diff --git a/man/sp3.Rd b/man/sp3.Rd
index 7ce615006..58621f161 100644
--- a/man/sp3.Rd
+++ b/man/sp3.Rd
@@ -42,94 +42,108 @@ These data were collected to support research funded by the Kearney Foundation o
 ## this example investigates the concept of a "median profile"
 
 # required packages
-if(require(ape) & require(cluster)) {
-
-data(sp3)
-
-# generate a RGB version of soil colors
-# and convert to HSV for aggregation
-sp3$h <- NA ; sp3$s <- NA ; sp3$v <- NA
-sp3.rgb <- with(sp3, munsell2rgb(hue, value, chroma, return_triplets=TRUE))
-sp3[, c('h','s','v')] <- t(with(sp3.rgb, rgb2hsv(r, g, b, maxColorValue=1)))
-
-# promote to SoilProfileCollection
-depths(sp3) <- id ~ top + bottom
-
-# aggregate across entire collection
-a <- slab(sp3, fm= ~ clay + cec + ph + h + s + v, slab.structure=10)
-
-# check
-str(a)
-
-# convert back to wide format
-library(reshape)
-a.wide.q25 <- cast(a, top + bottom ~ variable, value=c('p.q25'))
-a.wide.q50 <- cast(a, top + bottom ~ variable, value=c('p.q50'))
-a.wide.q75 <- cast(a, top + bottom ~ variable, value=c('p.q75'))
-
-# add a new id for the 25th, 50th, and 75th percentile pedons
-a.wide.q25$id <- 'Q25'
-a.wide.q50$id <- 'Q50'
-a.wide.q75$id <- 'Q75'
-
-# combine original data with "mean profile"
-vars <- c('top','bottom','id','clay','cec','ph','h','s','v')
-# make data.frame version of sp3
-sp3.df <- as(sp3, 'data.frame')
-sp3.grouped <- rbind(
-sp3.df[, vars], a.wide.q25[, vars], a.wide.q50[, vars], a.wide.q75[, vars]
-)
-
-# re-constitute the soil color from HSV triplets
-# convert HSV back to standard R colors
-sp3.grouped$soil_color <- with(sp3.grouped, hsv(h, s, v))
-
-# give each horizon a name
-sp3.grouped$name <- paste(round(sp3.grouped$clay), '/' , 
-round(sp3.grouped$cec), '/', round(sp3.grouped$ph,1))
-
-
-
-## perform comparison, and convert to phylo class object
-## D is rescaled to [0,]
-d <- profile_compare(sp3.grouped, vars=c('clay','cec','ph'), max_d=100, 
-k=0.01, replace_na=TRUE, add_soil_flag=TRUE, rescale.result=TRUE)
-
-
-h <- agnes(d, method='ward')
-p <- ladderize(as.phylo(as.hclust(h)))
-
-
-# look at distance plot-- just the median profile
-plot_distance_graph(d, 12)
-
-# similarity relative to median profile (profile #12)
-round(1 - (as.matrix(d)[12, ] / max(as.matrix(d)[12, ])), 2)
-
-## make dendrogram + soil profiles
-# first promote to SoilProfileCollection
-depths(sp3.grouped) <- id ~ top + bottom
-
-# setup plot: note that D has a scale of [0,1]
-par(mar=c(1,1,1,1))
-p.plot <- plot(p, cex=0.8, label.offset=3, direction='up', y.lim=c(2,0), 
-x.lim=c(1.25,length(sp3.grouped)+1), show.tip.label=FALSE)
-
-# get the last plot geometry
-lastPP <- get("last_plot.phylo", envir = .PlotPhyloEnv)
-
-# the original labels, and new (indexed) order of pedons in dendrogram
-d.labels <- attr(d, 'Labels')
-
-new_order <- sapply(1:lastPP$Ntip,
-function(i) which(as.integer(lastPP$xx[1:lastPP$Ntip]) == i))
-
-# plot the profiles, in the ordering defined by the dendrogram
-# with a couple fudge factors to make them fit
-plot(sp3.grouped, color="soil_color", plot.order=new_order,
-scaling.factor=0.01, width=0.1, cex.names=0.5,
-y.offset=max(lastPP$yy)+0.1, add=TRUE)
-
+if (require(ape) & require(cluster)) {
+  data(sp3)
+  
+  # generate a RGB version of soil colors
+  # and convert to HSV for aggregation
+  sp3$h <- NA
+  sp3$s <- NA
+  sp3$v <- NA
+  sp3.rgb <- with(sp3, munsell2rgb(hue, value, chroma, return_triplets = TRUE))
+    
+  sp3[, c('h', 's', 'v')] <- t(with(sp3.rgb, rgb2hsv(r, g, b, maxColorValue = 1)))
+  
+  # promote to SoilProfileCollection
+  depths(sp3) <- id ~ top + bottom
+  
+  # aggregate across entire collection
+  a <- slab(sp3, fm = ~ clay + cec + ph + h + s + v, slab.structure = 10)
+  
+  # check
+  str(a)
+  
+  # convert back to wide format
+  library(data.table)
+  
+  a.wide.q25 <- dcast(a, top + bottom ~ variable, value.var = c('p.q25'))
+  a.wide.q50 <- dcast(a, top + bottom ~ variable, value.var = c('p.q50'))
+  a.wide.q75 <- dcast(a, top + bottom ~ variable, value.var = c('p.q75'))
+  
+  # add a new id for the 25th, 50th, and 75th percentile pedons
+  a.wide.q25$id <- 'Q25'
+  a.wide.q50$id <- 'Q50'
+  a.wide.q75$id <- 'Q75'
+  
+  # combine original data with "mean profile"
+  vars <- c('top', 'bottom', 'id', 'clay', 'cec', 'ph', 'h', 's', 'v')
+  # make data.frame version of sp3
+  sp3.df <- as(sp3, 'data.frame')
+  sp3.grouped <- rbind(sp3.df[, vars], a.wide.q25[, vars], a.wide.q50[, vars], a.wide.q75[, vars])
+  
+  # re-constitute the soil color from HSV triplets
+  # convert HSV back to standard R colors
+  sp3.grouped$soil_color <- with(sp3.grouped, hsv(h, s, v))
+  
+  # give each horizon a name
+  sp3.grouped$name <- paste(
+    round(sp3.grouped$clay),
+    '/' ,
+    round(sp3.grouped$cec),
+    '/',
+    round(sp3.grouped$ph, 1)
+  )
+
+  ## perform comparison, and convert to phylo class object
+  ## D is rescaled to [0,]
+  d <- profile_compare(
+                        sp3.grouped,
+                        vars = c('clay', 'cec', 'ph'),
+                        max_d = 100,
+                        k = 0.01,
+                        replace_na = TRUE,
+                        add_soil_flag = TRUE,
+                        rescale.result = TRUE
+                      )
+  
+  h <- agnes(d, method = 'ward')
+  p <- ladderize(as.phylo(as.hclust(h)))
+  
+  # look at distance plot-- just the median profile
+  plot_distance_graph(d, 12)
+  
+  # similarity relative to median profile (profile #12)
+  round(1 - (as.matrix(d)[12,] / max(as.matrix(d)[12,])), 2)
+  
+  ## make dendrogram + soil profiles
+  # first promote to SoilProfileCollection
+  depths(sp3.grouped) <- id ~ top + bottom
+  
+  # setup plot: note that D has a scale of [0,1]
+  par(mar = c(1, 1, 1, 1))
+
+  # get the last plot geometry
+  lastPP <- get("last_plot.phylo", envir = .PlotPhyloEnv)
+  
+  # the original labels, and new (indexed) order of pedons in dendrogram
+  d.labels <- attr(d, 'Labels')
+  
+  new_order <- sapply(1:lastPP$Ntip,
+                      function(i)
+                        which(as.integer(lastPP$xx[1:lastPP$Ntip]) == i))
+  
+  # plot the profiles, in the ordering defined by the dendrogram
+  # with a couple fudge factors to make them fit
+  plot(
+    sp3.grouped,
+    color = "soil_color",
+    plot.order = new_order,
+    scaling.factor = 0.01,
+    width = 0.1,
+    cex.names = 0.5,
+    y.offset = max(lastPP$yy) + 0.1,
+    add = TRUE
+  )
 }
 }