Version 1.2.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: rflsgen
 Type: Package
 Title: Neutral Landscape Generator with Targets on Landscape Indices
-Version: 1.0.0
+Version: 1.2.0
 Author: Dimitri Justeau-Allaire, Grégoire Blanchard, Thomas Ibanez, Xavier Lorca, Ghislain Vieilledent, Philippe Birnbaum
 Maintainer: Dimitri Justeau-Allaire <[email protected]>
 Description: Interface to the 'flsgen' neutral landscape generator <https://github.com/dimitri-justeau/flsgen>. It allows to
@@ -13,9 +13,9 @@ Encoding: UTF-8
 LazyData: true
 Depends: 
   rJava,
-  raster,
-  terra (>= 1.5-12)
-Imports: rgdal, checkmate, utils, jsonlite
+  terra (>= 1.5-12),
+  jsonlite
+Imports: rgdal, checkmate, utils
 SystemRequirements: Java (>= 8)
 RoxygenNote: 7.2.0
 Suggests: testthat (>= 3.0.0), knitr, rmarkdown, landscapemetrics

NAMESPACE

@@ -9,5 +9,6 @@ export(flsgen_extract_structure_from_raster)
 export(flsgen_generate)
 export(flsgen_structure)
 export(flsgen_terrain)
+import(jsonlite)
 import(rJava)
-import(raster)
+import(terra)

NEWS.md

@@ -1,3 +1,16 @@
+# rflsgen 1.2.0
+
+* Rely on flsgen-1.2.0, which is now divided into modules. The R package only relies on the flsgen-core-1.2.0, which 
+allowed to remove dependencies to Geotools, resulting in a much lighter JAR that can now be directly package
+into rflsgen (no need to download anymore). This also reduces the time that was need for read and write operation
+for exchanging rasters between R and Java, now only data is exchanged.
+
+* Add IS_SQUARE target, which allows to produce only square patches.
+
+* Add ALL_DIFFERENT target, which allows to produce patches having all different areas.
+
+* Remove dependency to the raster package, and now switch to terra.
+
 # rflsgen 1.0.0
 
 * Rely on flsgen-1.1.0, which fixes several bug, improve performances, provide two new indices (AREA_MN, mean patch area and NON_FOCAL_PLAND, which is PLAND applied to the non-focal class), implement variable neighborhood for more flexible distance between patches in landscape generation, masking, landscape extraction from existing rasters, and more fine tuning.

R/flsgen_available_targets.R

@@ -38,5 +38,5 @@ CLASS_LEVEL_TARGETS <- c(
   "COHE",     # Degree of coherence
   "DIVI",     # Degree of division
   "IS_SQUARE", # If TRUE, all patches are square
-  "patchesAllDifferent" # If TRUE, all patches must have different size
+  "ALL_DIFFERENT" # If TRUE, all patches must have different size
 )

R/flsgen_create_class_targets.R

@@ -45,6 +45,7 @@
 #' @param COHE degree of coherence target (must be a vector of length 2)
 #' @param DIVI degree of landscape division target (must be a vector of length 2)
 #' @param IS_SQUARE if TRUE, the class is required to only produce square patches
+#' @param ALL_DIFFERENT if TRUE, the class is required to have differently sized patches
 #'
 #' @return A class targets object which can be converted to JSON for flsgen
 #'
@@ -58,14 +59,14 @@ flsgen_create_class_targets <- function(class_name, NP=NULL, AREA=NULL, AREA_MN=
                                         CA=NULL, PLAND=NULL, PD=NULL, SPI=NULL,
                                         LPI=NULL, MESH=NULL, SPLI=NULL, NPRO=NULL,
                                         SDEN=NULL, COHE=NULL, DIVI=NULL, IS_SQUARE=FALSE,
-                                        patchesAllDifferent=FALSE) {
+                                        ALL_DIFFERENT=FALSE) {
   checkmate::assert_string(class_name)
   class_targets <- list(
     name=class_name
   )
   for (i in CLASS_LEVEL_TARGETS) {
     if (!is.null(get(i))) {
-      if (i %in% c("IS_SQUARE", "patchesAllDifferent")) {
+      if (i %in% c("IS_SQUARE", "ALL_DIFFERENT")) {
         checkmate::assert_flag(get(i))
       } else {
         checkmate::assert_vector(get(i), len = 2)

R/flsgen_create_landscape_structure.R

@@ -29,7 +29,9 @@
 #' @param nb_rows Number of rows
 #' @param nb_cols Number of columns
 #' @param classes list of class structures
-#' @param mask_raster mask raster (path or raster object)
+#' @param mask_raster mask raster (path or terra::rast object)
+#'
+#' @import terra
 #'
 #' @details Either nb_rows and nb_cols, or mask_raster must be specified. The dimensions
 #' of the landscape are deduced from the mask raster if it is used.
@@ -62,16 +64,14 @@ flsgen_create_landscape_structure <- function(nb_rows, nb_cols, classes, mask_ra
     lstruct$nbRows <- nb_rows
     lstruct$nbCols <- nb_cols
   } else {
-    if (inherits(mask_raster, "Raster")) {
-      if (nchar(filename(mask_raster)) > 0) {
-        mask_raster <- filename(mask_raster)
-      } else {
-        file_name <- tempfile(fileext = ".tif")
-        writeRaster(mask_raster, file_name)
-        mask_raster <- file_name
+    if (inherits(mask_raster, "SpatRaster")) {
+      s <- terra::sources(mask_raster)[[1]]
+      on_disk <- all(nchar(s > 0) && all(file.exists(s)))
+      if (on_disk) {
+        lstruct$maskRasterPath <- s
       }
+      lstruct$maskRaster <- mask_raster
     }
-    lstruct$maskRasterPath <- mask_raster
   }
   return(structure(lstruct, class="FlsgenLandscapeStructure"))
 }

R/flsgen_create_landscape_targets.R

@@ -28,9 +28,11 @@
 #' @param nb_rows Number of rows
 #' @param nb_cols Number of columns
 #' @param classes list of class targets
-#' @param mask_raster mask raster (path or raster object)
+#' @param mask_raster mask raster (path or terra::rast object)
 #' @param NON_FOCAL_PLAND PLAND (proportion of landscape) target on the non-focal land-use class
 #'
+#' @import terra
+#'
 #' @details Either nb_rows and nb_cols, or mask_raster must be specified. The dimensions
 #' of the landscape are deduced from the mask raster if it is used.
 #'
@@ -61,16 +63,14 @@ flsgen_create_landscape_targets <- function(nb_rows, nb_cols, classes, mask_rast
     base_targets$nbRows <- nb_rows
     base_targets$nbCols <- nb_cols
   } else {
-    if (inherits(mask_raster, "Raster")) {
-      if (nchar(filename(mask_raster)) > 0) {
-        mask_raster <- filename(mask_raster)
-      } else {
-        file_name <- tempfile(fileext = ".tif")
-        writeRaster(mask_raster, file_name)
-        mask_raster <- file_name
+    if (inherits(mask_raster, "SpatRaster")) {
+      s <- terra::sources(mask_raster)[[1]]
+      on_disk <- all(nchar(s > 0) && all(file.exists(s)))
+      if (on_disk) {
+        base_targets$maskRasterPath <- s
       }
+      base_targets$maskRaster <- mask_raster
     }
-    base_targets$maskRasterPath <- mask_raster
   }
   if (!is.null(NON_FOCAL_PLAND)) {
     base_targets$NON_FOCAL_PLAND <- NON_FOCAL_PLAND

R/flsgen_extract_structure_from_raster.R

@@ -22,13 +22,13 @@
 #'
 #' @description Extracts a landscape structure from an existing raster
 #'
-#' @param raster_file raster object or path of the raster
+#' @param raster_file terra::rast object or path of the raster
 #' @param focal_classes vector of integers representing the raster values of
 #' the focal classes to extract the structure from
 #' @param connectivity Connectivity definition in the regular square grid (4 or 8)."
 #'
 #' @import rJava
-#' @import raster
+#' @import terra
 #'
 #' @return A JSON landscape structure that can be used with flsgen generate
 #'
@@ -41,29 +41,29 @@
 flsgen_extract_structure_from_raster <- function(raster_file, focal_classes, connectivity=4) {
   checkmate::assert_vector(focal_classes, min.len = 1)
   checkmate::assert_choice(connectivity, c(4, 8))
-  if (inherits(raster_file, "Raster")) {
-    if (nchar(filename(raster_file)) > 0) {
-      raster_file <- filename(raster_file)
-    } else {
-      file_name <- tempfile(fileext = ".tif")
-      writeRaster(raster_file, file_name)
-      raster_file <- file_name
-    }
-  } else {
-    checkmate::assert_string(raster_file)
-    checkmate::assert(file.exists(raster_file))
+  if (!inherits(raster_file, "SpatRaster")) {
+    raster_file <- terra::rast(raster_file)
   }
+  nb_rows <- nrow(raster_file)
+  nb_cols <- ncol(raster_file)
+  no_data_cells <- which(is.na(raster_file[,])) - 1
+  no_data_value <-terra::NAflag(raster_file)
+  s <- terra::sources(raster_file)[[1]]
   if (connectivity == 4) {
     neigh <- J("org.flsgen.grid.neighborhood.Neighborhoods")$FOUR_CONNECTED
   } else {
     if (connectivity == 8) {
       neigh <- J("org.flsgen.grid.neighborhood.Neighborhoods")$HEIGHT_CONNECTED
     }
   }
-  struct <- J("org.flsgen.solver.LandscapeStructure")$fromRaster(
-    raster_file,
+  struct <- J("org.flsgen.solver.LandscapeStructure")$fromRasterData(
+    .jarray(as.integer(values(raster_file))),
+    as.integer(nb_rows),
+    as.integer(nb_cols),
+    as.integer(no_data_value),
     .jarray(as.integer(focal_classes)),
-    neigh
+    neigh,
+    s
   )
   .jgc()
   return(struct$toJSON())

R/flsgen_generate.R

@@ -23,6 +23,8 @@
 #' @description Generate landscape raster from landscape structure
 #'
 #' @import rJava
+#' @import terra
+#' @import jsonlite
 #'
 #' @details The input landscape structure must be either specified as a JSON-formatted string
 #'  (structure_str parameter) or as a JSON file (structure_file parameter)
@@ -87,6 +89,7 @@ flsgen_generate <- function(structure_str, structure_file, terrain_file=NULL,
                             min_max_distance=NULL, connectivity=4, x=0, y=0,
                             resolution_x=0.0001, resolution_y=NULL, epsg="EPSG:4326",
                             max_try=2, max_try_patch=10, verbose=TRUE) {
+  mask_raster <- NULL
   # Check arguments
   if (missing(structure_str)) {
     if (missing(structure_file)) {
@@ -98,6 +101,10 @@ flsgen_generate <- function(structure_str, structure_file, terrain_file=NULL,
       stop("Either structure_str or structure_file must be used in generate_landscape_raster function to specify user targets, not both")
     }
     if (inherits(structure_str, "FlsgenLandscapeStructure")) {
+      if (!is.null(structure_str$maskRaster)) {
+        mask_raster <- structure_str$maskRaster
+        structure_str$maskRaster <- NULL
+      }
       for (i in 1:length(structure_str$classes)) {
         structure_str$classes[[i]] <- unclass(structure_str$classes[[i]])
       }
@@ -126,11 +133,27 @@ flsgen_generate <- function(structure_str, structure_file, terrain_file=NULL,
   struct_json <- jsonlite::fromJSON(structure_str)
   nb_rows <- struct_json$nbRows
   nb_cols <- struct_json$nbCols
+  no_data_cells <- c()
+  no_data_value <- -3000
+  if (!is.null(mask_raster)) {
+    nb_rows <- nrow(mask_raster)
+    nb_cols <- ncol(mask_raster)
+    no_data_cells <- which(is.na(mask_raster[,])) - 1
+    no_data_value <-terra::NAflag(mask_raster)
+  } else {
+    if (!is.null(struct_json$maskRasterPath)) {
+      mask_raster <- terra::rast(struct_json$maskRasterPath)
+      nb_rows <- nrow(mask_raster)
+      nb_cols <- ncol(mask_raster)
+      no_data_cells <- which(is.na(mask_raster[,])) - 1
+      no_data_value <-terra::NAflag(mask_raster)
+    }
+  }
 
   # Generate landscape raster using flsgen jar
-  reader <- .jnew("java.io.StringReader", structure_str)
-  struct <- J("org.flsgen.solver.LandscapeStructure")$fromJSON(reader)
-  reader$close()
+  struct <- J("org.flsgen.solver.LandscapeStructure")$fromJSON(
+    structure_str, as.integer(nb_rows), as.integer(nb_cols), .jarray(as.integer(no_data_cells))
+  )
   grid <- .jnew("org.flsgen.grid.regular.square.RegularSquareGrid", struct$getNbRows(), struct$getNbCols())
   terrain <- .jnew("org.flsgen.solver.Terrain", grid)
   if (is.null(terrain_file)) {
@@ -149,7 +172,7 @@ flsgen_generate <- function(structure_str, structure_file, terrain_file=NULL,
     generator <- .jnew("org.flsgen.solver.LandscapeGenerator", struct, as.integer(connectivity), as.integer(min_distance), as.integer(min_max_distance), terrain)
   }
   if (.jcall(generator, "Z", "generate", terrain_dependency, as.integer(max_try), as.integer(max_try_patch), verbose)) {
-    landscape_data <- .jcall(generator, "[I", "getRasterData", -2L)
+    landscape_data <- .jcall(generator, "[I", "getRasterData", as.integer(no_data_value))
     landscape_raster <- terra::rast(xmin = x, xmax = x + (nb_cols * resolution_x),
                                     ymax = y, ymin = y - (nb_rows * resolution_y),
                                     crs = epsg, nrows = nb_rows, ncols = nb_cols,

R/flsgen_structure.R

@@ -23,6 +23,8 @@
 #' @description Find landscape structures satisfying user targets
 #'
 #' @import rJava
+#' @import terra
+#' @import jsonlite
 #'
 #' @details The input user targets must be either specified as a JSON-formatted
 #'  string (targets_str parameter) or as a JSON file (target_file parameter).
@@ -67,6 +69,7 @@
 #' @export
 #'
 flsgen_structure <- function(targets_str, targets_file, nb_solutions=1, time_limit = 60, search_strategy="DEFAULT") {
+  mask_raster <- NULL
   # Check arguments
   if (missing(targets_str)) {
     if (missing(targets_file)) {
@@ -78,6 +81,10 @@ flsgen_structure <- function(targets_str, targets_file, nb_solutions=1, time_lim
       stop("Either targets_str or targets_file must be used in generate_landscape_structure function to specify user targets, not both")
     }
     if (inherits(targets_str, "FlsgenLandscapeTargets")) {
+      if (!is.null(targets_str$maskRaster)) {
+        mask_raster <- targets_str$maskRaster
+        targets_str$maskRaster <- NULL
+      }
       for (i in 1:length(targets_str$classes)) {
         targets_str$classes[[i]] <- unclass(targets_str$classes[[i]])
       }
@@ -88,9 +95,29 @@ flsgen_structure <- function(targets_str, targets_file, nb_solutions=1, time_lim
   checkmate::assert_int(time_limit, lower=0)
   checkmate::assert_choice(search_strategy, c("DEFAULT", "RANDOM", "DOM_OVER_W_DEG", "DOM_OVER_W_DEG_REF", "ACTIVITY_BASED", "CONFLICT_HISTORY", "MIN_DOM_LB", "MIN_DOM_UB"))
 
+  json_targets <- jsonlite::fromJSON(targets_str)
+
+  nb_rows <- 0
+  nb_cols <- 0
+  no_data_cells <- c()
+
+  if (!is.null(mask_raster)) {
+    nb_rows <- nrow(mask_raster)
+    nb_cols <- ncol(mask_raster)
+    no_data_cells <- which(is.na(mask_raster[,])) - 1
+  } else {
+    if (!is.null(json_targets$maskRasterPath)) {
+      mask_raster <- terra::rast(json_targets$maskRasterPath)
+      nb_rows <- nrow(mask_raster)
+      nb_cols <- ncol(mask_raster)
+      no_data_cells <- which(is.na(mask_raster[,])) - 1
+    }
+  }
+
   # Generate landscape structure using flsgen jar
-  reader <- .jnew("java.io.StringReader", targets_str)
-  solver <- J("org.flsgen.solver.LandscapeStructureSolver")$readFromJSON(reader)
+  solver <- J("org.flsgen.solver.LandscapeStructureSolver")$readFromJSON(
+    unclass(targets_str), as.integer(nb_rows), as.integer(nb_cols), .jarray(as.integer(no_data_cells))
+  )
   .jcall(solver, "V", "build")
   structs_json <- c()
   switch(search_strategy,

R/flsgen_terrain.R

@@ -23,6 +23,7 @@
 #' @description Fractal terrain generation with the diamond-square algorithm
 #'
 #' @import rJava
+#' @import terra
 #'
 #' @param width Width (in pixels) of output raster
 #' @param height Height (in pixels) of output raster
@@ -60,7 +61,6 @@ flsgen_terrain <- function(width, height, roughness=0.5, x=0, y=0, resolution=0.
                                 crs = epsg, nrows = height, ncols = width,
                                 nlyrs = 1)
   values(terrain_raster) <- raster_data
-  #.jcall(terrain, "V", "exportRaster", x, y, resolution, epsg, output)
   .jgc()
   return(terrain_raster)
 }

R/zzz.R

@@ -11,11 +11,11 @@
     if(jvn < 1.8) stop("Java >= 8 is needed for this package but not available")
   }
   # Download flsgen jar if not already downloaded
-  jar_path <- file.path(libname, pkgname, "java", "flsgen-1.2.0.jar")
+  jar_path <- file.path(libname, pkgname, "java", "flsgen-core-1.2.0.jar")
   if (!file.exists(jar_path)) {
     old_options <- options(timeout = max(1000, getOption("timeout")))
     on.exit(options(old_options))
-    utils::download.file("https://github.com/dimitri-justeau/flsgen/releases/download/v1.2.0/flsgen-1.2.0.jar", destfile = jar_path)
+    utils::download.file("https://github.com/dimitri-justeau/flsgen/releases/download/v1.2.0/flsgen-core-1.2.0.jar", destfile = jar_path)
   }
   .jpackage(pkgname, lib.loc = libname)
   J("java.lang.System")$setProperty("EPSG-HSQL.directory", tempdir())

cran-comments.md

@@ -1,3 +1,11 @@
+## rflsgen 1.2.0
+
+CRAN team complained about the size of the tarball, exceeding 5MB. To fix this:
+
+* We reduced the spatial resolution of example data to fix this issue;
+
+* We used pdf instead of html for documentation.
+
 ## rflsgen 0.1.2
 
 Configure Geotools to store its temporary EPSG database in R session's temporary directory.