A Rust implementation of the Polylabel algorithm
The orange dot is the polygon centroid. The teal dot is the ideal label position. Red boxes show the search space.
You can generate this visualisation yourself by cloning this repo, switching to the visualise
branch, and opening the visualise.ipynb
Jupyter notebook, then stepping through the cells. You can also easily visualise a Polygon of your own using the notebook.
```rust extern crate polylabel; use polylabel::polylabel;
extern crate geo; use geo::{Point, LineString, Polygon};
let coords = vec![ (0.0, 0.0), (4.0, 0.0), (4.0, 1.0), (1.0, 1.0), (1.0, 4.0), (0.0, 4.0), (0.0, 0.0) ]; let poly = Polygon::new(coords.into(), vec![]); let label_pos = polylabel(&poly, &0.10); // Point(0.5625, 0.5625) ```
A command-line tool is available: cargo install polylabel_cmd
. This enables the polylabel
command, which takes a GeoJSON file as input, as well as an optional (-t / --tolerance
) tolerance value. See more at crates.io.
https://docs.rs/polylabel
Call polylabel_ffi
with the following three mandatory arguments:
- Array
(a struct with two fields):
- data
: a void pointer to an array of two-element c_double
arrays, each of which represents a point on the exterior Polygon shell)
- len
: the length of the data
array, a size_t
- WrapperArray
(a struct with two fields):
- data
: a void pointer to an array of Array
s, each entry representing an interior Polygon ring. Empty if there are no rings.
- len
: the length of the data
array, a size_t
. 0 if it's empty.
- tolerance
, a c_double
The function returns a struct with two c_double
fields:
- x_pos
- y_pos
A Python example is available in ffi.py
An auto-generated header file is available at include/header.h
Using a 3.4 GHz Core i7, finding a label position on a ~9k-vertex polygon (representing the Norwegian mainland) using a tolerance of 1.0
takes around 35 ms. Depending upon the dimensions of your polygon(s), you may require a higher tolerance (i.e. a smaller number). See here for some guidance on the accuracy provided by each decimal place.
Binary libs for:
- x86_64
*nix (built using manylinux1
, thus easy to include in Python 2.7 / 3.5 / 3.6 wheels) and OS X
- i686
and x86_64
Windows
are available in releases.