how to use black-and-white fill patterns instead of color coding on Calendar Heatmap

Question

I\'m using Paul Bleicher\'s Calendar Heatmap to visualize some events over time and I\'m interested to add black-and-white fill patterns instead of (or on top of) the color

Answer 1

You can panel.level.plot from latticeExtra to add pattern. I think the question as it is asked is a little bit specific. So I try to generalize it. The idea is to give the steps to transform a time series to a calendar heatmap: with 2 patterns (fill color and a shape). We can imagine multiple time series (Close/Open). For example, you can get something like this

or like this, using a ggplot2 theme:

The function calendarHeat , giving a single time series (dat,value) , transforms data like this :

   date.seq value dotw woty   yr month seq
1 2012-01-01    NA    0    2 2012     1   1
2 2012-01-02    NA    1    2 2012     1   2
3 2012-01-03    NA    2    2 2012     1   3
4 2012-01-04    NA    3    2 2012     1   4
5 2012-01-05    NA    4    2 2012     1   5
6 2012-01-06    NA    5    2 2012     1   6

So I assume that I have data formated like this, otherwise, I extracted from calendarHeat the part of data transformation in a function(see this gist)

 dat <- transformdata(stock.data$Date, stock.data$by)

Then the calendar is essentially a levelplot with custom sacles , custom theme and custom panel' function.

library(latticeExtra)
levelplot(value~woty*dotw | yr, data=dat, border = "black",
          layout = c(1, nyr%%7),
          col.regions = (calendar.pal(ncolors)),
          aspect='iso',
          between = list(x=0, y=c(1,1)),
          strip=TRUE,
          panel = function(...) {
            panel.levelplot(...)
            calendar.division(...)  
            panel.levelplot.points(...,na.rm=T,
                                   col='blue',alpha=0.5,
                                   ## you can play with cex and pch here to get the pattern you      
                                   ## like
                                   cex =dat$value/max(dat$value,na.rm=T)*3
                                   pch=ifelse(is.na(dat$value),NA,20),
                                   type = c("p"))

          },
          scales= scales,
          xlim =extendrange(dat$woty,f=0.01),
          ylim=extendrange(dat$dotw,f=0.1),
          cuts= ncolors - 1,
          colorkey= list(col = calendar.pal(ncolors), width = 0.6, height = 0.5),
          subscripts=TRUE,
          par.settings = calendar.theme)

Where the scales are:

 scales = list(
   x = list( at= c(seq(2.9, 52, by=4.42)),
             labels = month.abb,
             alternating = c(1, rep(0, (nyr-1))),
             tck=0,
             cex =1),
   y=list(
     at = c(0, 1, 2, 3, 4, 5, 6),
     labels = c("Sunday", "Monday", "Tuesday", "Wednesday", "Thursday",
                "Friday", "Saturday"),
     alternating = 1,
     cex =1,
     tck=0))

And the theme is setting as :

 calendar.theme <- list(
   xlab=NULL,ylab=NULL,
   strip.background = list(col = "transparent"),
   strip.border = list(col = "transparent"),
   axis.line = list(col="transparent"),
   par.strip.text=list(cex=2))

The panel function uses a function caelendar.division. In fact, the division of the grid(month black countour) is very long and is done using grid package in the hard way (panel focus...). I change it a little bit, and now I call it in the lattice panel function: caelendar.division.