R/SimulationPlot.R

In Meiqian-Chen/GraphCpClust: This package is used to implement the change point estimation method and graph-based clustering method introduced in the three papers, and provide related data analysis.

#' Basic description
#'
#' @description  This fuction is used to compare graph-based clustering method and model-based clustering method introduced in Shi, Chen, Dong and Rao (2020)
#' @usage SimulationPlot()
#' @examples
#' SimulationPlot()
#' @seealso 
#' @export
SimulationPlot<-function(){
	add_legend <- function(...) {
	  opar <- par(fig=c(0, 1, 0, 1), oma=c(0, 0, 0, 0), 
	              mar=c(0, 0, 0, 0), new=TRUE)
	  on.exit(par(opar))
	  plot(0, 0, type='n', bty='n', xaxt='n', yaxt='n' )
	  legend(...)
	}

	
	fig2 <- function(...){
	  par(mar=c(3,3,4,2),oma=c(0,0,2,0))
	  layout(matrix(c(1,2,3),1,3,byrow=T))
	  
	  
	  #figure2#(1)
	  D=c(150);sigma=c(1:10)*0.1;loop.time=100;c(1,10,15)
	  set.seed(1)
	  s.e=1;d=D
	  y1=10*pnorm(-4+0.05*c(1:d))+rnorm(d,0,s.e)#
	  y2=c(rep(0,50),20*pnorm(-3+0.03*c(1:(d-50)))+rnorm(d-50,0,s.e))
	  y3=c(rep(0,100),5*pnorm(-2+0.07*c(1:(d-100)))+rnorm(d-100,0,s.e))
	  
	  plotchar=c(0,3,1)
	  linetype=c(1,3,5)
	  COL=c("blue","red","green")
	  
	  plot(c(1:d),y1,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[1],
	       pch=plotchar[1], col=COL[1],ylim=c(-5,25),main=expression(paste('T'==150) ),cex.main=1.4 ) 
	  lines(c(1:d),y2,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[2],
	        pch=plotchar[2], col=COL[2]) 
	  lines(c(1:d),y3,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[3],
	        pch=plotchar[3], col=COL[3]) 
	  
	  
	  #figure2#(2)
	  D=c(210);sigma=c(1:10)*0.1;loop.time=100;c(5,20,30)
	  set.seed(1)
	  s.e=1;d=D
	  y1=10*pnorm(-4+0.05*c(1:d))+rnorm(d,0,s.e)#
	  y2=c(rep(0,70),20*pnorm(-3+0.03*c(1:(d-70)))+rnorm(d-70,0,s.e))
	  y3=c(rep(0,140),5*pnorm(-2+0.07*c(1:(d-140)))+rnorm(d-140,0,s.e))
	  
	  plotchar=c(0,3,1)
	  linetype=c(1,3,5)
	  COL=c("blue","red","green")
	  
	  plot(c(1:d),y1,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[1],
	       pch=plotchar[1], col=COL[1],ylim=c(-5,25),main=expression(paste('T'==210) ),cex.main=1.4 ) 
	  lines(c(1:d),y2,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[2],
	        pch=plotchar[2], col=COL[2]) 
	  lines(c(1:d),y3,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[3],
	        pch=plotchar[3], col=COL[3]) 
	  
	  
	  
	  
	  #figure2#(3)
	  D=c(300);sigma=c(1:10)*0.1;loop.time=100;c(20,100,200)
	  set.seed(1)
	  s.e=1;d=D
	  y1=10*pnorm(-4+0.05*c(1:d))+rnorm(d,0,s.e)#
	  y2=c(rep(0,100),20*pnorm(-3+0.03*c(1:(d-100)))+rnorm(d-100,0,s.e))
	  y3=c(rep(0,200),5*pnorm(-2+0.07*c(1:(d-200)))+rnorm(d-200,0,s.e))
	  
	  plotchar=c(0,3,1)
	  linetype=c(1,3,5)
	  COL=c("blue","red","green")
	  
	  plot(c(1:d),y1,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[1],
	       pch=plotchar[1], col=COL[1],ylim=c(-5,25),main=expression(paste('T'==300) ),cex.main=1.4 ) 
	  lines(c(1:d),y2,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[2],
	        pch=plotchar[2], col=COL[2]) 
	  lines(c(1:d),y3,ylab="",xlab=expression(t),type="b", lwd=1.5,lty=linetype[3],
	        pch=plotchar[3], col=COL[3]) 
	  
	  add_legend("top", legend=c("Class 1","Class 2", "Class 3"),
	             cex=1.5, bty='n', horiz=TRUE, lty=linetype,lwd=1.5, pch=plotchar, col=COL  )
	  
	}


	
  fig3 <- function(...){
  	m1=readRDS(system.file("extdata/REg.rds",package="GraphCpClust"))
		t1=readRDS(system.file("extdata/REm.rds",package="GraphCpClust")) 
		m2=readRDS(system.file("extdata/REg2.rds",package="GraphCpClust"))
		t2=readRDS(system.file("extdata/REm2.rds",package="GraphCpClust")) 
		m3=readRDS(system.file("extdata/REg3.rds",package="GraphCpClust"))
		t3=readRDS(system.file("extdata/REm3.rds",package="GraphCpClust")) 
		##########end of simulation3

		#Figure 3
		plotchar=c(0,3)
		linetype=c(1,3)
		COL=c("blue","red")
		
		
		par(mar=c(3,3,5,2),oma=c(0,0,2,0))
		layout(matrix(c(1,2,3),1,3,byrow=T))
		
		plot(sigma,m1[1,],ylab=expression(paste("S"^"*")),xlab=expression(sigma), ylim=c(-1,1),type="b", lwd=1.5,lty=linetype[1],
		     pch=plotchar[1], col=COL[1],main=expression(paste('n'[1]==1, ", ",'n'[2]==10, ", ",'n'[3]==15,,", ",'T'==150) ),cex.main=1.4 ) 
		lines(sigma,t1[1,],type="b", lwd=1.5,lty=linetype[2],
		      pch=plotchar[2], col=COL[2]) 
		
		
		
		plot(sigma,m2[1,],
		     main=expression(paste('n'[1]==5,", ",'n'[2]==20,", ", 'n'[3]==30,", ",'T'==210)),ylab=expression(paste("S"^"*")),xlab=expression(sigma), ylim=c(-1,1),type="b", lwd=1.5,
		     lty=linetype[1],
		     pch=plotchar[1], col=COL[1],cex.main=1.4) 
		
		lines(sigma,t2[1,],type="b", lwd=1.5,lty=linetype[2],
		      pch=plotchar[2], col=COL[2]) 
		
		
		plot(sigma,m3[1,],
		     main=expression(paste('n'[1]==20,", ",'n'[2]==100, ", ",'n'[3]==200,", ",'T'==300)),ylab=expression(paste("S"^"*")),xlab=expression(sigma), ylim=c(-1,1),type="b", lwd=1.5,
		     lty=linetype[1],
		     pch=plotchar[1], col=COL[1],cex.main=1.4) 
		
		lines(sigma,t3[1,],type="b", lwd=1.5,lty=linetype[2],
		      pch=plotchar[2], col=COL[2]) 
		
		add_legend("top", legend=c("Graph-based clustering    ","Model-based clustering    "), 
		           cex=1.5, bty='n', horiz=TRUE, lty=linetype,lwd=1.5, pch=plotchar, col=COL  ) 
		
		
  }

  
  fig2()
  fig3()
}