Struct fluent_data::algorithm::Algo

pub struct Algo<Point: PartialEq + 'static> { /* private fields */ }

Fits incoming points to a set of balls model.

The algorithm can fit any kind of points in a space that:

• defines the square of the distance between two points,
• defines the weighted center of two points.

use fluent_data::algorithm::Algo;
use fluent_data::model::Model;
use fluent_data::space;

let dataset = vec![
       vec![5., -1.],
       vec![1., 1.],
       vec![11., -9.],
   ];
let algo = Algo::new(space::euclid_dist, space::real_combine);
let mut model = Model::new(space::euclid_dist);
for i in 0..3 {
   algo.fit(&mut model, dataset[i].clone());
}
let mut balls = model.iter_balls();
let first = balls.next().unwrap();
assert_eq!(&vec![6., -4.], first.center());
assert_eq!(f64::sqrt(110.), first.radius());
assert!(first.weight() < 2.001 && first.weight() > 1.999);

Implementations

impl<Point: PartialEq + 'static> Algo<Point>

pub fn new<Dist, Combine>(dist: Dist, combine: Combine) -> Selfwhere
    Dist: Fn(&Point, &Point) -> f64 + 'static,
    Combine: Fn(&Point, f64, &Point, f64) -> Point + 'static,

Creates a new algorithm for the given distance and combination functions.

pub fn fit<'a>(&'a self, model: &'a mut Model<Point>, point: Point)

Fits the incoming points to the given mixture model.