##########################################################
##                                                      ##
##  Real and Simulated Spatial PP.r                     ##
##                                                      ##
##  Jonathan Reuning-Scherer, Yale University           ##
##  FES 781 Applied Spatial Statistics                  ##
##  Revised Feb 2014                                    ##
##                                                      ##
##########################################################





#Graphs showing differece between CSR and separation

#make four plots per page
par(mfrow=c(2,2))


#complete randomness
x<-runif(50,0,10)
y<-runif(50,0,10)
plot(x,y, pch=19,col='red',cex=1.2,main="CSR",xlab='x',ylab='y')

#separation spatially
x<-runif(50,0,1)+rep(c(1:10),5)
y<-runif(50,0,1)+c(t(matrix(rep(c(1:10),5),ncol=5)))
plot(x,y, pch=19,col='red',cex=1.2,main="Systematic Process",xlab='x',ylab='y')

#10 Clustered process
xa<-runif(50)
ya<-runif(50)
movex<-runif(10,1,10)
movex<-sort(rep(movex,5))+xa
movey<-runif(10,1,10)
movey<-rep(movey,each=5)+ya
plot(movex,movey,pch=19,cex=1.2,col='red', main="Clustered Process",xlab='x',ylab='y')

#10 Regular Clusters

xsmile<-rep(c(1.5,3,5,7,8.5,5,2.5,7.5),6)+runif(48)
ysmile<-rep(c(3,1.5,1,1.5,3,5,8,8),6)+runif(48)
plot(xsmile,ysmile,pch=19,cex=1.2,col='red', main="Regular Clustered Process",xlab='x',ylab='y',
   xlim=c(1,10),ylim=c(1,10))


#another way to do generate a CSR using the spatstat package
library(spatstat)

#make one plot per page
par(mfrow=c(1,1))


#generate a CSR over the range (0,10) x (0,10) with mean 1 per unit square
pois1<-rpoispp(1,win=owin(xrange=c(0,10),yrange=c(0,10)))
plot(pois1$x,pois1$y, main="CSR process Using SPATSTAT", col="red", xlab="", ylab="")