ggbattleship - battleship curves with R and ggplot2, and some other methods

battleship_CAseriation.R

# From http://cainarchaeology.weebly.com/r-package-for-seriation-via-ca.html

library(CAseriation)
data("perfect_seriation")
#loads the sample dataset 

check.ca.plot(perfect_seriation,1,2) 
#plot the Correspondence Analysis scatterplot of the first 2 dimensions in order #to inspect data structure (e.g., seeking for the horseshoe effect)

sort.table(perfect_seriation,1)
#sort the input contingency table according to the scores of rows and columns categories on the 1 CA dimension; two seriation plots and a 'battleship' plot for the sorted table are also produced

plot.clusters.rows(perfect_seriation,1,2) 
#displays the CA scatterplot for row categories, with different clusters of points being given different colors 

plot.clusters.cols(perfect_seriation,1,2) 

battleships-r-help.r

 # https://stat.ethz.ch/pipermail/r-help//2012-November/339973.html
 library(plotrix)
 vessels<-matrix(c(zero=sample(1:10,5),one2ten=sample(5:20,5),
                       ten2hundred=sample(15:36,5),hundred2thousand=sample(10:16,5)),
                     ncol=4)
 battleship.plot(vessels,xlab="Number of passengers",
                     yaxlab=c("Barnacle","Maelstrom","Poopdeck","Seasick","Wallower"),
                     xaxlab=c("0","1-10","10-100","100-1000"))
 kiteChart(vessels,xlab="Number of passengers",ylab="Vessel",
               varlabels=c("Barnacle","Maelstrom","Poopdeck","Seasick","Wallower"),
               timelabels=c("0","1-10","10-100","100-1000"))



# Expanding on the idea of the battleship.plot, you can draw rectangles of 
# the right width with ggplot2 if you want.

Original data:

data2 <- read.csv(text=
"count, bin
7,0
11,1-10
6,11-100
13,101-1000
7,1001-10000
3,10001-100000
2,100001-1000000")
data2$bin <- ordered(data2$bin, 
levels=c("0","1-10","11-100","101-1000","1001-10000","10001-100000","100001-1000000"))

# Define the lower and upper reaches of each bin:

data2$low <- c(0,1,11,101,1001,10001,100001)
data2$high <- c(0,10,100,1000,10000,100000,1000000)

# And make multiple ones for different vessels (or whatever grouping):

data3 <- rbind(data2, data2, data2, data2)
data3$vessel <- rep(c("Barnacle","Maelstrom","Poopdeck","Seasick"),
                     each=7)
data3$count <- abs(data2$count + sample(-5:5, 7*4, replace=TRUE))

# With each bin taking the same size, regardless of its extent:

ggplot(data3) +
   geom_blank(aes(x=count/2, y=bin)) +
   geom_rect(aes(ymin=as.numeric(bin)-0.5, ymax=as.numeric(bin)+0.5,
                 xmin = -count/2, xmax = count/2)) +
   facet_grid(~vessel)

# Width (height, really) of rectangles is based on range. Since 
# logarithmic scale and exponential binning, rectangles are same height 
# (with some gaps due to discrete nature). Since log scale, still problems 
# with 0.

ggplot(data3) +
   geom_rect(aes(ymin=low, ymax=high, xmin=-count/2, xmax=count/2)) +
   facet_grid(~vessel) +
   scale_y_log10()

ggbattleship.R

library(reshape2)
library(ggplot2)
i <- melt(j) # j must be a dataframe with row names and col names
cat <- rep(1:as.integer(table(i[,1])[1]), length(unique(i[,1]) ))
ysep <- 0.475 # set horizontal separation between bars
breaks <- seq(0, round(max(i$value/2), digits = -1), length.out = 3)
xlabels <- c("", breaks[2:length(breaks)]*2)
ylabels <- row.names(j)
ggplot(i) +
  geom_rect(aes(ymin = cat - 1 * ysep, ymax = cat + 1 * ysep, xmin = -value/2, xmax = value/2), group = 'variable') +
  facet_grid(. ~variable) +
  theme(panel.grid = element_blank()) +
  scale_y_reverse(breaks = 1:as.integer(table(i[,1])[1]), 
                  labels = ylabels) +
  scale_x_continuous(breaks = breaks,
                     labels = xlabels)

seriation_battleship.R

# non-ggplot2 method for battleship plot, using the seriation package, which gives ordering functions
library('seriation')
data("Irish")
scale_by_rank <- function(x) apply(x, 2, rank)
x <- scale_by_rank(Irish[,-6])

## use the the sum of absolute rank differences
order <- c(
  seriate(dist(x, "minkowski", p = 1)),
  seriate(dist(t(x), "minkowski", p = 1))
)

## plot
bertinplot(x, order, options = list(panel = panel.squares))

tabular-plotBar

# https://www.rdocumentation.org/packages/tabula/versions/1.2.0/topics/plotBar

tesselle-tabula-Ford Diagram

https://packages.tesselle.org/tabula/reference/plot_ford.html