Move fields, sp, spdep to suggests

10 files changed, 55 insertions, 34 deletions

diff --git a/DESCRIPTION b/DESCRIPTION
index 02a58d4..8e54eeb 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -4,8 +4,8 @@ Title: Functions and Data for the Book 'Applied Hierarchical Modeling in Ecology
 Version: 0.2.11
 Date: 2024-01-14
 Depends: R (>= 2.10)
-Imports: grDevices, graphics, methods, stats, utils, sp, fields, coda, unmarked (>= 0.12.2), mvtnorm, spdep
-Suggests: raster
+Imports: grDevices, graphics, methods, stats, utils, coda, unmarked (>= 0.12.2), mvtnorm
+Suggests: fields, raster, sp, spdep
 Authors@R: c(
   person("Marc", "Kéry", role="aut"),
   person("Andy", "Royle", role="aut"),
diff --git a/NAMESPACE b/NAMESPACE
index 5330d0e..2c5d72d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -18,8 +18,8 @@ importFrom("unmarked", "unmarkedFrameOccu", "unmarkedFramePCount", "unmarkedFram
           "occuRN", "bup", "ranef", "coef", "fitted", "residuals", "vcov", "confint")
 # importFrom("plotrix", "draw.circle") # Now in file draw_circle.R
 # importFrom("RandomFields", "RFoptions", "RFsimulate", "RMexp")
-importFrom("fields",  "circulantEmbeddingSetup", "circulantEmbedding")
-importFrom("sp", "bubble", "coordinates<-")
+#importFrom("fields",  "circulantEmbeddingSetup", "circulantEmbedding")
+#importFrom("sp", "bubble", "coordinates<-")
 importFrom("coda", "crosscorr")
 importFrom("mvtnorm", "dmvnorm")
 
diff --git a/NEWS b/NEWS
index ea714af..be2d1e7 100644
--- a/NEWS
+++ b/NEWS
@@ -1,3 +1,7 @@
+CHANGES in 0.2.10 (2023-11-04)
+
+  * Remove plotrix from dependencies
+
 CHANGES in 0.2.9 (2023-08-21)
 
   * Ken Kellner takes over as Maintainer
diff --git a/R/plot-Nmix-resi&map-Nmix-resi_AHM1_6-9-3_plotting.R b/R/plot-Nmix-resi&map-Nmix-resi_AHM1_6-9-3_plotting.R
index b213993..6fa1e18 100644
--- a/R/plot-Nmix-resi&map-Nmix-resi_AHM1_6-9-3_plotting.R
+++ b/R/plot-Nmix-resi&map-Nmix-resi_AHM1_6-9-3_plotting.R
@@ -51,6 +51,10 @@ map.Nmix.resi <- function(fm, x, y){
 #    object named fm, which was fit by function pcount in unmarked
 # Function arguments are the fitted model object and the x and y coordinates
 #    of every site
+
+# Load required package
+checkNamespace("sp")
+
 mean.resi <- apply(residuals(fm), 1, mean, na.rm = TRUE)
 mean.resi[mean.resi == "NaN"] <- mean(mean.resi, na.rm = TRUE)
 spdata <- data.frame(residuals = mean.resi, x = x, y = y)
diff --git a/R/simDynoccSpatial_AHM2_9.R b/R/simDynoccSpatial_AHM2_9.R
index bc9a3c1..c48d9e0 100644
--- a/R/simDynoccSpatial_AHM2_9.R
+++ b/R/simDynoccSpatial_AHM2_9.R
@@ -103,8 +103,10 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
 
   if(FALSE) {x <- NULL; rm(x)}  # Stops R CMD check choking on 'curve'.
   
-  # Load raster package------------------------------------------
+  # Load required packages --------------------------------------
   checkNamespace("raster")
+  checkNamespace("fields")
+  checkNamespace("spdep")
 
   # Checks and fixes for input data -----------------------------
   side <- round(side[1])
@@ -167,8 +169,8 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
     message("Using package 'fields' instead of 'RandomFields'; see help(simDynoccSpatial).")
     if(!is.na(seed.XAC))
       set.seed(seed.XAC)
-    obj <- circulantEmbeddingSetup(grid=list(x=xcoord, y=ycoord), Covariance="Exponential", aRange=theta.XAC)
-    tmp <- try(circulantEmbedding(obj), silent=TRUE)
+    obj <- fields::circulantEmbeddingSetup(grid=list(x=xcoord, y=ycoord), Covariance="Exponential", aRange=theta.XAC)
+    tmp <- try(fields::circulantEmbedding(obj), silent=TRUE)
     if(inherits(tmp, "try-error"))
       stop("Simulation of random field failed.\nTry with smaller values for 'side' or 'theta.XAC'.")
     XAC <- matrix(tmp, ncol = side, byrow = TRUE)
diff --git a/R/simExpCorrRF.R b/R/simExpCorrRF.R
index 70bb909..f687950 100644
--- a/R/simExpCorrRF.R
+++ b/R/simExpCorrRF.R
@@ -30,8 +30,9 @@ simExpCorrRF <- function(variance = 1, theta = 1, size = 50, seed = NA, show.plo
 # show.plot: if TRUE, plots of the data will be displayed;
 #  set to FALSE if you are running simulations or use inside of other fct's.
 
-# Load raster package
+# Load required packages
 checkNamespace("raster")
+checkNamespace("fields")
 
 # Generate correlated random variables in a square
 step <- 1
@@ -50,8 +51,8 @@ grid <- cbind(x = rep(x, each=size), y = y)
  message("Using package 'fields' instead of 'RandomFields'; see help(simExpCorrRF).")
   if(!is.na(seed))
     set.seed(seed)  # Only for compatibility with RandomFields, better to set seed before calling simExpCommRF
-  obj <- circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta)
-  tmp <- try(circulantEmbedding(obj), silent=TRUE)
+  obj <- fields::circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta)
+  tmp <- try(fields::circulantEmbedding(obj), silent=TRUE)
   if(inherits(tmp, "try-error"))
     stop("Simulation of random field failed.\nTry with smaller values for 'size' or 'theta'.")
   field <- as.vector(tmp * sqrt(variance))
diff --git a/R/simPPe_AHM2_10.R b/R/simPPe_AHM2_10.R
index 0187e45..1023fdb 100644
--- a/R/simPPe_AHM2_10.R
+++ b/R/simPPe_AHM2_10.R
@@ -33,8 +33,9 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
   #    (this is the parameter of the gridding process
   #    and determines the size of the quadrats)
 
-  # -------------- Load raster package -----------------------
+  # -------------- Load required packages --------------------
   checkNamespace("raster")
+  checkNamespace("fields")
 
   # -------------- Check and fix input -----------------------
   buffer.width <- round(buffer.width[1])
@@ -84,8 +85,8 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
   #    x=x, y=y, grid=TRUE)@data$variable1, ncol = lscape.size) # MVN r.v. with spatial correlation
   #} else {
     message("Using package 'fields' instead of 'RandomFields'; see help(simPPe).")
-    obj <- circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta.X)
-    tmp <- try(circulantEmbedding(obj), silent=TRUE)
+    obj <- fields::circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta.X)
+    tmp <- try(fields::circulantEmbedding(obj), silent=TRUE)
     if(inherits(tmp, "try-error"))
       stop("Simulation of random field failed.\nTry with smaller values for 'lscape.size' or 'theta.X'.")
     field <- matrix(tmp * sqrt(variance.X), ncol = lscape.size)
diff --git a/inst/RandomFieldsSupport/simDynoccSpatial.R b/inst/RandomFieldsSupport/simDynoccSpatial.R
index 4bb53af..01fa6b1 100644
--- a/inst/RandomFieldsSupport/simDynoccSpatial.R
+++ b/inst/RandomFieldsSupport/simDynoccSpatial.R
@@ -103,6 +103,9 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
 
   if(FALSE) {x <- NULL; rm(x)}  # Stops R CMD check choking on 'curve'.
 
+  checkNamespace("raster")
+  checkNamespace("fields")
+
   # Checks and fixes for input data -----------------------------
   side <- round(side[1])
   nyears <- round(nyears[1])
@@ -164,8 +167,8 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
     message("Using package 'fields' instead of 'RandomFields'; see help(simDynoccSpatial).")
     if(!is.na(seed.XAC))
       set.seed(seed.XAC)
-    obj <- circulantEmbeddingSetup(grid=list(x=xcoord, y=ycoord), Covariance="Exponential", aRange=theta.XAC)
-    tmp <- try(circulantEmbedding(obj), silent=TRUE)
+    obj <- fields::circulantEmbeddingSetup(grid=list(x=xcoord, y=ycoord), Covariance="Exponential", aRange=theta.XAC)
+    tmp <- try(fields::circulantEmbedding(obj), silent=TRUE)
     if(inherits(tmp, "try-error"))
       stop("Simulation of random field failed.\nTry with smaller values for 'side' or 'theta.XAC'.")
     XAC <- matrix(tmp, ncol = side, byrow = TRUE)
@@ -228,19 +231,19 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
 
       # Plot random field covariate XAC
       # rows are in x, columns in y direction
-      image(1:side, 1:side, XAC, col=topo.colors(100), 
+      raster::image(1:side, 1:side, XAC, col=topo.colors(100), 
           main = paste("Gaussian random field XAC with \n neg. exponential correlation (range =", theta.XAC, ")"), 
           xlab = 'x', ylab = 'y')
 
-      image(1:side, 1:side, psi[,,1], col=topo.colors(100),
+      raster::image(1:side, 1:side, psi[,,1], col=topo.colors(100),
           main = paste("Initial occupancy probability"), xlab = 'x', ylab = 'y')
 
-      image(1:side, 1:side, z[,,1], col=c("white", "black"), 
+      raster::image(1:side, 1:side, z[,,1], col=c("white", "black"), 
           main = paste("Initial presence/absence (true system state z):\n black = occupied, white = unoccupied"),
           xlab = 'x', ylab = 'y')
       abline(h = 0:side+0.5, v = 0:side+0.5, col = "lightgrey")
 
-      image(1:side, 1:side, Xauto[,,1], col=topo.colors(100), 
+      raster::image(1:side, 1:side, Xauto[,,1], col=topo.colors(100), 
           main = "Autocovariate between year 1 and year 2", xlab = 'x', ylab = 'y')
     }, silent = TRUE)
     if(inherits(tryPlot, "try-error")) {
@@ -272,15 +275,15 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
     # --------------------
     if(show.plots) {
       tryPlot <- try( {
-        image(1:side, 1:side, phi[,,k-1], col=topo.colors(100),
+        raster::image(1:side, 1:side, phi[,,k-1], col=topo.colors(100),
               main = paste("Persistence between year", k-1, "and year", k), xlab = 'x', ylab = 'y')
-        image(1:side, 1:side, gamma[,,k-1], col=topo.colors(100),
+        raster::image(1:side, 1:side, gamma[,,k-1], col=topo.colors(100),
               main = paste("Colonization between year", k-1, "and year", k), xlab = 'x', ylab = 'y')
-        image(1:side, 1:side, z[,,k], col=c("white", "black"),
+        raster::image(1:side, 1:side, z[,,k], col=c("white", "black"),
             main = paste('Presence/absence (z) in year', k, ':\n black = occupied, white = unoccupied'),
             xlab = 'x', ylab = 'y')
         abline(h = 0:side+0.5, v = 0:side+0.5, col = "lightgrey")
-        image(1:side, 1:side, Xauto[,,k], col=topo.colors(100),
+        raster::image(1:side, 1:side, Xauto[,,k], col=topo.colors(100),
             main = paste("Autocovariate between year", k, "and year", k+1), xlab = 'x', ylab = 'y')
       }, silent = TRUE)
       if(inherits(tryPlot, "try-error")) {
@@ -312,7 +315,7 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
     for(j in 1:nsurveys){               # Loop over replicates
       prob <- z[,,k] * p[,,j,k]  # zero out p for unoccupied sites
       y[,,j,k] <- rbinom(M, 1, prob)
-    # image(1:side, 1:side, y[,,j,k], main = paste("Year", k, "and rep", j))
+    # raster::image(1:side, 1:side, y[,,j,k], main = paste("Year", k, "and rep", j))
         # Look at clumped pattern in y
     }
   }
@@ -345,9 +348,9 @@ simDynoccSpatial <- function(side = 50, nyears = 10, nsurveys = 3,
       # Plots comparing true and observed latent states
       par(mfrow = c(2,2), mar = c(5,4,5,2), cex.main = 1.3, cex.lab = 1.5, cex.axis = 1.2)
       for(k in 1:nyears){
-        image(1:side, 1:side, z[,,k], col=c("white", "black"), main = paste('Presence/absence (z) in year', k), xlab = 'x', ylab = 'y')
+        raster::image(1:side, 1:side, z[,,k], col=c("white", "black"), main = paste('Presence/absence (z) in year', k), xlab = 'x', ylab = 'y')
         abline(h = 0:side+0.5, v = 0:side+0.5, col = "lightgrey")
-        image(1:side, 1:side, zobs[,,k], col=c("white", "black"), main = paste('Ever_detected (zobs) in year', k), xlab = 'x', ylab = 'y')
+        raster::image(1:side, 1:side, zobs[,,k], col=c("white", "black"), main = paste('Ever_detected (zobs) in year', k), xlab = 'x', ylab = 'y')
         abline(h = 0:side+0.5, v = 0:side+0.5, col = "lightgrey")
       }
     }, silent = TRUE)
diff --git a/inst/RandomFieldsSupport/simExpCorrRF.R b/inst/RandomFieldsSupport/simExpCorrRF.R
index 225c263..72249cf 100644
--- a/inst/RandomFieldsSupport/simExpCorrRF.R
+++ b/inst/RandomFieldsSupport/simExpCorrRF.R
@@ -29,6 +29,9 @@ simExpCorrRF <- function(variance = 1, theta = 1, size = 50, seed = NA, show.plo
 # show.plot: if TRUE, plots of the data will be displayed;
 #  set to FALSE if you are running simulations or use inside of other fct's.
 
+checkNamespace("raster")
+checkNamespace("fields")
+
 # Generate correlated random variables in a square
 step <- 1
 x <- seq(1, size, step)
@@ -45,8 +48,8 @@ if(requireNamespace("RandomFields", quietly=TRUE)) {
  message("Using package 'fields' instead of 'RandomFields'; see help(simExpCorrRF).")
   if(!is.na(seed))
     set.seed(seed)  # Only for compatibility with RandomFields, better to set seed before calling simExpCommRF
-  obj <- circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta)
-  tmp <- try(circulantEmbedding(obj), silent=TRUE)
+  obj <- fields::circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta)
+  tmp <- try(fields::circulantEmbedding(obj), silent=TRUE)
   if(inherits(tmp, "try-error"))
     stop("Simulation of random field failed.\nTry with smaller values for 'size' or 'theta'.")
   field <- as.vector(tmp * sqrt(variance))
@@ -65,7 +68,7 @@ if(show.plots){
     # Random field
     # image(x, y, field,col=topo.colors(20), main = paste("Gaussian random field with \n negative exponential correlation (theta =", theta, ")"), cex.main = 1)
     par(mar = c(3,2,5,1))
-    raster::plot(rasterFromXYZ(cbind(grid, field)), col=topo.colors(20),
+    raster::plot(raster::rasterFromXYZ(cbind(grid, field)), col=topo.colors(20),
     main = paste("Gaussian random field with \n negative exponential correlation (theta =", theta, ")"), cex.main = 1, legend=FALSE, box=FALSE)
     box()
   }, silent = TRUE)
diff --git a/inst/RandomFieldsSupport/simPPe.R b/inst/RandomFieldsSupport/simPPe.R
index cd25af4..f8ddb8a 100644
--- a/inst/RandomFieldsSupport/simPPe.R
+++ b/inst/RandomFieldsSupport/simPPe.R
@@ -32,6 +32,9 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
   # quads.along.side: number of quadrats along the side of the core area
   #    (this is the parameter of the gridding process
   #    and determines the size of the quadrats)
+  
+  checkNamespace("raster")
+  checkNamespace("field")
 
   # -------------- Check and fix input -----------------------
   buffer.width <- round(buffer.width[1])
@@ -81,8 +84,8 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
       x=x, y=y, grid=TRUE)@data$variable1, ncol = lscape.size) # MVN r.v. with spatial correlation
   } else {
     message("Using package 'fields' instead of 'RandomFields'; see help(simPPe).")
-    obj <- circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta.X)
-    tmp <- try(circulantEmbedding(obj), silent=TRUE)
+    obj <- fields::circulantEmbeddingSetup(grid=list(x=x, y=y), Covariance="Exponential", aRange=theta.X)
+    tmp <- try(fields::circulantEmbedding(obj), silent=TRUE)
     if(inherits(tmp, "try-error"))
       stop("Simulation of random field failed.\nTry with smaller values for 'lscape.size' or 'theta.X'.")
     field <- matrix(tmp * sqrt(variance.X), ncol = lscape.size)
@@ -125,7 +128,7 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
     tryPlot <- try( {
       # *** Fig. 1: Original point pattern
       # Random field of X with activity-centers overlaid
-      image(rasterFromXYZ(cbind(grid, c(field))), col=topo.colors(10),
+      raster::image(raster::rasterFromXYZ(cbind(grid, c(field))), col=topo.colors(10),
           main = "Point pattern with\ncore and buffer area",
           xlab = "", ylab = "", axes = FALSE, asp = 1)
       mtext(paste("Mean intensity (lambda) =", round(lambda_pp, 5)), side=1)
@@ -138,7 +141,7 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
       # *** Fig. 2: Show abundance and presence/absence in each quadrat on original landscape ***
       # Covariate 1: the Gaussian random field with autocorrelation
       # Reproduce random field with activity centers
-      image(rasterFromXYZ(cbind(grid, c(field))), col=topo.colors(10), main = "Abundance, N",
+      raster::image(raster::rasterFromXYZ(cbind(grid, c(field))), col=topo.colors(10), main = "Abundance, N",
           xlab = "", ylab = "", axes = FALSE, asp = 1)
       mtext(paste0("Mean(N) = ", E_N, ", var(N) = ", round(var(c(Nac)), 2)), side=1)
       polygon(c(buffer.width, size.core+buffer.width, size.core+buffer.width, buffer.width),
@@ -161,7 +164,7 @@ simPPe <- function(lscape.size = 150, buffer.width = 25, variance.X = 1, theta.X
 
       # Figure 3 for presence/absence of activity centers (= distribution)
       # Reproduce random field with activity centers
-      image(rasterFromXYZ(cbind(grid, c(field))), col=topo.colors(10), main = "Occurrence, z",
+      raster::image(raster::rasterFromXYZ(cbind(grid, c(field))), col=topo.colors(10), main = "Occurrence, z",
           xlab = "", ylab = "", axes = FALSE, asp = 1)
       mtext(paste("Mean(z) =", E_z), side=1)
       polygon(c(buffer.width, size.core+buffer.width, size.core+buffer.width, buffer.width),