# Re: R-beta: help with R simulation

kjetil halvorsen (kjetil@wara.bolnet.bo)
Sun, 07 Sep 1997 20:25:58 -0400

```Date: Sun, 07 Sep 1997 20:25:58 -0400
From: kjetil halvorsen <kjetil@wara.bolnet.bo>
To: Bill Simpson <wsimpson@uwinnipeg.ca>
Subject: Re: R-beta: help with R simulation

I were running this under rapril.exe (windows 95), without any
changes, and it runs without problems:

> sim(10,10,2)
> objects()
[1] "do.sim" "sim"    "x"      "xm"     "y"      "ym"
> xm
[1]  129.02992309   63.87708251   37.27706587    0.05316485
100.24870778
[6]  -92.92987217  104.51354394  -12.88036980   65.85988750
-154.17145926
> ym
[1]   10.939346 -115.379259  -46.486649   -3.739839   -8.394732
11.185299
[7]  -91.186218   66.468282   -4.766670  -29.084236

Bill Simpson wrote:
>
> [[this bounced first, because it has 'help' in the Subject line ...
>   -- Martin Maechler
> ]]
>
> I am a complete novice R programmer. (Though I know C quite well)
>
> I am trying to write some R code to do the following simulation.
>
> There is a 2-frame "movie" of noise and signal dots.  the noise
> dots have random positions in each frame.  The signal dots are
> placed randomly in frame 1, but in frame 2 each signal dot's y
> coordinate is increment by jump (the dots jump upwards).
> I want to find the x and y distance from each dot in frame 1 to its
> nearest neighbour in frame 2.  In the simulation I will find the mean
> x and mean y distance for a given pair of frames.  Many pairs of
> frames will be generated, and the distribution of the mean nearest
> neighbour distances (x and y) will be computed.
>
> The code below is my feeble attempt to do the simulation.
> So far as I know, it doesn't work.  Any help appreciated!
> (I am using Mac version of R)
>
> Bill Simpson
>
> # nearest neighbour distance simulation
> # for dynamic noise dots
>
> do.sim<-function(nnoise, nsignal, jump)
> {
> ntotal<-nsignal+nnoise
> x<<-NULL
> y<<-NULL
> x.temp<-0
> y.temp<-0
>
> #generate noise dots
> nx1<-runif(nnoise,0,4095)
> nx2<-runif(nnoise,0,4095)
> ny1<-runif(nnoise,0,4095)
> ny2<-runif(nnoise,0,4095)
>
> #generate signal dots
> sx1<-runif(nsignal,0,4095)
> sx2<-sx1
> sy1<-runif(nsignal,0,4095)
> sy2<-sy1+jump
> sy2<-ifelse(sy2>4095, sy2-4096,sy2) #wrap around
>
> #put noise and signal dots together
> tx1<-c(nx1,sx1)
> tx2<-c(nx2,sx2)
> ty1<-c(ny1,sy1)
> ty2<-c(ny2,sy2)
>
> #compute distance to nearest neighbour (x and y) in frame 2
> #for each dot in frame 1
> for(i in 1:ntotal)
>         {
>         rbest<-2*(4096^2)
>         for(j in 1:ntotal)
>                 {
>                 xd<-tx2[i]-tx1[j]
>                 yd<-ty2[i]-ty1[j]
>                 rr<-xd^2 + yd^2
>                 if(rr<rbest)
>                         {
>                         rbest<-rr
>                         x.temp<-xd
>                         y.temp<-yd
>                         }
>                 }
>         x<<-c(x,x.temp)
>         y<<-c(y,y.temp)
>         }
> }
>
>
> sim<-function(nnoise, nsignal, jump)
> {
> xm<<-NULL
> ym<<-NULL
>
> for(i in 1:10)
>         {
>         do.sim(nnoise, nsignal, jump)
>         xm<<-c(xm,mean(x))
>         ym<<-c(ym,mean(y))
>         }
> }
>
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