1 Grammar of Graphics for base plot

1.1 Aesthetic mapping

bb_aes() for aesthetic mapping, that equivalents to ggplot2::aes().

library(plotbb)

p <- bbplot(mtcars, bb_aes(mpg, disp, col=factor(cyl)))
p + bb_grid(col='grey50', lty='dashed') + bb_point(pch=19)

1.2 Geometric layer

p2 <- p + bb_point() + bb_lm(bb_aes(group=cyl), lwd=2)
p3 <- p2 + bb_lm(col="red", lwd=3, lty='dotted')
p4 <- p + bb_text(bb_aes(label=cyl), cex=2)
par(mfrow=c(1,3))
p2; p3; p4

1.2.1 Heatmap

df <- data.frame(x = rep(1:10, 12),
                 y = rep(1:12, each = 10),
                 values = rnorm(120, mean = 10, sd = 5),
                 type = sample(LETTERS[1:5], 120, replace=TRUE),
                 stringsAsFactors = FALSE)
par(mfrow=c(2,2))
bbplot(df, bb_aes(x,y, col=values)) + bb_tile() + 
  bb_title("heatmap for continuous numerical values") 
bbplot(df, bb_aes(x,y, col=values)) + bb_tile() + bb_scale_col_palette("YlOrRd") +
  bb_title("applying a color palette") 
bbplot(df, bb_aes(x,y, col=type)) + bb_tile() +
  bb_title("heatmap for discrete categorical values") 
bbplot(df, bb_aes(x,y, col=values)) + bb_tile() + bb_text(col='black') +
  bb_title("heatmap with text labels") + bb_theme_expand()

1.3 Setting labels

p2 + bb_labs(title = "hello", sub = "just for demo",
              xlab="this is xlab", ylab = "this is ylab") +
  bb_title("hello world") # last one rules

1.4 Theme

g <- p2 +
     bb_theme(col.main="red", cex.main=2,
             mar = c(4, 4, 3, 1)) +
     bb_title("applying graphics::par")
par(mfrow=c(1,2))
print(g) 
p2 + bb_title("theme has no side effect")

bb_theme has no side effect and will only apply to the bbplot object that it added to. This is very important for developing pre-defined themes.

par(mfrow=c(1,2)) 
p3 + bb_theme_expand()
print(p3)

p + bb_grid(col='grey50', lty='dashed') +
  bb_point(pch=19) +
  bb_theme_expand() +
  bb_theme_grey()

p + bb_point(pch=19, cex=2) +
  bb_theme_expand() +
  bb_theme_deepblue()

1.4.1 TODO

bb_theme_expand
bb_theme_grey
bb_theme_deepblue
develop more pre-defined themes

1.5 Scale

bb_scale_col_palette
more to be implemented

1.6 Legend

Not yet implemented

1.7 Using existing code with plotbb

Suppose we have existing code to plot something:

plot(mtcars$mpg, mtcars$disp)
abline(lm(disp ~ mpg, data=mtcars), col='red')

We can wrap the codes into a function:

f <- function() { 
  plot(mtcars$mpg, mtcars$disp)
  abline(lm(disp ~ mpg, data=mtcars), col='red')
}

Then we can convert it to a bbplot object. The plot produced by the function will be used as the canvas, and we can apply theme and add layers to it:

library(dplyr) 
d <- group_by(mtcars, cyl) %>%
  summarize(xm=mean(mpg), ym=mean(disp))

pp <- as.bbplot(f) +
   bb_theme_expand() +
   bb_theme_grey() +
   bb_lm(bb_aes(mpg, disp, group=cyl, col=factor(cyl)), data=mtcars, lwd=2, lty='dashed') +
   bb_point(bb_aes(xm, ym, col=factor(cyl)), data=d, pch=19, cex=2) +
   bb_title("hello plotbb") +
   bb_grid(col='grey30', lty='dashed') ## grid lines were plotted as background by default

As there are many features currently not available, plotbb supports adding layers using base graphics commands that you are already familiar with. Any base graphics commands in formula, expression or function can be served as layer to be added to a bbplot object.

pp + (~points(30, 400, pch=19, col="red", cex=3)) + 
   ~text(30, 420, label="hae fun :)", col="blue", cex=1.2)

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