,8 @@
 # sdsfun 0.6.0
 
+* The aggregation method for hierarchical clustering in `hclustgeo_disc()` is set 
+to `ward.D2` by default (#18).
+
 # sdsfun 0.5.0
 
 * Add `hclustgeo_disc` for hierarchical clustering with spatial soft constraints (#13).

R/stratification.R

@@ -55,6 +55,8 @@ discretize_vector = \(x, n, method = 'natural',
 #' @param D1 (optional) A `matrix` with other dissimilarities between the same observations data. if `data`
 #' is an `sf` object and alpha is not `0`, the `D1` will be generated by `sdsfun::sf_distance_matrix()`,
 #' others will use a `matrix` with all elements equal to `0`.
+#' @param hclustm (optional) The agglomeration method to be used, default is `ward.D2`. For more details,
+#' please see `stats::hclust()`.
 #' @param scale (optional) Whether to scaled the dissimilarities matrix, default is `TRUE`.
 #' @param wt (optional) Vector with the weights of the observations. By default, `wt` is `NULL`.
 #' @param ... (optional) Other arguments passed to `stats::dist()`.
@@ -69,7 +71,8 @@ discretize_vector = \(x, n, method = 'natural',
 #' plot(gzma["group"])
 #'
 hclustgeo_disc = \(data, n, alpha = 0.5, D1 = NULL,
-                   scale = TRUE, wt = NULL, ...){
+                   hclustm = "ward.D2", scale = TRUE,
+                   wt = NULL, ...){
   if (inherits(data,"sf")) {
     if (alpha != 0 & is.null(D1)) {
       D1 = sdsfun::sf_distance_matrix(data)
@@ -82,6 +85,6 @@ hclustgeo_disc = \(data, n, alpha = 0.5, D1 = NULL,
   }
   D0 = as.matrix(stats::dist(data,...))
   deltadist = stats::as.dist(RcppHClustGeoMat(D0,D1,alpha,scale,wt))
-  resh = stats::hclust(deltadist,method="ward.D",members=wt)
+  resh = stats::hclust(deltadist,method=hclustm,members=wt)
   return(stats::cutree(resh,k = n))
 }