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How to speed up kernel density smoothing for many data points [message #86130]

Thu, 10 October 2013 05:22

jacobsvensmark
Messages: 7
Registered: October 2013

Junior Member

Okay so I have a long array of N 2D points: x = fltarr(N,2) (as exemplified below). For each point x(i,*) I need to input the distance to all other points into my K function: K(xi-x), sum together K for each point, square root and put into my final function f1(i).

I guess I need help both making the input xi-x faster, as well as making K run faster. I tried with 'REPLICATE_INPLACE' which helped some, but I am out of ideas....

PRO test_kernel

N = 1000000
r = 2*randomn(seed,N)
v = 2*randomu(seed,N)
x = [[r],[v]]

; Just a smoothing parameter, unimportant...
hopt = 6.24/(N^(1./6.))*sqrt((stddev(x(*,0))^2+stddev(x(*,1))^2)/2. )

; Slow loop, where I need help
f1 = fltarr(N)
xi = fltarr(N,2)
for i=0L,N-1 do begin
REPLICATE_INPLACE, xi, x(i,0), 1, [1,0]
REPLICATE_INPLACE, xi, x(i,1), 1, [0,1]
f1(i) = 1./float(N) * total(1./(hopt^2)*K(xi-x,hopt))
endfor

END

FUNCTION K,tvec,h
t = vec_norm(tvec)/h
aa = where(t ge 1.,n0)
bb = where(t lt 1.,nt)
RES = fltarr(n_elements(t))
if n0 ne 0 then RES(aa) = 0.
if nt ne 0 then RES(bb) = 4./!Pi*(1.-t(bb)^2)^3
RETURN,res
END

Thanks, Jacob

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[Message index]

		How to speed up kernel density smoothing for many data points By: jacobsvensmark on Thu, 10 October 2013 05:22
		Re: How to speed up kernel density smoothing for many data points By: Moritz Fischer on Thu, 10 October 2013 05:55
		Re: How to speed up kernel density smoothing for many data points By: Moritz Fischer on Thu, 10 October 2013 06:03
		Re: How to speed up kernel density smoothing for many data points By: jacobsvensmark on Thu, 10 October 2013 06:29
		Re: How to speed up kernel density smoothing for many data points By: Moritz Fischer on Thu, 10 October 2013 06:48

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