Adding simulation tools to mobsim

.Rbuildignore

@@ -11,6 +11,7 @@ codemeta.json
 ^README_files$
 ^LICENSE\.md$
 ^examples$
+^\.claude$
 ^\.github$
 ^doc$
 ^Meta$

.gitignore

@@ -1,6 +1,9 @@
 Rproj.user
 .Rproj.user
 .Rhistory
+README.html
+.claude/settings.local.json
+
 
 # C++
 .o
@@ -21,4 +24,3 @@ revdep/
 
 # Mac
 .DS_Store
-README.html

DESCRIPTION

@@ -1,15 +1,15 @@
 Package: mobsim
 Type: Package
 Title: Spatial Simulation and Scale-Dependent Analysis of Biodiversity Changes
-Version: 0.3.2
+Version: 0.3.3
 Authors@R: c(
     person("Felix", "May", email = "felix.may@fu-berlin.de",
         role = c("aut", "cre","cph"),
         comment = c(ORCID = "0000-0002-1106-8188")),
     person("Alban", "Sagouis", email = "alban.sagouis@idiv.de",
         role = "aut",
         comment = c(ORCID = "0000-0002-3827-1063")),
-    person("German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig",
+    person("German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig",
         role = "fnd", comment = c(ROR = "01jty7g66")),
     person("Freie Universität Berlin",
         role = "fnd", comment = c(ROR = "046ak2485"))
@@ -24,7 +24,7 @@ Description: Simulation, analysis and sampling of spatial
     decay of similarity.
 License: GPL (>= 3)
 Depends:
-    R (>= 4.0.0)
+    R (>= 4.1.0)
 Imports:
     Rcpp,
     vegan,
@@ -33,20 +33,22 @@ Imports:
     utils,
     graphics,
     stats,
+    spatstat.geom,
+    spatstat.explore,
     methods
 Suggests:
     quarto,
-    spatstat.geom,
     spatstat.random,
     testthat (>= 3.0.0),
     mockery,
     vctrs
 LinkingTo: Rcpp
 Config/testthat/edition: 3
 Config/testthat/parallel: false
+Config/testthat/start-first: *utils*, *create_motherpoints*, *simulation*, *sampling*
 VignetteBuilder: quarto
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Language: en-GB
 Encoding: UTF-8
 URL: https://github.com/MoBiodiv/mobsim

NAMESPACE

@@ -3,20 +3,35 @@
 S3method(plot,community)
 S3method(plot,dist_decay)
 S3method(plot,divar)
+S3method(plot,mother_map)
 S3method(plot,sad)
 S3method(plot,spec_sample_curve)
 S3method(summary,community)
 S3method(summary,sad)
+S3method(torusify,community)
+S3method(torusify,data.frame)
+S3method(torusify,mother_map)
+S3method(torusify,numeric)
 export(abund_rect)
 export(community)
+export(community2ppp)
 export(community_to_sad)
+export(create_motherpoints)
+export(create_random_ID)
 export(dist_decay)
 export(dist_decay_quadrats)
 export(div_rand_rect)
 export(div_rect)
 export(divar)
+export(drift_x_motherpoints)
+export(drift_x_species)
+export(drift_y_motherpoints)
+export(drift_y_species)
+export(jitter_motherpoints)
+export(jitter_species)
 export(rThomas_rcpp)
 export(rare_curve)
+export(replace_individuals)
 export(sample_quadrats)
 export(sampling_grids)
 export(sampling_one_quadrat)
@@ -31,7 +46,11 @@ export(sim_thomas_community)
 export(sim_thomas_coords)
 export(spec_sample)
 export(spec_sample_curve)
+export(torusify)
 importFrom(Rcpp,sourceCpp)
 importFrom(methods,is)
 importFrom(sads,rsad)
+importFrom(spatstat.explore,marktable)
+importFrom(spatstat.geom,owin)
+importFrom(spatstat.geom,ppp)
 useDynLib(mobsim, .registration = TRUE)

R/Diversity_Area_Relationships.R

@@ -118,8 +118,8 @@ div_rand_rect <- function(
    n_rect = 100,
    exclude_zeros = FALSE
 ) {
-   dx_plot <- comm$x_min_max[2] - comm$x_min_max[1]
-   dy_plot <- comm$y_min_max[2] - comm$y_min_max[1]
+   dx_plot <- comm$x_min_max[[2]] - comm$x_min_max[[1]]
+   dy_plot <- comm$y_min_max[[2]] - comm$y_min_max[[1]]
 
    area <- dx_plot * dy_plot * prop_area
    square_size <- sqrt(area)
@@ -139,13 +139,13 @@ div_rand_rect <- function(
 
    xpos <- stats::runif(
       n_rect,
-      min = comm$x_min_max[1],
-      max = comm$x_min_max[2] - dx_rect
+      min = comm$x_min_max[[1]],
+      max = comm$x_min_max[[2]] - dx_rect
    )
    ypos <- stats::runif(
       n_rect,
-      min = comm$y_min_max[1],
-      max = comm$y_min_max[2] - dy_rect
+      min = comm$y_min_max[[1]],
+      max = comm$y_min_max[[2]] - dy_rect
    )
 
    div_plots <- mapply(
@@ -154,7 +154,7 @@ div_rand_rect <- function(
       ypos,
       MoreArgs = list(xsize = dx_rect, ysize = dy_rect, comm = comm)
    )
-   if (exclude_zeros == TRUE)
+   if (isTRUE(exclude_zeros))
       div_plots <- div_plots[, div_plots["n_species", ] > 0]
 
    return(c(
@@ -220,8 +220,8 @@ divar <- function(
       stop("DiVAR requires a community object as input. See ?community.")
 
    n_scales <- length(prop_area)
-   dx_plot <- comm$x_min_max[2] - comm$x_min_max[1]
-   dy_plot <- comm$y_min_max[2] - comm$y_min_max[1]
+   dx_plot <- comm$x_min_max[[2]] - comm$x_min_max[[1]]
+   dy_plot <- comm$y_min_max[[2]] - comm$y_min_max[[1]]
 
    div_area <- sapply(
       prop_area,
@@ -314,11 +314,11 @@ abund_rect <- function(x0, y0, xsize, ysize, comm) {
    x <- comm$census$x
    y <- comm$census$y
 
-  # logical vector which trees are in the sampling rectangle
-  in_rect <- (x >= x0 & x < (x0 + xsize) & y >= y0 & y < (y0 + ysize))
+   # logical vector which trees are in the sampling rectangle
+   in_rect <- (x >= x0 & x < (x0 + xsize) & y >= y0 & y < (y0 + ysize))
 
-  abund <- table(comm$census$species[in_rect])
-  return(abund)
+   abund <- table(comm$census$species[in_rect])
+   return(abund)
 }
 
 #' Distance decay of similarity
@@ -345,6 +345,7 @@ abund_rect <- function(x0, y0, xsize, ysize, comm) {
 #'@export
 #'
 dist_decay <- function(
+   comm,
    prop_area = 0.005,
    n_samples = 20,
    method = "bray",
@@ -354,12 +355,12 @@ dist_decay <- function(
 
    if (length(prop_area) != 1L) stop("prop_area has to be of length 1")
 
-  if (!is(comm, "community"))
-    stop("dist_decay requires a community object as input. See ?community.")
+   if (!is(comm, "community"))
+      stop("dist_decay requires a community object as input. See ?community.")
 
-  dx_plot <- comm$x_min_max[2] - comm$x_min_max[1]
-  dy_plot <- comm$y_min_max[2] - comm$y_min_max[1]
-  area <- dx_plot * dy_plot * prop_area
+   dx_plot <- comm$x_min_max[[2]] - comm$x_min_max[[1]]
+   dy_plot <- comm$y_min_max[[2]] - comm$y_min_max[[1]]
+   area <- dx_plot * dy_plot * prop_area
 
    samples1 <- sample_quadrats(
       comm,
@@ -379,12 +380,12 @@ dist_decay <- function(
       similarity = as.numeric(similarity)
    )
 
-  # order by increasing distance
-  dat_out <- dat_out[order(dat_out$distance), ]
+   # order by increasing distance
+   dat_out <- dat_out[order(dat_out$distance), ]
 
-  class(dat_out) <- c("dist_decay", "data.frame")
+   class(dat_out) <- c("dist_decay", "data.frame")
 
-  return(dat_out)
+   return(dat_out)
 }
 
 #' Distance decay of similarity with user-defined quadrats
@@ -424,12 +425,12 @@ dist_decay_quadrats <- function(samples, method = "bray", binary = FALSE) {
       similarity = as.numeric(similarity)
    )
 
-  # order by increasing distance
-  dat_out <- dat_out[order(dat_out$distance), ]
+   # order by increasing distance
+   dat_out <- dat_out[order(dat_out$distance), ]
 
-  class(dat_out) <- c("dist_decay", "data.frame")
+   class(dat_out) <- c("dist_decay", "data.frame")
 
-  return(dat_out)
+   return(dat_out)
 }
 
 
@@ -503,4 +504,3 @@ plot.dist_decay <- function(x, ...) {
 #
 #    return(abund.plots[,1])
 # }
-#

R/Sample_quadrats.R

@@ -57,18 +57,18 @@ sample_quadrats <- function(
 
   quadrat_size <- sqrt(quadrat_area)
 
-  community_size <- (comm$x_min_max[2] - comm$x_min_max[1]) *
-    (comm$y_min_max[2] - comm$y_min_max[1])
+  community_size <- (comm$x_min_max[[2]] - comm$x_min_max[[1]]) *
+    (comm$y_min_max[[2]] - comm$y_min_max[[1]])
 
   if (quadrat_size < community_size) {
     # This works as long as we use square quadrats
 
     if (n_quadrats == 1L) {
       xy_dat <- sampling_one_quadrat(
-        xmin = comm$x_min_max[1],
-        xmax = comm$x_min_max[2] - quadrat_size,
-        ymin = comm$y_min_max[1],
-        ymax = comm$y_min_max[2] - quadrat_size,
+        xmin = comm$x_min_max[[1]],
+        xmax = comm$x_min_max[[2]] - quadrat_size,
+        ymin = comm$y_min_max[[1]],
+        ymax = comm$y_min_max[[2]] - quadrat_size,
         seed = seed
       )
     } else {
@@ -80,20 +80,20 @@ sample_quadrats <- function(
             xy_dat <- sampling_random_spatstat(
               n_quadrats = n_quadrats,
               min_dist = min_dist,
-              xmin = comm$x_min_max[1],
-              xmax = comm$x_min_max[2] - quadrat_size,
-              ymin = comm$y_min_max[1],
-              ymax = comm$y_min_max[2] - quadrat_size,
+              xmin = comm$x_min_max[[1]],
+              xmax = comm$x_min_max[[2]] - quadrat_size,
+              ymin = comm$y_min_max[[1]],
+              ymax = comm$y_min_max[[2]] - quadrat_size,
               seed = seed
             )
           } else {
             xy_dat <- sampling_random_bruteforce(
               n_quadrats = n_quadrats,
               min_dist = min_dist,
-              xmin = comm$x_min_max[1],
-              xmax = comm$x_min_max[2] - quadrat_size,
-              ymin = comm$y_min_max[1],
-              ymax = comm$y_min_max[2] - quadrat_size,
+              xmin = comm$x_min_max[[1]],
+              xmax = comm$x_min_max[[2]] - quadrat_size,
+              ymin = comm$y_min_max[[1]],
+              ymax = comm$y_min_max[[2]] - quadrat_size,
               seed = seed
             )
           } # end of no spatstat
@@ -102,10 +102,10 @@ sample_quadrats <- function(
           xy_dat <- sampling_random_overlap(
             n_quadrats = n_quadrats,
             min_dist = min_dist,
-            xmin = comm$x_min_max[1],
-            xmax = comm$x_min_max[2] - quadrat_size,
-            ymin = comm$y_min_max[1],
-            ymax = comm$y_min_max[2] - quadrat_size,
+            xmin = comm$x_min_max[[1]],
+            xmax = comm$x_min_max[[2]] - quadrat_size,
+            ymin = comm$y_min_max[[1]],
+            ymax = comm$y_min_max[[2]] - quadrat_size,
             seed = seed
           )
         }
@@ -114,10 +114,10 @@ sample_quadrats <- function(
       if (method == "transect") {
         xy_dat <- sampling_transects(
           n_quadrats = n_quadrats,
-          xmin = comm$x_min_max[1],
-          xmax = comm$x_min_max[2],
-          ymin = comm$y_min_max[1],
-          ymax = comm$y_min_max[2],
+          xmin = comm$x_min_max[[1]],
+          xmax = comm$x_min_max[[2]],
+          ymin = comm$y_min_max[[1]],
+          ymax = comm$y_min_max[[2]],
           x0 = x0,
           y0 = y0,
           delta_x = delta_x,
@@ -129,10 +129,10 @@ sample_quadrats <- function(
       if (method == "grid") {
         xy_dat <- sampling_grids(
           n_quadrats = n_quadrats,
-          xmin = comm$x_min_max[1],
-          xmax = comm$x_min_max[2],
-          ymin = comm$y_min_max[1],
-          ymax = comm$y_min_max[2],
+          xmin = comm$x_min_max[[1]],
+          xmax = comm$x_min_max[[2]],
+          ymin = comm$y_min_max[[1]],
+          ymax = comm$y_min_max[[2]],
           x0 = x0,
           y0 = y0,
           delta_x = delta_x,
@@ -156,8 +156,8 @@ sample_quadrats <- function(
     comm_tab <- table(comm$census$species)
 
     xy_dat <- data.frame(
-      x = comm$x_min_max[1],
-      y = comm$y_min_max[1]
+      x = comm$x_min_max[[1]],
+      y = comm$y_min_max[[1]]
     )
 
     rownames(xy_dat) <- "site1"
@@ -171,13 +171,13 @@ sample_quadrats <- function(
   }
 
   # plot sampling design
-  if (plot == TRUE) {
+  if (isTRUE(plot)) {
     plot(comm)
     graphics::rect(
-      xy_dat$x,
-      xy_dat$y,
-      xy_dat$x + quadrat_size,
-      xy_dat$y + quadrat_size,
+      xleft = xy_dat$x,
+      ybottom = xy_dat$y,
+      xright = xy_dat$x + quadrat_size,
+      ytop = xy_dat$y + quadrat_size,
       lwd = 2,
       col = grDevices::adjustcolor("white", alpha.f = 0.6)
     )
@@ -243,7 +243,7 @@ sampling_random_spatstat <- function(
 #' Creates coordinates (lower left corner of a quadrat) randomly distributed but without overlapping each
 #' other
 #'
-#' This function works without having the \code{spatstat.random} package install.
+#' This function works without having the \code{spatstat.random} package installed.
 #'
 #' @inheritParams sampling_random_spatstat
 #'