implemented get_nearestneighbour

Related to Issue #19:
#19

R/get_nearestneighbour.R

@@ -0,0 +1,79 @@
+#' get_nearestneighbour
+#'
+#' @description Calculates the minimal euclidian distance between classes for a raster/matrix.
+#'
+#' @param landscape RasterLayer or matrix (with x,y,id columns)
+#'
+#' @details
+#' Fast and memory safe Rcpp implementation for calcuting minimal euclidian distances between
+#' classes in a raster or matrix.
+#'
+#' @examples
+#' # get patches for class 1 from testdata as raster
+#' class_1 <- get_patches(landscape,1)[[1]]
+#'
+#' # calculate the distance between patches
+#' get_nearestneighbour(class_1)
+#'
+#' # do the same with a 3 column matrix (x,y,id)
+#' class_1_matrix <- raster::rasterToPoints(class_1)
+#' get_nearestneighbour(class_1_matrix)
+#'
+#' @aliases get_nearestneighbour
+#' @rdname get_nearestneighbour
+#'
+#' @export
+get_nearestneighbour <- function(landscape) UseMethod("get_nearestneighbour")
+
+#' @name get_nearestneighbour
+#' @export
+get_nearestneighbour.RasterLayer <- function(landscape) {
+    points_mat <- raster::rasterToPoints(landscape)
+
+    ord <- order(as.matrix(points_mat)[, 1])
+    num <- seq_along(ord)
+    rank <- match(num, ord)
+
+    res <-
+        rcpp_get_nearest_neighbor(raster::as.matrix(points_mat)[ord, ])
+
+    min_dist <-
+        unname(cbind(num, res[rank], as.matrix(points_mat)[, 3]))
+
+    tbl <- tibble::tibble(cell = min_dist[, 1],
+                          dist = min_dist[, 2],
+                          id = min_dist[, 3])
+
+    dplyr::group_by(tbl, by = id) %>%
+        dplyr::summarise(value = min(dist)) %>%
+        purrr::set_names("id", "distance")
+}
+
+
+#' @name get_nearestneighbour
+#' @export
+get_nearestneighbour.matrix <- function(landscape) {
+
+    if ( ncol(landscape) != 3){
+        stop("Coordinate matrix must have 3 (x,y,id) columns.", call. = TRUE)
+    }
+
+    ord <- order(as.matrix(landscape)[, 1])
+    num <- seq_along(ord)
+    rank <- match(num, ord)
+
+    res <-
+        rcpp_get_nearest_neighbor(raster::as.matrix(landscape)[ord, ])
+
+    min_dist <-
+        unname(cbind(num, res[rank], as.matrix(landscape)[, 3]))
+
+    tbl <- tibble::tibble(cell = min_dist[, 1],
+                          dist = min_dist[, 2],
+                          id = min_dist[, 3])
+
+    dplyr::group_by(tbl, by = id) %>%
+        dplyr::summarise(value = min(dist)) %>%
+        purrr::set_names("id", "distance")
+
+}

src/rcpp_get_nearest_neighbor.cpp

@@ -112,7 +112,7 @@ dplyr::arrange(id,-y)
         num <- seq_along(ord)
         rank <- match(num, ord)
 
-        res <- rcpp_get_nearest_neighbor2(X[ord,])
+        res <- rcpp_get_nearest_neighbor(X[ord,])
 
         unname(cbind(num, res[rank], X[, 3]))
     }

tests/testthat/test-get-nearestneighbour.R

@@ -0,0 +1,18 @@
+context("get_nearestneighbour")
+
+
+# get patches for class 1 from testdata as raster
+class_1 <- get_patches(landscape,1)[[1]]
+# calculate the distance between patches
+nn_rast <- get_nearestneighbour(class_1)
+# do the same with a 3 column matrix (x,y,id)
+class_1_matrix <- raster::rasterToPoints(class_1)
+nn_mat<- get_nearestneighbour(class_1_matrix)
+
+test_that("get_adjacencies runs and returns a matrix", {
+    expect_is(nn_rast, "tbl_df")
+    expect_is(nn_mat, "tbl_df")
+
+    expect_true(nn_rast[1,2] == 7)
+    expect_true(nn_mat[1,2] == 7)
+})