Spot Matrix in R with ggplot2

spot_matrix.R

##################################
#             Data
##################################

ops.mat <-
  matrix(c(392,  114,  250, 115, 115,  78,
           2349, 560,  428, 286, 226, 173,
           4037, 1215, 817, 879, 479, 337,
           966,  592,  142, 256,  90, 407),
        nrow=4, byrow=TRUE)
project.node.totals <- c(28047, 79005, 140853, 29529)

rownames(ops.mat) <- c("go", "c", "cpp", "fortran")
colnames(ops.mat) <- c("a = b","a == b","!a","a && b","a != b","&a")

scale.max.1 <- function(x) x / max(x)
ops.rate.mat <- scale.max.1(apply(ops.mat, 2, '/', project.node.totals))
ops.rate.df <- data.frame(reshape2::melt(ops.rate.mat, varnames=c("parser", "op"), value.name = "rate"))

##################################
#            Includes
##################################

install.packages(c("ggplot2", "bertin", "pals", "gridExtra"))
library(ggplot2)

##################################
#            Table
##################################

Hmisc::latex(ops.mat, title='')

##################################
#         Bertin Matrix
##################################

bertin::plot.bertin(ops.mat, main='', palette = c("black", "black"), showpalette = FALSE)

##################################
#            Heatmap
##################################

heatmap(ops.mat, Colv=NA, Rowv=NA, col=pals::parula(64))

##################################
#          Spot Matrix
##################################

ggplot(data=ops.rate.df, aes(op, parser)) + geom_point(aes(size = rate))

##################################
#       Spot Matrix Theme
##################################

spot.theme <- list(
  theme_classic(),
  theme(axis.ticks.x=element_blank(), axis.text.x=element_text(size = 19, angle = 90, hjust = 0)),
  theme(axis.ticks.y=element_blank(), axis.text.y=element_text(size = 19)),
  theme(axis.line=element_blank()),
  theme(text = element_text(size = 22)),
  theme(legend.position = "none"),
  theme(plot.margin = unit(c(10,10,10,10), "mm")),
  scale_size_continuous(range = c(-0.3, 15)),
  scale_x_discrete(position = "top"))


# Themed plot
ggplot(data=ops.rate.df, aes(op, parser)) + geom_point(aes(size = rate)) + spot.theme

##################################
#   Spot Matrix Variation Grid
##################################

colors <- pals::parula(10)[c(1,4,7,9)]

plain.spot  <- ggplot(ops.rate.df, aes(op, parser)) + spot.theme + ggtitle("Plain Spot") +
                   geom_point(colour = colors[[1]], aes(size = rate))

donut.spot  <- ggplot(ops.rate.df, aes(op, parser)) + spot.theme + ggtitle("Donut Spot") +
                   geom_point(colour = colors[[2]], aes(size = 1)) +
                   geom_point(colour = "white",     aes(size = scale.max.1(1/rate)))

center.spot <- ggplot(ops.rate.df, aes(op, parser)) + spot.theme + ggtitle("Center Spot") +
                   geom_point(colour = "gray20",    aes(size = 1)) +
                   geom_point(colour = colors[[3]], aes(size = rate))

ring.spot   <- ggplot(ops.rate.df, aes(op, parser)) + spot.theme + ggtitle("Ring Spot") +
                   geom_point(colour = "black",     aes(size = 1)) +
                   geom_point(colour = "white",     aes(size = 0.8)) +
                   geom_point(colour = colors[[4]], aes(size = 0.81*rate))

spot.grid <- gridExtra::grid.arrange(plain.spot, donut.spot, center.spot, ring.spot, nrow=2)

##################################
#       Colored Groups
##################################

op.type <- factor(c(1,2,2,2,2,3), labels=c("assignment", "logical", "address"))

ggplot(ops.rate.df, aes(op, parser)) + spot.theme +
    geom_point(colour = "black", aes(size = 1)) +
    geom_point(colour = "white", aes(size = 0.8)) +
    geom_point(aes(colour = op.type[op], size = 0.81*rate)) +
    scale_colour_manual(values = colors[2:4])