ofxSpatialHash

Fast nearest neighbour lookup for 2d particle systems

Tests

Debug Build

World size 1000 x 1000. Grid size 10. Search radius 150.
Adding ofVec2f as pointers ofxSpatialHash::addPoint()

Points	Milliseconds
100	0.054
1,000	0.302
10,000	1.245
50,000	5.035
100,000	9.392
500,000	47.302
1,000,000	95.738
10,000,000	995.733

Nearest neighbour search. Milliseconds.

Points	Hash glm	Hash ofVec2f	Naive glm	Naive ofVec2f
100	0.004	0.004	0.012	0.008
1,000	0.018	0.015	1.204	0.573
10,000	0.136	0.105	104.703	51.006
50,000	0.683	0.548	2609.96	1305.25
100,000	1.463	1.087	10890.3	5574.67
500,000	7.769	5.615	330835	168685
1,000,000	19.107	12.219	n/a	n/a
10,000,000	207.801	129.039	n/a	n/a

Release Build

Adding ofVec2f as pointers ofxSpatialHash::addPoint()

Points	Milliseconds
100	0.01
1,000	0.07
10,000	0.241
50,000	0.968
100,000	1.582
500,000	12.341
1,000,000	14.337
10,000,000	268.345

Nearest neighbour search. Milliseconds.

Points	Hash glm	Hash ofVec2f	Naive glm	Naive ofVec2f
100	0	0	0.001
1,000	0	0	0.14	0.251
10,000	0.005	0.005	19.369	25.852
50,000	0.043	0.057	326.108	295.424
100,000	0.154	0.143	1103.8	1029.82
500,000	0.828	0.572	28465.3	30356.9
1,000,000	1.707	1.711	n/a	n/a
10,000,000	23.678	23.955	n/a	n/a

License

MIT License

Installation

Git clone or copy into openFrameworks/addons/ folder.

Usage

First use

First initialise the hash with the correct dimensions ofxSpatialHash::init()
Points can be added to the hash with ofxSpatialHash::addPoint(float x, float y, T value)
Search for points getNearestPoints(float x, float y, float radius) and test for distance if necessary

Update points

Clear hash ofxSpatialHash::clear()
Add points ofxSpatialHash::addPoint(float x, float y, T value)

Example

All points contained in the green squares will be returned from a call to ofxSpatialHash::getNearestPoints(float x, float y, float radius)
Users need to test the returned points to see if they are inside the radius with a call to ofVec2f::distance or glm::distaance

Known issues

• 2d only.
• Points must be positive in x and y.
• The spatial hash top left corner is anchored to 0,0.
• The class needs a predefined space width and height. Points outside this space will cause errors.
• The returned points from a nearest neighbour search will contain points outside of the search radius.
• An extra distance check provided by the user is needed to make sure you have points contained inside the radius.