Implementing the pivot algorithm for self-avoiding walks in 2 dimensions

[curiouscoder]

rm(list=ls())

 RW2D<-function(N)
  {
    i<-0
    xdir<-0
    ydir<-0
    xpos<-vector()
    xpos[1]<-xdir
    ypos<-vector()
   ypos[1]<-ydir
    for (i in 1:N-1)
      {
        r<-runif(1)
        if(r<=0.25) {xdir<-xdir+1}
        if(r>0.25 && r<=0.5) {xdir<-xdir-1}
        if(r>0.5 && r<=0.75) {ydir<-ydir +1}
        if(r>0.75) {ydir<-ydir-1}
        xpos[i+1]<-xdir
        ypos[i+1]<-ydir
      }
    return(cbind(xpos,ypos))
  }
 rw<-RW2D(30)
 rw
 xmin<-min(rw[,1])
 xmax<-max(rw[,1])
 ymin<-min(rw[,2])
 ymax<-max(rw[,2])

 plot(rw[,1],rw[,2],type="l",xlab="x",ylab="y",main="Random Walk Simulation
 In Two Dimensions",col="green4",xlim=range(xmin:xmax),ylim=range(ymin:ymax))

install.packages("purrr")
library(purrr)
rdunif(1,30,1) #choosing a pivot
rotation<-function(theta)
{ 
 A= matrix(c(cos(theta),sin(theta),-sin(theta),cos(theta)),ncol=2,nrow=2,byrow=T)
 return(A)
}

r90=rotation(pi/2);r90
r180=rotation(pi)
r270=rotation(3*pi/2)
list_matrix=list(r90,r180,r270)

newchain = rw[0:pivot,];newchain
tempchain= rw[(pivot+1) :n,]; tempchain

for( i in 1: n-pivot)
{

#matrix(unlist(sample(list_matrix, size=1)),ncol=2)%*%tempchain[i,]

}

I'm trying to do the algorithm described here: https://arxiv.org/pdf/cond-mat/0109308.pdf

How do I store the resultant matrix?

[technocrat]

See the FAQ: How to do a minimal reproducible example reprex for beginners. This is almost it, aside from

@curiouscoder

newchain = rw[0:pivot,];newchain

pivot is missing. A reprex gives you a chance to catch that before posting.

A couple of minor things:

@curiouscoder

rm(list=ls())

is considered bad form, because someone running the reprex may have other objects in memory that they care, perhaps, deeply about.

@curiouscoder

install.packages("purrr")

also is bad form because it messes with the user's setup, which may be non-standard. Instead use

require(purrr)

Without pivot I can't test, but what you probably need to do is to "catch" the return value of the for loop. That's as simple as

my_result  <- for(i in seq_along(source_object) my_code