Timeline for Selecting for 2D points that are within a threshold distance of an upper- and lower-bound number of points
Current License: CC BY-SA 3.0
9 events
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| Oct 27, 2013 at 20:40 | comment | added | RTaylor | Ah I see, I misunderstood your plot. Would it work faster to use the Nearest specification ssch is referring to? It seems like that does some kind of binning steps and works more quickly than computing the distance from one point to every other point. | |
| Oct 27, 2013 at 20:35 | comment | added | Dr. belisarius | @RTaylor That's what I've done. For all disks, h[min, max] is the number of points between min and max :) | |
| Oct 27, 2013 at 20:34 | comment | added | RTaylor | For the selection part, I then want to select points where their corresponding disks contain at least $k_a$ points and at most $k_b$ points. Is this clearer? Apologies again. | |
| Oct 27, 2013 at 20:33 | comment | added | RTaylor | I mean that we place a disk of radius $r$ on the plane centered at each point. I'm then looking to generate a distribution for the number of points contained in a disk by looking at all disks. | |
| Oct 27, 2013 at 20:31 | comment | added | Dr. belisarius | @RTaylor "for each point" or "for one point" ? | |
| Oct 27, 2013 at 20:26 | comment | added | RTaylor | This is also great, but I think I was unclear in my writing, and I apologize. I meant a distribution for the count of the number of points within a disk centered on each point. So it should be a simple 1D curve or histogram. | |
| Oct 27, 2013 at 20:17 | comment | added | Dr. belisarius |
Perhaps there is a way for computing h[] faster. Let's see.
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| Oct 27, 2013 at 20:15 | history | edited | Dr. belisarius | CC BY-SA 3.0 |
added 39 characters in body
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| Oct 27, 2013 at 20:06 | history | answered | Dr. belisarius | CC BY-SA 3.0 |