R help - Dec 2009 - Help with Nested loop - very slow, can I use an apply?

Hi there

I have two tables, with longitudinal and latitudinal coordinates. what I
want is a cross table between each coordinate, to find the distance between
each building and different landmarks


I currently have this nested loop which is fine for when i have 10 stores of
interest, against 200 other landmarks and uses pythagarus to find the
distance


for(i in 1:nrow(store_c)){
	landmark_store_cross_tab$foo=landmark_c$landmark_name
	for (j in 1:nrow(landmark_c)){
	landmark_store_cross_tab[j,i+1]=sqrt((landmark_c$x[j]-store_c$x[i])^2
		+(landmark_c$y[j]-store_c$y[i])^2)/1000
}
names(landmark_store_cross_tab)[i+1]=store_c$store_name[i]
}

can someone suggest how I can make this faster?


I am hoping to use one of the apply functions

Thanks

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From an old post by Gabor
http://tolstoy.newcastle.edu.au/R/help/04/01/0147.html

   
apply 
(outer 
(landmark_c,t(store_c),"-"),c(1,4),function(x)sqrt(sum(diag(x*x))))

On 7 Dec 2009, at 10:58PM, dolar wrote:
>
> Hi there
>
> I have two tables, with longitudinal and latitudinal coordinates.  
> what I
> want is a cross table between each coordinate, to find the distance  
> between
> each building and different landmarks
>
>
> I currently have this nested loop which is fine for when i have 10  
> stores of
> interest, against 200 other landmarks and uses pythagarus to find the
> distance
>
>
> for(i in 1:nrow(store_c)){
> 	landmark_store_cross_tab$foo=landmark_c$landmark_name
> 	for (j in 1:nrow(landmark_c)){
> 	landmark_store_cross_tab[j,i+1]=sqrt((landmark_c$x[j]-store_c$x[i])^2
> 		+(landmark_c$y[j]-store_c$y[i])^2)/1000
> }
> names(landmark_store_cross_tab)[i+1]=store_c$store_name[i]
> }
>
> can someone suggest how I can make this faster?
>
>
> I am hoping to use one of the apply functions
>
> Thanks
>
> -- 
> View this message in context:
http://n4.nabble.com/Help-with-Nested-loop-very-slow-can-I-use-an-apply-tp954979p954979.html
> Sent from the R help mailing list archive at Nabble.com.
>
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