Merge pull request #148 from SpatialPlanning/devel

Devel

Author: jaseeverett

.github/workflows/MacOS.yaml

@@ -46,6 +46,7 @@ jobs:
             any::rcmdcheck
             any::remotes
             any::lpsymphony
+            any::slam
           needs: check
 
       - uses: r-lib/actions/check-r-package@v2

.github/workflows/Ubuntu.yaml

@@ -53,6 +53,7 @@ jobs:
             any::rcmdcheck
             any::remotes
             any::lpsymphony
+            any::slam
           needs: check
 
       - uses: r-lib/actions/check-r-package@v2

.github/workflows/Windows.yaml

@@ -50,6 +50,7 @@ jobs:
             any::rcmdcheck
             any::remotes
             any::lpsymphony
+            any::slam
           needs: check
 
       - uses: r-lib/actions/check-r-package@v2

.github/workflows/test-coverage.yaml

@@ -42,6 +42,7 @@ jobs:
             any::rcmdcheck
             any::remotes
             any::lpsymphony
+            any::slam
           needs: coverage
 
       - name: Test coverage

NAMESPACE

@@ -68,19 +68,16 @@ importFrom(dplyr,summarise)
 importFrom(dplyr,summarize)
 importFrom(dplyr,tibble)
 importFrom(dplyr,ungroup)
-importFrom(forcats,fct_relevel)
 importFrom(ggnewscale,new_scale_colour)
 importFrom(ggnewscale,new_scale_fill)
 importFrom(ggplot2,aes)
-importFrom(ggplot2,after_stat)
 importFrom(ggplot2,annotate)
 importFrom(ggplot2,coord_polar)
 importFrom(ggplot2,coord_sf)
 importFrom(ggplot2,element_blank)
 importFrom(ggplot2,element_line)
 importFrom(ggplot2,element_rect)
 importFrom(ggplot2,element_text)
-importFrom(ggplot2,expansion)
 importFrom(ggplot2,geom_abline)
 importFrom(ggplot2,geom_bar)
 importFrom(ggplot2,geom_segment)

R/data.R

@@ -1,6 +1,6 @@
 #' Planning Units
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_PUs`
 #' A data frame with XXXX rows and XXX columns:
@@ -14,9 +14,9 @@
 
 # -------------------------------------------------------------------------
 
-#' Boundary of planning units
+#' Boundary of Planning Units
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_bndry`
 #' A data frame with XXXX rows and XXX columns:
@@ -32,7 +32,7 @@
 
 #' Regionalisation
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_region`
 #' A data frame with XXXX rows and XXX columns:
@@ -47,7 +47,7 @@
 
 #' Binary Species Data
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_species_bin`
 #' A data frame with XXXX rows and XXX columns:
@@ -63,7 +63,7 @@
 
 #' Binary Species Data 2
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_species_bin2`
 #' A data frame with XXXX rows and XXX columns:
@@ -79,7 +79,7 @@
 
 #' Probability Species Data
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_species_prob`
 #' A data frame with XXXX rows and XXX columns:
@@ -93,9 +93,9 @@
 
 # -------------------------------------------------------------------------
 
-#' MPA Data
+#' Marine Protected Areas (MPAs) Data
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_mpas`
 #' A data frame with XXXX rows and XXX columns:
@@ -117,7 +117,7 @@
 #' @format `dat_category`
 #' A data frame with XXXX rows and XXX columns:
 #' \describe{
-#'   \item{feature}{all features available for spatial prioritisation}
+#'   \item{feature}{all features available for spatial prioritization}
 #'   \item{category}{the categories of all features}
 #'   ...
 #' }
@@ -135,7 +135,7 @@
 #' @format `dat_category2`
 #' A data frame with XXXX rows and XXX columns:
 #' \describe{
-#'   \item{feature}{all features available for spatial prioritisation}
+#'   \item{feature}{all features available for spatial prioritization}
 #'   \item{category}{the categories of all features}
 #'   ...
 #' }
@@ -148,7 +148,7 @@
 
 #' Climate metric data
 #'
-#' An sf dataframe of planning units for spatial prioritisation
+#' An sf dataframe of Planning Units for spatial prioritization
 #'
 #' @format `dat_clim`
 #' A data frame with 780 rows and 3 columns:
@@ -179,14 +179,14 @@
 # -------------------------------------------------------------------------
 
 
-#' Current MPAs of the Coral Sea
+#' Current Marine Protected Areas (MPAs) of the Coral Sea
 #'
-#' sf file containing the current marine protected areas of the coral sea
+#' sf file containing the current Marine Protected Areas (MPAs) of the coral sea
 #'
 #' @format `MPAsCoralSea`
 #' A data frame with 397 rows and 17 columns:
 #' \describe{
-#'   \item{wdpa}{binary vector denoting presence or absence of a current marine protected area}
+#'   \item{wdpa}{binary vector denoting presence or absence of a current MPA}
 #'   ...
 #' }
 #' @source https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA

R/splnr_get_distCoast.R

@@ -2,7 +2,7 @@
 #'
 #' @description
 #' This function calculates the shortest distance from the centroid of each
-#' planning unit in an `sf` object to the nearest coastline. It can use either
+#' Planning Unit in an `sf` object to the nearest coastline. It can use either
 #' a default coastline from the `rnaturalearth` package or a custom-provided
 #' coastline `sf` object.
 #'
@@ -13,7 +13,7 @@
 #' a suitable projected CRS for accurate distance calculations.
 #'
 #' @param dat_sf `[sf]` \cr An `sf` object containing polygon or point features
-#'   representing the planning units. Must have a valid CRS.
+#'   representing the Planning Units. Must have a valid CRS.
 #' @param custom_coast `[sf]` \cr An optional `sf` object representing a
 #'   custom coastline. If `NULL` (the default), the coastline is downloaded
 #'   from `rnaturalearth`.
@@ -99,20 +99,20 @@ splnr_get_distCoast <- function(dat_sf, custom_coast = NULL, res = "medium") {
       sf::st_transform(crs = sf::st_crs(dat_sf))
   }
 
-  # Calculate centroids of the planning units
-  # Using centroids is a standard approach to represent the location of each planning unit
-  message("Calculating centroids for planning units.")
+  # Calculate centroids of the Planning Units
+  # Using centroids is a standard approach to represent the location of each Planning Unit
+  message("Calculating centroids for Planning Units.")
   grid_centroid <- sf::st_centroid(sf::st_geometry(dat_sf))
 
-  # Calculate the distance matrix between each planning unit centroid and the coastline
+  # Calculate the distance matrix between each Planning Unit centroid and the coastline
   message("Calculating distances to coastline.")
   dist_mat <- sf::st_distance(grid_centroid, coast) %>%
     # Explicitly set the distance units to kilometers
     units::set_units("km") %>%
     # Drop the units class to get a numeric matrix for easier computation
     units::drop_units()
 
-  # Find the minimum distance for each planning unit (each row in the matrix)
+  # Find the minimum distance for each Planning Unit (each row in the matrix)
   # This identifies the shortest distance from each centroid to any part of the coastline
   message("Finding minimum distances and adding to dataframe.")
   dat_sf$coastDistance_km <- do.call(pmin, as.data.frame(dist_mat))