| Simple? problem [message #30081] |
Tue, 09 April 2002 08:49  |
Ivan Valtchanov
Messages: 8
Registered: April 2002
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Junior Member |
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Hi,
I have a small problem concerning a good programming techniques, so here it is:
----------------------
pro test,nx,ny,image
; Make some random X and Y arrays
x = randomu(s,1000)
y = randomu(s,1000)
; now give arbitrary weights for each point
w = randomu(s,1000)/100.0
; take the square
w2=2.0*w*w
; I want to construct a 2-D image with a specified dimension
image = fltarr(nx,ny)
; I want to sum up the contribution of each point as Gaussian
; with width=w to the image pixels
for i=0, nx-1 do begin
xgi = i/float(nx)
dx = x-xgi
for j=0, ny-1 do begin
ygi = j/float(ny)
dy = y-ygi
dr2 = dx*dx+dy*dy
arg = -dr2/w2 > (-20.0) ; to avoid overflows
image[i,j] = total(exp(arg))
endfor
endfor
return
end
---------------------------
This is obviously quite unoptimised - two cycles etc. Do you have any ideas, references or do you know if it is already solved in IDL?
I have looked for something similar in David Fanning pages and IDL astronomical libraries but I couldn't find something to adapt, maybe I have missed it?
Thanks.
Ivan V.
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| Re: Simple? problem [message #30190 is a reply to message #30081] |
Thu, 11 April 2002 02:55  |
Jaco van Gorkom
Messages: 97
Registered: November 2000
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Member |
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"Ivan Valtchanov" <ivanv@discovery.saclay.cea.fr> wrote in message
news:20020410101353.334cb503.ivanv@discovery.saclay.cea.fr.. .
> To describe what is my objective: this is an adaptive kernel
> smoothing, where the width of the kernel is locally variable.
> I would like to apply it to scattered points and not (for the
> moment) to images.
>
> Hope this helps?
Ok, I see now why the code is like that. Nothing really smart
comes to mind, apart from vectorizing the inner loop as in my
previous post. Of course, if the number of scattered points is
generally smaller than the number of rows/points in the image
then a loop over the points, adding their gaussian contribution to
the whole image, might be more efficient.
Cheers,
jaco
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