An example of using rbind_ggplot

rbind_ggplot_example.R

library(ggplot2)
library(lubridate)
libarry(ggthemes)
# Create a series of dates (hourly)
hourly_date <- seq.POSIXt(dmy("01012012"), dmy("31122012"), by = "1 hour")
# Create some fictional fdom data.
fdom <- data.frame(date = hourly_date, fdom = sin(1:length(hourly_date)/300)+10)

# Create a series of dates (daily)
daily_date <- seq.POSIXt(dmy("01012012"), dmy("31122012"), by = "1 day")
# Sample the daily dates (take 30 samples for the year)
samples <- sample(daily_date, 30)
# order the dates
sampels <- sort(samples)
doc <- data.frame(date = samples, doc = rnorm(30, 10, 3))
library(scales)
# Create the fdom plot (Need to scale the x axis sto ensure the start and end are the same on both plots.)
plot1 <- ggplot() + geom_line(aes(x=date, y=fdom), fdom) + theme_few(20) + 
  ylab("FDOM (QSU)") + 
  scale_x_datetime(limits = c(ymd("2012-01-01"),ymd("2012-12-31")))
plot1
# Create the doc plot
plot2 <- ggplot() + geom_point(aes(x=date, y= doc), doc) + theme_few(20) + 
  ylab(expression(paste("DOC (mg",L^{-1},")"))) +
  scale_x_datetime(limits = c(ymd("2012-01-01"),ymd("2012-12-31")))
plot2


# Now to combine the two plots together.
library(gridExtra)
library(gtable)
grid.arrange(plot1, plot2, ncol=1)
# The problem is that the plots are not aligned. 
# The following function will take care of that.
rbind_ggplot <- function(...){
  ## Taken and modified from http://stackoverflow.com/questions/13294952/
  ggplots <- list(...)
  if(!all(sapply(ggplots, is.ggplot))){
    stop("All objects must be of class ggplot (see ?is.ggplot)")
  }
  gtl <- lapply(ggplots, ggplotGrob)
  
  bind2 <- function (x, y) 
  {
    if(ncol(x) != ncol(y)){
      stop("plots have incorrect dimensions")
    }
    if (nrow(x) == 0) 
      return(y)
    if (nrow(y) == 0) 
      return(x)
    y$layout$t <- y$layout$t + nrow(x)
    y$layout$b <- y$layout$b + nrow(x)
    x$layout <- rbind(x$layout, y$layout)
    x$heights <- gtable:::insert.unit(x$heights, y$heights)
    x$rownames <- c(x$rownames, y$rownames)
    x$widths <- grid::unit.pmax(x$widths, y$widths)
    x$grobs <- append(x$grobs, y$grobs)
    x
  }
  
  Reduce(bind2, gtl)
}

## The rbind_ggplot function is now done within the grid.arrange function.
grid.arrange(rbind_ggplot(plot1, plot2), ncol=1)

## The next step is to remove the x axis labels on the fdom plot
plot1 <- plot1 + theme(axis.ticks.x = element_blank(), axis.text.x = element_blank(), axis.title.x = element_blank())
plot1
# And putting it back into the grid.arrange
grid.arrange(rbind_ggplot(plot1, plot2), ncol=1)

### Now if you want to have a legend for your plots. 
# Crate a data.frame with 3 sites of fdom
fdom <- data.frame(date = hourly_date, 
                   fdom_bog = sin(1:length(hourly_date)/300)+10,
                   fdom_outlet = sin(1:length(hourly_date)/300)+5,
                   fdom_girnock = sin(1:length(hourly_date)/300)+2
)
# Reshape the data frame to make only 3 columns
library(reshape2)
fdom <- melt(fdom, id.var="date")
# Now there is a date column, a variable column (fdom for each site) and the assoicated fdom value
head(fdom)
# Now make the same plot as before but use the variable to do the colouring of the line.
plot1 <- ggplot() + geom_line(aes(date, value, colour=variable), fdom) + theme_few(20) + 
  scale_colour_discrete("Legend title", labels = c("Bog", "Outlet", "Girnock")) + 
  ylab("FDOM (QSU)") + 
  scale_x_datetime(limits = c(ymd("2012-01-01"),ymd("2012-12-31")))
plot1

# And now for the DOC.
doc <- data.frame(date = samples, 
                  doc_bog = rnorm(30, 10, 3),
                  doc_outlet = rnorm(30, 10, 2),
                  doc_girnock = rnorm(30, 10, 1)
)
doc <- melt(doc, id.var="date")

# I added the dashed line to make it a little easier to see the trend. 
plot2 <- ggplot() + geom_point(aes(date, value, colour=variable), size = 2, doc) + 
  geom_line(aes(date, value, colour=variable), linetype = 2, doc) + 
  theme_few(20) + 
  scale_colour_discrete("Legend title", labels = c("Bog", "Outlet", "Girnock")) + 
  ylab(expression(paste("DOC (mg",L^{-1},")"))) +
  scale_x_datetime(limits = c(ymd("2012-01-01"),ymd("2012-12-31")))

plot2  


grid.arrange(rbind_ggplot(plot1, plot2), ncol=1)