Introduction

Lately, I was plotting a lot of spatial statistic functions, comparing them and trying to make a sense out of them.
To facilitate the procedure I wrote the following function to create a plot for the spatstat class ‘fv’, combined with ‘Quantum Plots’ from:

Esser, D. S., Leveau, J. H. J., Meyer, K. M., & Wiegand, K. (2014). Spatial scales of interactions among bacteria and between bacteria and the leaf surface. FEMS Microbiology Ecology, 91(3), fiu034. http://doi.org/10.1093/femsec/fiu034

The colored bands at the bottom of the plot highlight the spatial scales at which the summary statistics deviate from the simulation envelopes.

Function

quantumPlot <- function(x,colour=c("#d73027", "#ffffbf", "#91bfdb")){

  # load Packages
  require(ggplot2)
  require(ggthemes)

  # convert fv to dataframe
  env.data <- as.data.frame(tree.data)
  env.data <- env.data[-1,]

  # plot it
  gg_quantomPlot <- ggplot(env.data, aes(r, obs))+
                            # plot observed value
                            geom_line(colour=c("#4d4d4d"))+
                            # plot simulation envelopes
                            geom_ribbon(aes(ymin=lo,ymax=hi),alpha=0.1, colour=c("#e0e0e0")) +
                            # axes names and limits
                            ylim(min(env.data$obs)-1, max(env.data$obs)+2) +
                            xlab("Distance r (m)") +
                            ylab("summary statistic") +
                            # plot expected value, according to null model
                            geom_hline(yintercept=1, linetype = "dashed", colour=c("#999999")) +
                            # plot 'Quantums'
                            geom_rug(data=env.data[env.data$obs > env.data$hi,], sides="b", colour=colour[1])  +
                            geom_rug(data=env.data[env.data$obs < env.data$lo,], sides="b", colour=colour[2]) +
                            geom_rug(data=env.data[env.data$obs >= env.data$lo & env.data$obs <= env.data$hi,], sides="b", color=colour[3]) +
                            # make it look beautiful
                            theme_tufte()
  return(gg_quantomPlot)
}

https://gist.github.com/marcosci/e261a586f82d8575a843

Now you can give the result your envelope-fv object and plot it:

attach(redwood)
redwood.pcf <- envelope(redwood, fun=pcf)
quantumPlot(redwood.pcf)