On Aug 1, 7:02 am, Jeremy Bailin <astroco...@gmail.com> wrote:
> On Jul 31, 10:50 am, Bennett <juggernau...@gmail.com> wrote:
>
>
>
>> On Jul 31, 7:37 am, Jeremy Bailin <astroco...@gmail.com> wrote:
>
>>> On Jul 30, 7:54 am, Bennett <juggernau...@gmail.com> wrote:
>
>>>> On Jul 29, 11:50 am, Jeremy Bailin <astroco...@gmail.com> wrote:
>
>>>> > On Jul 29, 2:32 am, Brian Larsen <balar...@gmail.com> wrote:
>
>>>> > > We do need some more information but this is just screaming for
>>>> > > histogram. Have a read throughhttp://www.dfanning.com/tips/histogram_tutorial.html
>>>> > > . Using histogram to see which x's are common you can step through
>>>> > > the reverse_indices and see which y's are then common. There is
>>>> > > probably a more graceful way however.
>
>>>> > > Cheers,
>
>>>> > > Brian
>
>>>> > > ------------------------------------------------------------ --------------
>>>> > > Brian Larsen
>>>> > > Boston University
>>>> > > Center for Space Physicshttp://people.bu.edu/balarsen/Home/IDL
>
>>>> > In particular, if you're dealing with integers that don't span too big
>>>> > a range, use HIST_2D and find the maximum element. If you've got
>>>> > floats or a wide range, use UNIQ to turn each into an integer on a
>>>> > small range first.
>
>>>> > -Jeremy.
>
>>>> I think if I were to be working with small datasets....ie not in the
>>>> millions of points I would use something like this
>
>>>> coords = [[10,1],[20,32],[5,7],[6,8],[20,32],[2,14],[20,32],[10,10],
>>>> [3,1],[21,14]]
>
>>>> counter = intarr(9)
>
>>>> FOR i = 0, 8 DO BEGIN
>>>> FOR j = 0, 8 DO BEGIN
>
>>>> IF array_equal(coords[*,i],coords[*,j]) THEN counter[i]++
>
>>>> ENDFOR
>>>> ENDFOR
>
>>>> ;- Histogram to find the max bins (no need to measure anything below 2
>>>> ;- because that would just be a single hit and if all of your pairs
>>>> ;- only occur once then who cares, right?
>>>> hist = histogram(counter, min=2, reverse_indices=ri)
>>>> maxHist = max(hist, mxpos)
>>>> IF maxHist EQ 1 THEN print, 'Each pair occurs no more than once'
>
>>>> ;- Use the reverse indices given by histogram to find out exactly
>>>> ;- where in your counter these maxes are occurring
>>>> array_index = (counter[ri[ri[1]:ri[2]-1]])[0]
>
>>>> ;- Find where counter is equal to the array index determined by
>>>> ;- reverse indices
>>>> max_index = where(counter EQ array_index)
>
>>>> ;- Voila with your max pair
>>>> print, coords[*,max_index[0]]
>
>>>> Which spits out....
>>>> 20 32
>
>>>> This could be tweaked to find the top two or three or whatever as
>>>> well.
>>>> Hope this helps.
>
>>> My version of that would be:
>
>>> min1=min(coords[0,*], max=max1)
>>> min2=min(coords[1,*], max=max2)
>>> arraymap = hist_2d(coords[0,*], coords[1,*], min1=min1, max1=max1,
>>> bin1=1, min2=min2, max2=max2, bin2=1)
>>> maxval = max(arraymap, maxelement)
>>> print, array_indices([max1-min1+1,max2-min2+1], maxelement, /dimen)+
>>> [min1,min2]
>
>>> ...which avoids loops, and is more obvious to me.
>
>>> -Jeremy.
>
>> No loops is all and good...but if you put a decimal in coords like
>> this
>
>> coords = [[10.0,1.0],[20.0,32.3],[5,7],[6,8],[20.0,32.3],[2,14],
>> [20.0,32.3],[10,10],[3,1],[21,14]]
>
>> your code still spits out (20.0 32.0) where it should spit out (20.0
>> 32.3)
>> By the way the code I presented up there should have the following
>> line replaced
>> array_index = (counter[ri[ri[1]:ri[2]-1]])[0]
>> with
>> array_index = (counter[ri[ri[mxpos]:ri[mxpos+1]-1]])[0]
>
> Like I said, if you have floats (or a very large range of integers),
> you should map them into integers first using SORT and UNIQ...
>
> coordsize = size(coords,/dimen)
> coords0_sorted = coords[0,sort(coords[0,*])]
> map0 = uniq(coords0_sorted)
> nmap = n_elements(map0)
> new_coords0 = lonarr(coordsize[1])
> for i=0l,nmap-1 do new_coords0[where(coords[0,*] eq
> coords0_sorted[map0[i]])]=i
>
> ...and the same for coords[1,*]. There's probably a more efficient way
> of doing that, but you get the idea.
>
> -Jeremy.
coords = [[10.0,1.0],[20.0,32.3],[5,7],[6,8],[20.0,32.3],[2,14],
[20.0,32.3],[10,10],[3,1],[21,14]]
sz = size(coords, /dimensions)
result = rebin(coords,2,sz[1],sz[1])
result2 = rebin(reform(coords,2,1,sz[1]),2,sz[1],sz[1])
indices = array_indices(result/result2,where(result/result2 EQ 1))
hist = histogram(indices[2,*])
maxHist = max(hist, mxpos)
print, coords[*,mxpos]
No loops...but definitely limited by size...can't really go with more
than a 7500 indices
|
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