Comments (7)
btw, in python, you can do this easily by using query_ball_point, see:
https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.KDTree.query_ball_point.html#scipy.spatial.KDTree.query_ball_point
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@jefferis I just ran into the same problem. I am trying to implement a particular 2D clustering algorithm that would benefit from locating "most dense" areas. I cannot spare storing a full matrix (100 million points), but I could use an array listing number of closest points within a certain radius.
I will try to look into making this happen and doing a PR if I can...
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OK. Thank you @romanzenka. I'm happy to answer questions.
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PS @romanzenka if you found a patch against https://github.com/jefferis/RANN2 considerably easier (it uses RCpp) then I might consider a CRAN submission for that.
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@jefferis Okay, I will look into RANN2 first.
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I sent a preliminary PR into RANN2 just to show what I'm thinking - with your approval I can finish this up in a more complete fashion.
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Related Issues (17)
- nn2 should check length query/data explicitly
- release RANN1 to CRAN HOT 6
- fix bug in checking query vs data dimensions HOT 1
- bd tree HOT 16
- nn2 docs say it returns a data.frame (not a matrix)
- weighted distance HOT 3
- Remove register keyword from ANN source for CRAN
- points to line distance
- Solaris compile error ERR HOT 1
- Don't use CPPFLAGS for compiler flags HOT 1
- Please ship declarations in inst/include so we can linkingTo your c++ functions HOT 2
- tic::use_tic() for automatic deployment of pkgdown and testing on AppVeyor HOT 6
- Consider provinding L1 metric in the RANN package
- Support other Minkowski metrics HOT 20
- RANN.L1 remote dependency HOT 11
- Objects with zero distance HOT 1
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