CODEWITHSUNDEEP
rggplot2statistics
p-robot
p-robot

Reputation: 4904

Custom scatterplot matrix using facet_grid in ggplot2

I'm trying to write a custom scatterplot matrix function in ggplot2 using facet_grid. My data have two categorical variables and one numeric variable.

I'd like to facet (make the scatterplot rows/cols) according to one of the categorical variables and change the plotting symbol according to the other categorical.

I do so by first constructing a larger dataset that includes all combinations (combs) of the categorical variable from which I'm creating the scatterplot panels.

My questions are:

Thanks in advance. 

require(ggplot2)

# Data
nC <- 5
nM <- 4

dat <- data.frame(
    Control = rep(LETTERS[1:nC], nM), 
    measure = rep(letters[1:nM], each = nC), 
    value = runif(nC*nM))

# Change factors to characters
dat <- within(dat, {
    Control <- as.character(Control)
    measure <- as.character(measure)
})
# Check, lapply(dat, class)

# Define scatterplot() function
scatterplotmatrix <- function(data,...){

    controls <- with(data, unique(Control))
    measures <- with(data, unique(measure))
    combs <- expand.grid(1:length(controls), 1:length(measures), 1:length(measures))

    # Add columns for values
    combs$value1 = 1
    combs$value2 = 0

    for ( i in 1:NROW(combs)){
        combs[i, "value1"] <- subset(data, subset = Control==controls[combs[i,1]] & measure == measures[combs[i,2]], select = value)
        combs[i, "value2"] <- subset(data, subset = Control==controls[combs[i,1]] & measure == measures[combs[i,3]], select = value)
    }

    for ( i in 1:NROW(combs)){
        combs[i,"Control"] <- controls[combs[i,1]]
        combs[i,"Measure1"] <- measures[combs[i,2]]
        combs[i,"Measure2"] <- measures[combs[i,3]]
    }

    # Final pairs plot
    plt <- ggplot(combs, aes(x = value1, y = value2, shape = Control)) + 
    geom_point(size = 8, colour = "#F8766D") + 
    facet_grid(Measure2 ~ Measure1) + 
    ylab("") + 
    xlab("") + 
    scale_x_continuous(breaks = c(0,0.5,1), labels = c("0", "0.5", "1"), limits = c(-0.05, 1.05)) + 
    scale_y_continuous(breaks = c(0,0.5,1), labels = c("0", "0.5", "1"), limits = c(-0.05, 1.05)) +
    geom_rect(data = subset(combs, subset = Measure1 == Measure2), colour='white', xmin = -Inf, xmax = Inf,ymin = -Inf,ymax = Inf) 

    return(plt)
}

# Call
plt1 <- scatterplotmatrix(dat)
plt1

Upvotes: 2

Views: 2041

Answers (1)

jlhoward
jlhoward

Reputation: 59355

I'm not aware of a way to move the panel strips (the labels) to the bottom or left. Also, it's not possible to format the individual panels separately (e.g., turn off the tick marks for just one facet). So if you really need these features, you will probably have to use something other than, or in addition to ggplot. You should really look into GGally, although I've never had much success with it.

As far as leaving some of the panels blank, here is a way.

nC <- 5; nM <- 4
set.seed(1)     # for reproducible example
dat <- data.frame(Control = rep(LETTERS[1:nC], nM), 
                  measure = rep(letters[1:nM], each = nC),
                  value = runif(nC*nM))

scatterplotmatrix <- function(data,...){
  require(ggplot2)
  require(data.table)
  require(plyr)      # for .(...)
  DT <- data.table(data,key="Control")
  gg <- DT[DT,allow.cartesian=T]
  setnames(gg,c("Control","H","x","V","y"))
  fmt <- function(x) format(x,nsmall=1)
  plt <- ggplot(gg, aes(x,y,shape = Control)) + 
    geom_point(subset=.(as.numeric(H)<as.numeric(V)),size=5, colour="#F8766D") + 
    facet_grid(V ~ H) + 
    ylab("") + xlab("") + 
    scale_x_continuous(breaks=c(0,0.5,1), labels=fmt, limits=c(-0.05, 1.05)) + 
    scale_y_continuous(breaks=c(0,0.5,1), labels=fmt, limits=c(-0.05, 1.05))   
  return(plt)
}
scatterplotmatrix(dat)

The main feature of this is the use of subset=.(as.numeric(H)<as.numeric(V)) in the call to geom_point(...). This subsets the dataset so you only get a point layer when the condition is met, e.g. in facets where is.numeric(H)<is.numeric(V). This works because I've left the H and V columns as factors and is.numeric(...) operating on a factor returns the levels, not the names.

The rest is just a more compact (and much faster) way of creating what you called comb.

Upvotes: 3

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