finalizing cleanup

.gitignore

@@ -1,3 +1,4 @@
+inst/doc
 .Rproj.user
 .Rhistory
 .RData

DESCRIPTION

@@ -41,13 +41,14 @@ Roxygen: list(markdown = TRUE)
 RoxygenNote: 6.1.1
 Imports: 
     classInt,
-    gridExtra,
     dplyr,
     ggplot2,
-    purrr,
     raster,
     tibble,
     tidyr
 Suggests: 
     testthat,
-    covr
+    covr,
+    knitr,
+    rmarkdown
+VignetteBuilder: knitr

R/data.R

@@ -5,7 +5,7 @@
 #'
 #' @format A raster layer object.
 #' @source Simulated neutral landscape models with R. \url{https://github.com/ropensci/NLMR/}
-"fbmmap"
+"fractal_landscape"
 
 #' Example map (planar gradient).
 #'
@@ -14,7 +14,7 @@
 #'
 #' @format A raster layer object.
 #' @source Simulated neutral landscape models with R. \url{https://github.com/ropensci/NLMR/}
-"grdmap"
+"gradient_landscape"
 
 #' Example map (random).
 #'
@@ -23,4 +23,4 @@
 #'
 #' @format A raster layer object.
 #' @source Simulated neutral landscape models with R. \url{https://github.com/ropensci/NLMR/}
-"rndmap"
+"random_landscape"

R/show_landscape.R

@@ -16,18 +16,18 @@
 #'
 #' @examples
 #' \dontrun{
-#' x <- grdmap
+#' x <- gradient_landscape
 #'
 #' # classify
-#' y <- util_classify(grdmap,  n = 3, level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
+#' y <- util_classify(gradient_landscape,  n = 3, level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
 #'
 #' show_landscape(x)
 #' show_landscape(y, discrete = TRUE)
 #'
-#' show_landscape(list(grdmap, rndmap))
-#' show_landscape(raster::stack(grdmap, rndmap))
+#' show_landscape(list(gradient_landscape, random_landscape))
+#' show_landscape(raster::stack(gradient_landscape, random_landscape))
 #'
-#' show_landscape(list(grdmap, y), unique_scales = TRUE)
+#' show_landscape(list(gradient_landscape, y), unique_scales = TRUE)
 #'
 #' }
 #'
@@ -98,83 +98,42 @@ show_landscape.list <- function(x,
                                 n_row = NULL,
                                 ...) {
 
-  if (!unique_scales){
-    x_tibble <- tibble::enframe(x, "id", "maps")
-    x_tibble <- dplyr::mutate(x_tibble,
-                              maps = lapply(x_tibble$maps, util_raster2tibble))
-    x_tibble <- tidyr::unnest(x_tibble)
-
-    if(!discrete){
-      p <- ggplot2::ggplot(x_tibble, ggplot2::aes_string("x", "y")) +
-        ggplot2::coord_fixed() +
-        ggplot2::geom_raster(ggplot2::aes_string(fill = "z")) +
-        ggplot2::facet_wrap(~id, nrow = n_row, ncol = n_col) +
-        ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$x))) +
-        ggplot2::scale_y_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$y))) +
-        ggplot2::guides(fill = FALSE) +
-        ggplot2::labs(titel = NULL, x = NULL, y = NULL) +
-        theme_facetplot()
-    }
-
-    if(discrete){
-      p <- ggplot2::ggplot(x_tibble, ggplot2::aes_string("x", "y")) +
-        ggplot2::coord_fixed() +
-        ggplot2::geom_raster(ggplot2::aes(fill = factor(z))) +
-        ggplot2::facet_wrap(~id, nrow = n_row, ncol = n_col) +
-        ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$x))) +
-        ggplot2::scale_y_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$y))) +
-        ggplot2::guides(fill = FALSE) +
-        ggplot2::labs(titel = NULL, x = NULL, y = NULL) +
-        theme_facetplot_discrete()
-    }
-
+  x_tibble <- tibble::enframe(x, "id", "maps")
+  x_tibble <- dplyr::mutate(x_tibble,
+                            maps = lapply(x_tibble$maps, function(x){
+
+                              if(unique_scales) x <- util_rescale(x)
+                              util_raster2tibble(x)
+
+                            })
+                            )
+  x_tibble <- tidyr::unnest(x_tibble)
+
+  if (!discrete) {
+    p <- ggplot2::ggplot(x_tibble, ggplot2::aes_string("x", "y")) +
+      ggplot2::coord_fixed() +
+      ggplot2::geom_raster(ggplot2::aes_string(fill = "z")) +
+      ggplot2::facet_wrap( ~ id, nrow = n_row, ncol = n_col) +
+      ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0, max(x_tibble$x))) +
+      ggplot2::scale_y_continuous(expand = c(0, 0), limits = c(0, max(x_tibble$y))) +
+      ggplot2::guides(fill = FALSE) +
+      ggplot2::labs(titel = NULL, x = NULL, y = NULL) +
+      theme_facetplot()
   }
 
-  if (unique_scales){
-
-    landscape_plots <- lapply(seq_along(x), function(id){
-
-      x_tibble <- raster::as.data.frame(x[[id]], xy = TRUE)
-      names(x_tibble)[3] <- "z"
-      x_tibble$id <-  names(x[[id]])
-
-
-      p <- tryCatch({
-        p <- ggplot2::ggplot(x_tibble, ggplot2::aes_string("x", "y")) +
-          ggplot2::coord_fixed() +
-          ggplot2::geom_raster(ggplot2::aes_string(fill = "z")) +
-          ggplot2::facet_wrap(~id, nrow = 1, ncol = 1) +
-          ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$x))) +
-          ggplot2::scale_y_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$y))) +
-          ggplot2::guides(fill = FALSE) +
-          ggplot2::labs(titel = NULL, x = NULL, y = NULL) +
-          theme_facetplot() +
-          ggplot2::theme(plot.margin = ggplot2::unit(c(0, 0, 0, 0), "cm")) +
-          theme_facetplot()
-        print(p)
-      },
-      error = function(e) {
-        ggplot2::ggplot(x_tibble, ggplot2::aes_string("x", "y")) +
-          ggplot2::coord_fixed() +
-          ggplot2::geom_raster(ggplot2::aes_string(fill = "z")) +
-          ggplot2::facet_wrap(~id, nrow = 1, ncol = 1) +
-          ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$x))) +
-          ggplot2::scale_y_continuous(expand = c(0, 0), limits = c(0,max(x_tibble$y))) +
-          ggplot2::guides(fill = FALSE) +
-          ggplot2::labs(titel = NULL, x = NULL, y = NULL) +
-          theme_facetplot() +
-          ggplot2::theme(plot.margin = ggplot2::unit(c(0, 0, 0, 0), "cm")) +
-          theme_facetplot_discrete()
-      })
-
-      p
-
-    })
-
-    p <- gridExtra::grid.arrange(grobs = landscape_plots, nrow=n_row, ncol=n_col)
-
+  if (discrete) {
+    p <- ggplot2::ggplot(x_tibble, ggplot2::aes_string("x", "y")) +
+      ggplot2::coord_fixed() +
+      ggplot2::geom_raster(ggplot2::aes(fill = factor(z))) +
+      ggplot2::facet_wrap( ~ id, nrow = n_row, ncol = n_col) +
+      ggplot2::scale_x_continuous(expand = c(0, 0), limits = c(0, max(x_tibble$x))) +
+      ggplot2::scale_y_continuous(expand = c(0, 0), limits = c(0, max(x_tibble$y))) +
+      ggplot2::guides(fill = FALSE) +
+      ggplot2::labs(titel = NULL, x = NULL, y = NULL) +
+      theme_facetplot_discrete()
   }
 
+
   return(p)
 
 }

R/util_binarize.R

@@ -13,7 +13,7 @@
 #'
 #' @examples
 #' breaks <- c(0.3, 0.5)
-#' binary_maps <- util_binarize(grdmap, breaks)
+#' binary_maps <- util_binarize(gradient_landscape, breaks)
 #'
 #' @aliases util_binarize
 #' @rdname util_binarize

R/util_classify.R

@@ -19,7 +19,7 @@
 #'
 #' @param x raster
 #' @param n Number of classes
-#' @param style Style of breaks (see classInt::classInvervals() for more details)
+#' @param style chosen style: one of "fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust", "bclust", "fisher", or "jenks" (see classInt::classInvervals() for more details)
 #' @param weighting Vector of numeric values that are considered to be habitat percentages (see details)
 #' @param level_names Vector of names for the factor levels.
 #' @param real_land Raster with real landscape (see details)
@@ -29,33 +29,33 @@
 #'
 #' @examples
 #' # Mode 1
-#' util_classify(fbmmap,
+#' util_classify(fractal_landscape,
 #'               n = 3,
 #'               style = "fisher",
 #'               level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
 #'
 #' # Mode 2
-#' util_classify(fbmmap,
+#' util_classify(fractal_landscape,
 #'               weighting = c(0.5, 0.25, 0.25),
 #'               level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
 #'
 #' # Mode 3
-#' real_land <- util_classify(grdmap,
+#' real_land <- util_classify(gradient_landscape,
 #'               n = 3,
 #'               level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
 #'
-#' fbmmap_real <- util_classify(fbmmap, real_land = real_land)
-#' fbmmap_mask <- util_classify(fbmmap, real_land = real_land, mask_val = 1)
+#' fractal_landscape_real <- util_classify(fractal_landscape, real_land = real_land)
+#' fractal_landscape_mask <- util_classify(fractal_landscape, real_land = real_land, mask_val = 1)
 #'
 #' \dontrun{
 #' landscapes <- list(
-#' '1 nlm' = fbmmap,
+#' '1 nlm' = fractal_landscape,
 #' '2 real' = real_land,
-#' '3 result' = fbmmap_real,
-#' '4 result with mask' = fbmmap_mask
+#' '3 result' = fractal_landscape_real,
+#' '4 result with mask' = fractal_landscape_mask
 #' )
 #'
-#' util_facetplot(landscapes, div_scales = TRUE, nrow = 1)
+#' show_landscape(landscapes, unique_scales = TRUE, nrow = 1)
 #' }
 #'
 #' @aliases util_classify

R/util_merge.R

@@ -10,7 +10,7 @@
 #' @return Rectangular matrix with values ranging from 0-1
 #'
 #' @examples
-#' x <- util_merge(grdmap, rndmap)
+#' x <- util_merge(gradient_landscape, random_landscape)
 #' show_landscape(x)
 #'
 #' @aliases util_merge

R/util_raster2tibble.R

@@ -10,7 +10,7 @@
 #' @return a tibble
 #'
 #' @examples
-#' maptib <- util_raster2tibble(fbmmap)
+#' maptib <- util_raster2tibble(fractal_landscape)
 #' \dontrun{
 #' library(ggplot2)
 #' ggplot(maptib, aes(x,y)) +

R/util_rescale.R

@@ -9,8 +9,8 @@
 #' @details Rasters generated by \code{nlm_} functions are scaled between 0 and 1 as default, this option can be set to \code{FALSE} if needed.
 #'
 #' @examples
-#' unscmap <- util_merge(grdmap, rndmap, rescale = FALSE)
-#' util_rescale(unscmap)
+#' unscaled_landscape <- gradient_landscape + fractal_landscape
+#' util_rescale(unscaled_landscape)
 #'
 #' @aliases util_rescale
 #' @rdname util_rescale
@@ -28,3 +28,5 @@ util_rescale <- function(x) {
 
   return(rescaled_NLM)
 }
+
+

R/util_tibble2raster.R

@@ -15,9 +15,9 @@
 #' @return Raster* object
 #'
 #' @examples
-#' maptib <- util_raster2tibble(rndmap)
+#' maptib <- util_raster2tibble(random_landscape)
 #' mapras <- util_tibble2raster(maptib)
-#' all.equal(rndmap, mapras)
+#' all.equal(random_landscape, mapras)
 #'
 #' @aliases util_tibble2raster
 #' @rdname util_tibble2raster

R/util_writeESRI.R

@@ -21,7 +21,7 @@
 #'
 #' @examples
 #' \dontrun{
-#' util_writeESRI(grdmap, "grdmap.asc")
+#' util_writeESRI(gradient_landscape, "gradient_landscape.asc")
 #' }
 #'
 #' @aliases util_writeESRI

README.Rmd

@@ -30,21 +30,22 @@ Objects).
 
 #### Utilities:
 
-`util_binarize`: Binarize continuous raster values, if > 1 breaks are given, return a RasterBrick.<br/>
-`util_classify`: Classify a raster into proportions based upon a vector of class weightings.<br/>
-`util_merge`: Merge a primary raster with other rasters weighted by scaling factors.<br/>
-`util_raster2tibble`, `util_tibble2raster`: Coerce raster* objects to tibbles and vice versa.<br/>
-`util_rescale`: Linearly rescale element values in a raster to a range between 0 and 1.<br/>
+- `util_binarize`: Binarize continuous raster values, if > 1 breaks are given, return a RasterBrick.
+- `util_classify`: Classify a raster into proportions based upon a vector of class weightings.
+- `util_merge`: Merge a primary raster with other rasters weighted by scaling factors.
+- `util_raster2tibble`, `util_tibble2raster`: Coerce raster* objects to tibbles and vice versa.
+- `util_rescale`: Linearly rescale element values in a raster to a range between 0 and 1.
+- `util_writeESRI`: Export raster objects as ESRI asciis (with Windows linebreaks).
 
 #### Visualization
 
-`show_landscape`: Plot a Raster* object with the landscapetools default theme (as ggplot) or multiple raster (RasterStack, -brick or list of raster) side by side as facets.<br/>
+- `show_landscape`: Plot a Raster* object with the landscapetools default theme (as ggplot) or multiple raster (RasterStack, -brick or list of raster) side by side as facets.
 
 #### Themes:
 
-`theme_nlm`, `theme_nlm_grey`: Opinionated ggplot2 theme to visualize raster (continuous data).<br/>
-`theme_nlm_discrete`, `theme_nlm_grey_discrete`: Opinionated ggplot2 theme to visualize raster (discrete data).<br/>
-`theme_faceplot`: Opinionated ggplot2 theme to visualize raster in a facet wrap.<br/>
+- `theme_nlm`, `theme_nlm_grey`: Opinionated ggplot2 theme to visualize raster (continuous data).
+- `theme_nlm_discrete`, `theme_nlm_grey_discrete`: Opinionated ggplot2 theme to visualize raster (discrete data).
+- `theme_faceplot`: Opinionated ggplot2 theme to visualize raster in a facet wrap.
 
 ## Installation
 
@@ -71,15 +72,15 @@ show_landscape(nlm_raster)
 ### Binarize
 
 ```{r fig.retina=2}
-# Binarize the map into habitat and matrix
+# Binarize the landscape into habitat and matrix
 binarized_raster <- util_binarize(nlm_raster, breaks = 0.31415)
 show_landscape(binarized_raster)
 ```
 
 ### Classify
 
 ```{r fig.retina=2}
-# Classify the map into land uses
+# Classify the landscape into land uses
 classified_raster <- util_classify(nlm_raster,
                                    n = 3,
                                    level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
@@ -89,15 +90,15 @@ show_landscape(classified_raster, discrete = TRUE)
 ### Merge
 
 ```{r fig.retina=2}
-# Create a primary and two secondary maps
+# Create a primary and two secondary landscapes
 prim <- nlm_edgegradient(ncol = 100, nrow = 100)
 
 sec1 <- nlm_distancegradient(ncol = 100, nrow = 100,
                              origin = c(10, 10, 10, 10))
 
 sec2 <- nlm_random(ncol = 100, nrow = 100)
 
-# Merge all maps into one
+# Merge all landscapes into one
 merg <- util_merge(prim, c(sec1, sec2), scalingfactor = 1)
 
 # Plot an overview