[R] Converting nested "for" loops to an "apply" function(s)

[Kurt Newman]

Resending.  Previous message was truncated.  Sorry for possible confusion.

----------------------------------------
> From: km_newman at hotmail.com
> To: r-help at r-project.org
> Date: Sat, 9 Aug 2008 18:25:47 -0400
> Subject: [R] Converting nested "for" loops to an "apply" function(s)
> 
> 
> Hello,
> 
> I would like to know more about how to use the "apply" family and have attempted to convert nested "for" loops in example code from Contributed Documentation ("The Friendly Beginners' R Course” by Toby Marthews (ZIP, 2007-03-01)") to an "apply" function(s).  The relevant code is:
> 
> distances=c(51,65,175,196,197,125,10,56)	#distances of 8 houses from the town centre in m
> bearings=c(10,8,210,25,74,128,235,335)	#bearings of the houses in degrees
> 
> xpos=distances*sin(bearings*pi/180)		#in sin and cos the argument MUST be in radians
> ypos=distances*cos(bearings*pi/180)		
> 
> numpoints=length(distances)
> nnd=rep(sqrt(2*400*400),times=numpoints)	#start with the maximum possible distance
> for (i in 1:numpoints) {	
>  for (j in 1:numpoints) {
>   if (i!=j) {		
>    diffx=abs(xpos[i]-xpos[j])
>    diffy=abs(ypos[i]-ypos[j])
>    nd=sqrt((diffx^2)+(diffy^2))
>    if (nd < nnd[i]) {nnd[i]=nd}
  }
 }
}
print(data.frame(xpos,ypos,nnd))

My attempts to convert the nested "for" loops to an "apply" function(s) have not been successful.  I would like to know how to convert the code to increase my knowledge of R programming and to evaluate operational efficiency of the different strategies.

Thank you in advance for your comments / suggestions.

Kurt Newman



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