https://github.com/bast/polygons
Fast points-in-polygon test and distances to polygons.
https://github.com/bast/polygons
distance geometry polygon pyo3 rust spacial
Last synced: 6 months ago
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Fast points-in-polygon test and distances to polygons.
- Host: GitHub
- URL: https://github.com/bast/polygons
- Owner: bast
- License: gpl-3.0
- Created: 2017-04-18T10:51:07.000Z (over 8 years ago)
- Default Branch: main
- Last Pushed: 2024-01-31T07:16:51.000Z (over 1 year ago)
- Last Synced: 2024-03-23T13:23:11.497Z (over 1 year ago)
- Topics: distance, geometry, polygon, pyo3, rust, spacial
- Language: Rust
- Homepage:
- Size: 975 KB
- Stars: 12
- Watchers: 4
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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[](https://doi.org/10.5281/zenodo.3825616)
# Polygons: Fast points-in-polygon test and distances to polygons
Computes distances to polygon edges and vertices and can check whether
points are inside/outside.
This library is optimized to perform well with hundreds or thousands of
polygons and thousands or millions of points.
Example timings (190 polygons, 1 M reference points, run on 12th Gen Intel i7-12700T at 4.6 GHz):
- distances to nearest edges: 320 ms
- distances to nearest vertices: 290 ms
- check whether points are inside or outside: 45 ms
## Installation using pip
```
$ pip install polygons
```
## Supported versions
- Python: 3.10 - 3.13
- Operating systems: Linux, macOS, and Windows
## Capabilities
- Check whether points are inside or outside polygons
- Nearest distances to edges
- Nearest distances to vertices
## Recommended citation
If you use this tool in a program or publication, please acknowledge its
author(s):
```bibtex
@misc{polygons,
author = {Bast, Radovan},
title = {Polygons: Fast points-in-polygon test and distances to polygons},
month = {03},
year = {2025},
publisher = {Zenodo},
version = {v0.3.5},
doi = {10.5281/zenodo.3825616},
url = {https://doi.org/10.5281/zenodo.3825616}
}
```
## Python example
```python
import polygons
# polygon_points is a list of lists
# the library has been developed to perform
# with very many polygons - this is just to have a simple example
# in this example the polygons have the same number of points but there
# is no restriction like this, this is only an example
polygon_points = [
[(0.0, 0.0), (1.0, 0.0), (1.0, 1.0), (0.0, 1.0)],
[(0.0, 2.0), (1.0, 2.0), (1.0, 3.0), (0.0, 3.0)],
]
# the more points you compute in one go, the better
# here using two points to make a simple example but if you have many points
# then compute a thousand or a million in one go
# so that the library can parallelize over the points
points = [(0.5, 0.5), (0.5, -0.5)]
# parameters for the tree construction:
# - each tree node has 4 children nodes
# - each leaf collects 4 edges
# you can try different parameters and check the timing
# they (should) have no effect on the results apart from timing
num_edges_children = 4
num_nodes_children = 4
tree = polygons.build_search_tree(
polygon_points, num_edges_children, num_nodes_children
)
inside = polygons.points_are_inside(tree, points)
print(inside) # [True, False]
# indices are the indices of the nearest polygon vertices (counted
# consecutively)
indices, distances = polygons.distances_nearest_vertices(tree, points)
print(indices) # [0, 0]
print(distances) # [0.7071067811865476, 0.7071067811865476]
distances = polygons.distances_nearest_edges(tree, points)
print(distances) # [0.5, 0.5]
indices, distances = polygons.distances_nearest_vertices(
tree, [(0.6, 0.6), (0.5, -0.5)]
)
print(indices) # [2, 0]
print(distances) # [0.5656854249492381, 0.7071067811865476]
```
## References which were used during coding
-
-
-
## Development notes
Running the benchmark:
```
$ cargo test --release -- --ignored --nocapture
```
Python interface inspired by https://github.com/dev-cafe/rustafarian.
Building and testing the Python interface:
```
$ maturin develop
```
## Image
Social media preview generated using https://github.com/qrohlf/trianglify.