How to build a crossword-like plot for a boolean matrix

Question

I have a boolean matrix:

mm <- structure(c(TRUE, TRUE, TRUE, FALSE, TRUE, FALSE, TRUE, FALSE, 
                  FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRU         


        

Answer 1

You can do this using ggplot2's geom_tile and reshape2's melt:

library(ggplot2)
library(reshape2)

melted <- melt(mm)
ggplot(melted, aes(x = Var2, y = Var1, fill = value)) + geom_tile() +
    scale_fill_manual(values = c("white", "black"))

To make it a bit neater, you could remove the legend and the gray edges with some adjustments to the theme:

ggplot(melted, aes(x = Var2, y = Var1, fill = value)) + geom_tile() +
    scale_fill_manual(values = c("white", "black")) +
    theme_bw() +
    theme(legend.position = "none")

Final output:

Answer 2

Here are a few more approaches to round out the graphics options.

1. base graphics with rect:

   plot.new()
   par(mar=rep(0, 4))
   plot.window(xlim=c(0, ncol(mm)), ylim=c(0, nrow(mm)), asp=1)
   o <- cbind(c(row(mm)), c(col(mm))) - 1
   rect(o[, 1], o[, 2], o[, 1] + 1, o[, 2] + 1, col=t(mm)[, ncol(mm):1])
   

   

2. lattice::levelplot and latticeExtra:

   library(latticeExtra)
   levelplot(t(mm)[, ncol(mm):1], asp=1, scales='sliced', 
             col.regions=c('white', 'black'), margin=FALSE, colorkey=FALSE) + 
     layer(panel.grid(h=nrow(mm)-1, v=ncol(mm)-1, col=1))
   

   

3. rasterVis::levelplot, raster, and latticeExtra:

   library(rasterVis)
   library(latticeExtra)
   levelplot(raster(mm), col.regions=c('white', 'black'), 
             margin=FALSE, colorkey=FALSE) + 
     layer(panel.grid(h=nrow(mm)-1, v=ncol(mm)-1, col=1))
   

   

4. sp::spplot, raster, and latticeExtra:

   library(raster)
   library(latticeExtra)
   spplot(raster(mm), colorkey=FALSE, col.regions=c('white', 'black')) +
     layer(panel.grid(h=nrow(mm)-1, v=ncol(mm)-1, col=1))
   

   

5. raster

   It can be a bit fiddly to set the graphics device's dimensions such that raster doesn't plot additional (partial) cells outside the intended x and y limits. When using this approach, if the goal is to export to e.g. png, I plot to windows/x11/quartz first and resize the window until the plotted area is as I'd intended, then query the device dimensions with dev.size() and use these values to determine the dimension ratio for plotting to png.

   plot(raster(mm), legend=FALSE, col=c('white', 'black'))
   abline(h=seq(0, 1, len=nrow(mm) + 1), 
          v=seq(0, 1, len=ncol(mm) + 1))
   

   

Answer 3

Here's an approach that uses qheat a wrapper for ggplot2 from the qdap package:

library(qdap)
qheat(t(data.frame(mm)), by.column=NULL, high="black", text.color =NA,
    grid="grey20") + guides(fill=FALSE)

Answer 4

Here's an approach using plot from the graphics package:

plot(rep(1:10, each = 10), rep(-(1:10), 10), axes = FALSE, ann = FALSE,
     pch = ifelse(mm, 0, 15), cex = 6, asp = 1, xpd = NA)