octree
| Crates.io | octree |
| lib.rs | octree |
| version | 0.1.0 |
| source | src |
| created_at | 2020-02-06 10:32:36.679699 |
| updated_at | 2020-03-10 09:34:27.208075 |
| description | Octree algorithm for nearest neighbor search in 3D space |
| homepage | https://github.com/ybyygu/rust-octree |
| repository | https://github.com/ybyygu/rust-octree |
| max_upload_size | |
| id | 205452 |
| size | 3,874,981 |
Wenping Guo (ybyygu)
documentation
README
This is my first crate for learning Rust.
Performance
test data: examples/data/3wu2.xyz, coordinates of 51053 particles extracted from a PDB file 3wu2 1
How to to reproduce
rust-octree (v0.0.6):
RAYON_NUM_THREADS=1 cargo run --example demo --release
scipy-ckdtree(v1.3.2):
ipython> edit scripts/bench.py
ipython> %timeit -n 10 run_test()
Related crates
References
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Behley, J.; Steinhage, V.; Cremers, A. B. Efficient Radius Neighbor Search in Three-Dimensional Point Clouds. In 2015 IEEE International Conference on Robotics and Automation (ICRA); 2015; pp 3625–3630.